Introduction to Semantic Web Rules & Policies

92
Introduction to Semantic Web Rules & Policies Daniel Olmedilla L3s Research Center / Hannover University Programa de Postgrado en Ingeniería Informática y de Telecomunicación (Máster y Doctorado) Universidad Autónoma de Madrid, 3 rd April, 2008

description

Introduction to Semantic Web Rules & Policies. Daniel Olmedilla L3s Research Center / Hannover University Programa de Postgrado en Ingeniería Informática y de Telecomunicación (Máster y Doctorado) Universidad Autónoma de Madrid, 3 rd April, 2008. About this lecture Why this lecture?. - PowerPoint PPT Presentation

Transcript of Introduction to Semantic Web Rules & Policies

Page 1: Introduction to  Semantic Web Rules & Policies

Introduction to Semantic Web Rules amp

PoliciesDaniel Olmedilla

L3s Research Center Hannover University

Programa de Postgrado en Ingenieriacutea Informaacutetica y de Telecomunicacioacuten (Maacutester y Doctorado)

Universidad Autoacutenoma de Madrid 3rd April 2008

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 2

About this lectureWhy this lecture

bull Lot of noise about the Semantic Web Lot of relevant papers and work on Semantic Web in last

years

bull Techniques and tools can be used in the context of adaptivity lifelong learning and competence development

bull Intelligent systemsagents need to be guided

bull Software agents Development is expensive Are static Are unflexible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 3

About this lecture Objectives

This lecture is intended to provide reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 4

About this lectureDisclaimer

The objective is to present the main ideas

not a full explanation of the theory that lays behind

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 5

About this lectureInteractive

And also important This is not

a conference presentation a monologue

Each module partially builds on concepts from previous modules

Exercises are provided in order to strength understanding

You are also encouraged to interrupt and

ASK Questionswhenever you need it

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 6

About this lectureThe slides

Slides are wordy so they can be easily understood offline after the tutorial

More definitions and references are available in notes and hidden slides

Lecture is available from

httpwwwL3Sde~olmedillapresentations200820080403_UAM_Masterppt

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 7

OutlineLecture Overview

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 8

OutlineIntroduction

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 9

IntroductionWarming Up Problem

Institutions companies and people need to control the way they Make business Take decisions Offer their assets Etc hellip

Computers help us on our daily work performing tasks that we cannot perform (or we do it worse) automatically on our behalf

But generally we need to control how decisions and actions are taken

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 10

IntroductionWhat is a policy

In a very broad way a policy is defined as

a statement defining the behaviour of an entity

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 11

IntroductionPolicies are everywhere

B2B contracts eg quantity flexible contracts late delivery penalties

etc Negotiation

eg rules associated with auction mechanisms Security

eg access control policies Privacy

Information Collection Policies (aka ldquo P3P Privacy Policiesrdquo)

Obfuscation Policies Workflow management

What to do under different sets of conditions Context aware computing

What service to invoke to access a particular contextual attribute

Context-sensitive preferences[ by Norman Sadeh Semantic Web Policy Workshop panel ISWC 2005 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 12

Exercise 1Specify your own policies

How do you decide (in general terms) which transportation you use to come to the university

whether you share your

Homework

Pictures from your holidays in Hawaii

Your famous report so many companies are willing to pay for

whether you take a private call when being at work

which tasks you perform everyday at work

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 13

Exercise 1Problem (I)

Now imagine a system application or software agent couldshould decide on your behalf How do you tell such an agent how it should do it

The way we make business take decisions etc Is dynamic that is often changesEvolves with the time

We cannot re-code re-compile re-install a new software agent every time we change the way we take decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 14

Exercise 1Problem (II)

Furthermore we need that the system acting on our behalfdoes what we want

How do we tell it What if we make a mistake and tell

something wrong is contextual that is depends on many factors is ldquointelligentrdquo (does things as we would do

them) is not reserved only to millionaires

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 15

IntroductionThe goal

Build applicationsagents whereBehaviour is flexible

Can be changedupdated without re-coding re-compiling re-

installing etchellip In a costless manner

Can be managed by administratorsusers without needing to be computer experts

Can be understood by normal users

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 16

OutlineWhy the Semantic Web

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 17

Why the Semantic Web HTML in your browser

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 18

Why the Semantic Web HTML Markup

lth2gt Topics lth2gtltpgtEducational Principles ltbrgtKnowledge Management ltbrgtEducation Process Modeling ltbrgtLearning Design ltbrgtCompetence Development ltbrgthellipltpgtlth2gt Lecturers lth2gtltpgtAlbert Angehrn INSEAD France ltbrgtBoyan Bontchev Sofia University Bulgaria ltbrgtAlexandar Dimov Sofia University Bulgaria ltbrgtDai Griffiths University of Bolton United Kingdom ltbrgthellipltpgt

Markup forpresentation only

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 19

Why the Semantic Web HTML Limitations

HTML deals only with formatting of data

It does not provide information about the data it contains

Query engines do a great job but queries like Give me the list of subjects that the winter school will

deal with Return the affiliations of the lecturers in the winter school

are not possible on the current Web

Search on current Web is based on syntactic matching

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 20

Why the Semantic Web Current Web

bull Downloadable Resources identified by URLs untyped

bull Links href src limited non-descriptive

bull User Exciting world

semantics of the resource however gleaned from content

bull Machine processable Very little information available

significance of the links only evident from the context around the anchor [Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 21

Why the Semantic Web Semantic Web Definition

ldquoThe Semantic Web is an extension of the current web in which information is given well-defined meaning better enabling computers and people to work in cooperationrdquo

Tim Berners-Lee James Hendler Ora LassilaThe Semantic Web Scientific American May 17 2001

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 22

Why the Semantic Web The Semantic Web

bull Resources (any resource) Globally Identified by URIs Extensible Relational

bull Links Identified by URIs Extensible Relational

bull User Even more exciting world

richer user experience bull Machine

More processable information is available (Data Web)

bull Computers and people Work learn and exchange

knowledge effectively

[Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 23

OutlineLast Year Lecture

Daniel Olmedilla

Last Year LectureThe Semantic Web Stack

XML Namespaces

URI UnicodeApr 3rd 2008 24Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF foundations

XML Namespaces

URI Unicode

bull Share basic syntax with other Web standards URI unique identifiers Namespaces organizegroup identifiers XML reuse syntax and data types

Apr 3rd 2008 25Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Model

XML Namespaces

URI Unicode

bull Data model facility Evolution of hyperlinks Open extensible (open world assumption) Graph model Easy interconnection of

distributed data

Apr 3rd 2008 26Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Schema

XML Namespaces

URI Unicode

bull Facility for shared vocabulary Properties to share link types Classes to share resource types

Apr 3rd 2008 27Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureSPARQL

XML Namespaces

URI Unicode

bull Querying facility Flexible pattern matching No reasoning

Some reasoning support via entailment regime

Apr 3rd 2008 28Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureOWL Description Logic

XML Namespaces

URI Unicode

bull Reasoning facility Support complex ontology models Reasoning on class and instance level

on

tolo

gy

com

ple

xity

amount of data

Apr 3rd 2008 29Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureThe Semantic Web Stack

XML Namespaces

URI Unicode

Part of this year lecture

Apr 3rd 2008 30Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureWarning (or clarification )

bull OWL Web Ontology Language

Ontology = OWL

Apr 3rd 2008 31Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 32

OutlineRule-Based Representation amp Reasoning

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

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Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 2: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 2

About this lectureWhy this lecture

bull Lot of noise about the Semantic Web Lot of relevant papers and work on Semantic Web in last

years

bull Techniques and tools can be used in the context of adaptivity lifelong learning and competence development

bull Intelligent systemsagents need to be guided

bull Software agents Development is expensive Are static Are unflexible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 3

About this lecture Objectives

This lecture is intended to provide reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 4

About this lectureDisclaimer

The objective is to present the main ideas

not a full explanation of the theory that lays behind

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 5

About this lectureInteractive

And also important This is not

a conference presentation a monologue

Each module partially builds on concepts from previous modules

Exercises are provided in order to strength understanding

You are also encouraged to interrupt and

ASK Questionswhenever you need it

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 6

About this lectureThe slides

Slides are wordy so they can be easily understood offline after the tutorial

More definitions and references are available in notes and hidden slides

Lecture is available from

httpwwwL3Sde~olmedillapresentations200820080403_UAM_Masterppt

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 7

OutlineLecture Overview

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 8

OutlineIntroduction

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 9

IntroductionWarming Up Problem

Institutions companies and people need to control the way they Make business Take decisions Offer their assets Etc hellip

Computers help us on our daily work performing tasks that we cannot perform (or we do it worse) automatically on our behalf

But generally we need to control how decisions and actions are taken

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 10

IntroductionWhat is a policy

In a very broad way a policy is defined as

a statement defining the behaviour of an entity

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 11

IntroductionPolicies are everywhere

B2B contracts eg quantity flexible contracts late delivery penalties

etc Negotiation

eg rules associated with auction mechanisms Security

eg access control policies Privacy

Information Collection Policies (aka ldquo P3P Privacy Policiesrdquo)

Obfuscation Policies Workflow management

What to do under different sets of conditions Context aware computing

What service to invoke to access a particular contextual attribute

Context-sensitive preferences[ by Norman Sadeh Semantic Web Policy Workshop panel ISWC 2005 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 12

Exercise 1Specify your own policies

How do you decide (in general terms) which transportation you use to come to the university

whether you share your

Homework

Pictures from your holidays in Hawaii

Your famous report so many companies are willing to pay for

whether you take a private call when being at work

which tasks you perform everyday at work

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 13

Exercise 1Problem (I)

Now imagine a system application or software agent couldshould decide on your behalf How do you tell such an agent how it should do it

The way we make business take decisions etc Is dynamic that is often changesEvolves with the time

We cannot re-code re-compile re-install a new software agent every time we change the way we take decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 14

Exercise 1Problem (II)

Furthermore we need that the system acting on our behalfdoes what we want

How do we tell it What if we make a mistake and tell

something wrong is contextual that is depends on many factors is ldquointelligentrdquo (does things as we would do

them) is not reserved only to millionaires

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 15

IntroductionThe goal

Build applicationsagents whereBehaviour is flexible

Can be changedupdated without re-coding re-compiling re-

installing etchellip In a costless manner

Can be managed by administratorsusers without needing to be computer experts

Can be understood by normal users

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 16

OutlineWhy the Semantic Web

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 17

Why the Semantic Web HTML in your browser

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 18

Why the Semantic Web HTML Markup

lth2gt Topics lth2gtltpgtEducational Principles ltbrgtKnowledge Management ltbrgtEducation Process Modeling ltbrgtLearning Design ltbrgtCompetence Development ltbrgthellipltpgtlth2gt Lecturers lth2gtltpgtAlbert Angehrn INSEAD France ltbrgtBoyan Bontchev Sofia University Bulgaria ltbrgtAlexandar Dimov Sofia University Bulgaria ltbrgtDai Griffiths University of Bolton United Kingdom ltbrgthellipltpgt

Markup forpresentation only

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 19

Why the Semantic Web HTML Limitations

HTML deals only with formatting of data

It does not provide information about the data it contains

Query engines do a great job but queries like Give me the list of subjects that the winter school will

deal with Return the affiliations of the lecturers in the winter school

are not possible on the current Web

Search on current Web is based on syntactic matching

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 20

Why the Semantic Web Current Web

bull Downloadable Resources identified by URLs untyped

bull Links href src limited non-descriptive

bull User Exciting world

semantics of the resource however gleaned from content

bull Machine processable Very little information available

significance of the links only evident from the context around the anchor [Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 21

Why the Semantic Web Semantic Web Definition

ldquoThe Semantic Web is an extension of the current web in which information is given well-defined meaning better enabling computers and people to work in cooperationrdquo

Tim Berners-Lee James Hendler Ora LassilaThe Semantic Web Scientific American May 17 2001

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 22

Why the Semantic Web The Semantic Web

bull Resources (any resource) Globally Identified by URIs Extensible Relational

bull Links Identified by URIs Extensible Relational

bull User Even more exciting world

richer user experience bull Machine

More processable information is available (Data Web)

bull Computers and people Work learn and exchange

knowledge effectively

[Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 23

OutlineLast Year Lecture

Daniel Olmedilla

Last Year LectureThe Semantic Web Stack

XML Namespaces

URI UnicodeApr 3rd 2008 24Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF foundations

XML Namespaces

URI Unicode

bull Share basic syntax with other Web standards URI unique identifiers Namespaces organizegroup identifiers XML reuse syntax and data types

Apr 3rd 2008 25Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Model

XML Namespaces

URI Unicode

bull Data model facility Evolution of hyperlinks Open extensible (open world assumption) Graph model Easy interconnection of

distributed data

Apr 3rd 2008 26Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Schema

XML Namespaces

URI Unicode

bull Facility for shared vocabulary Properties to share link types Classes to share resource types

Apr 3rd 2008 27Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureSPARQL

XML Namespaces

URI Unicode

bull Querying facility Flexible pattern matching No reasoning

Some reasoning support via entailment regime

Apr 3rd 2008 28Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureOWL Description Logic

XML Namespaces

URI Unicode

bull Reasoning facility Support complex ontology models Reasoning on class and instance level

on

tolo

gy

com

ple

xity

amount of data

Apr 3rd 2008 29Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureThe Semantic Web Stack

XML Namespaces

URI Unicode

Part of this year lecture

Apr 3rd 2008 30Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureWarning (or clarification )

bull OWL Web Ontology Language

Ontology = OWL

Apr 3rd 2008 31Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 32

OutlineRule-Based Representation amp Reasoning

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 3: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 3

About this lecture Objectives

This lecture is intended to provide reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 4

About this lectureDisclaimer

The objective is to present the main ideas

not a full explanation of the theory that lays behind

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 5

About this lectureInteractive

And also important This is not

a conference presentation a monologue

Each module partially builds on concepts from previous modules

Exercises are provided in order to strength understanding

You are also encouraged to interrupt and

ASK Questionswhenever you need it

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 6

About this lectureThe slides

Slides are wordy so they can be easily understood offline after the tutorial

More definitions and references are available in notes and hidden slides

Lecture is available from

httpwwwL3Sde~olmedillapresentations200820080403_UAM_Masterppt

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 7

OutlineLecture Overview

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 8

OutlineIntroduction

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 9

IntroductionWarming Up Problem

Institutions companies and people need to control the way they Make business Take decisions Offer their assets Etc hellip

Computers help us on our daily work performing tasks that we cannot perform (or we do it worse) automatically on our behalf

But generally we need to control how decisions and actions are taken

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 10

IntroductionWhat is a policy

In a very broad way a policy is defined as

a statement defining the behaviour of an entity

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 11

IntroductionPolicies are everywhere

B2B contracts eg quantity flexible contracts late delivery penalties

etc Negotiation

eg rules associated with auction mechanisms Security

eg access control policies Privacy

Information Collection Policies (aka ldquo P3P Privacy Policiesrdquo)

Obfuscation Policies Workflow management

What to do under different sets of conditions Context aware computing

What service to invoke to access a particular contextual attribute

Context-sensitive preferences[ by Norman Sadeh Semantic Web Policy Workshop panel ISWC 2005 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 12

Exercise 1Specify your own policies

How do you decide (in general terms) which transportation you use to come to the university

whether you share your

Homework

Pictures from your holidays in Hawaii

Your famous report so many companies are willing to pay for

whether you take a private call when being at work

which tasks you perform everyday at work

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 13

Exercise 1Problem (I)

Now imagine a system application or software agent couldshould decide on your behalf How do you tell such an agent how it should do it

The way we make business take decisions etc Is dynamic that is often changesEvolves with the time

We cannot re-code re-compile re-install a new software agent every time we change the way we take decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 14

Exercise 1Problem (II)

Furthermore we need that the system acting on our behalfdoes what we want

How do we tell it What if we make a mistake and tell

something wrong is contextual that is depends on many factors is ldquointelligentrdquo (does things as we would do

them) is not reserved only to millionaires

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 15

IntroductionThe goal

Build applicationsagents whereBehaviour is flexible

Can be changedupdated without re-coding re-compiling re-

installing etchellip In a costless manner

Can be managed by administratorsusers without needing to be computer experts

Can be understood by normal users

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 16

OutlineWhy the Semantic Web

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 17

Why the Semantic Web HTML in your browser

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 18

Why the Semantic Web HTML Markup

lth2gt Topics lth2gtltpgtEducational Principles ltbrgtKnowledge Management ltbrgtEducation Process Modeling ltbrgtLearning Design ltbrgtCompetence Development ltbrgthellipltpgtlth2gt Lecturers lth2gtltpgtAlbert Angehrn INSEAD France ltbrgtBoyan Bontchev Sofia University Bulgaria ltbrgtAlexandar Dimov Sofia University Bulgaria ltbrgtDai Griffiths University of Bolton United Kingdom ltbrgthellipltpgt

Markup forpresentation only

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 19

Why the Semantic Web HTML Limitations

HTML deals only with formatting of data

It does not provide information about the data it contains

Query engines do a great job but queries like Give me the list of subjects that the winter school will

deal with Return the affiliations of the lecturers in the winter school

are not possible on the current Web

Search on current Web is based on syntactic matching

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 20

Why the Semantic Web Current Web

bull Downloadable Resources identified by URLs untyped

bull Links href src limited non-descriptive

bull User Exciting world

semantics of the resource however gleaned from content

bull Machine processable Very little information available

significance of the links only evident from the context around the anchor [Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 21

Why the Semantic Web Semantic Web Definition

ldquoThe Semantic Web is an extension of the current web in which information is given well-defined meaning better enabling computers and people to work in cooperationrdquo

Tim Berners-Lee James Hendler Ora LassilaThe Semantic Web Scientific American May 17 2001

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 22

Why the Semantic Web The Semantic Web

bull Resources (any resource) Globally Identified by URIs Extensible Relational

bull Links Identified by URIs Extensible Relational

bull User Even more exciting world

richer user experience bull Machine

More processable information is available (Data Web)

bull Computers and people Work learn and exchange

knowledge effectively

[Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 23

OutlineLast Year Lecture

Daniel Olmedilla

Last Year LectureThe Semantic Web Stack

XML Namespaces

URI UnicodeApr 3rd 2008 24Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF foundations

XML Namespaces

URI Unicode

bull Share basic syntax with other Web standards URI unique identifiers Namespaces organizegroup identifiers XML reuse syntax and data types

Apr 3rd 2008 25Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Model

XML Namespaces

URI Unicode

bull Data model facility Evolution of hyperlinks Open extensible (open world assumption) Graph model Easy interconnection of

distributed data

Apr 3rd 2008 26Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Schema

XML Namespaces

URI Unicode

bull Facility for shared vocabulary Properties to share link types Classes to share resource types

Apr 3rd 2008 27Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureSPARQL

XML Namespaces

URI Unicode

bull Querying facility Flexible pattern matching No reasoning

Some reasoning support via entailment regime

Apr 3rd 2008 28Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureOWL Description Logic

XML Namespaces

URI Unicode

bull Reasoning facility Support complex ontology models Reasoning on class and instance level

on

tolo

gy

com

ple

xity

amount of data

Apr 3rd 2008 29Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureThe Semantic Web Stack

XML Namespaces

URI Unicode

Part of this year lecture

Apr 3rd 2008 30Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureWarning (or clarification )

bull OWL Web Ontology Language

Ontology = OWL

Apr 3rd 2008 31Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 32

OutlineRule-Based Representation amp Reasoning

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 4: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 4

About this lectureDisclaimer

The objective is to present the main ideas

not a full explanation of the theory that lays behind

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 5

About this lectureInteractive

And also important This is not

a conference presentation a monologue

Each module partially builds on concepts from previous modules

Exercises are provided in order to strength understanding

You are also encouraged to interrupt and

ASK Questionswhenever you need it

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 6

About this lectureThe slides

Slides are wordy so they can be easily understood offline after the tutorial

More definitions and references are available in notes and hidden slides

Lecture is available from

httpwwwL3Sde~olmedillapresentations200820080403_UAM_Masterppt

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 7

OutlineLecture Overview

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 8

OutlineIntroduction

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 9

IntroductionWarming Up Problem

Institutions companies and people need to control the way they Make business Take decisions Offer their assets Etc hellip

Computers help us on our daily work performing tasks that we cannot perform (or we do it worse) automatically on our behalf

But generally we need to control how decisions and actions are taken

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 10

IntroductionWhat is a policy

In a very broad way a policy is defined as

a statement defining the behaviour of an entity

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 11

IntroductionPolicies are everywhere

B2B contracts eg quantity flexible contracts late delivery penalties

etc Negotiation

eg rules associated with auction mechanisms Security

eg access control policies Privacy

Information Collection Policies (aka ldquo P3P Privacy Policiesrdquo)

Obfuscation Policies Workflow management

What to do under different sets of conditions Context aware computing

What service to invoke to access a particular contextual attribute

Context-sensitive preferences[ by Norman Sadeh Semantic Web Policy Workshop panel ISWC 2005 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 12

Exercise 1Specify your own policies

How do you decide (in general terms) which transportation you use to come to the university

whether you share your

Homework

Pictures from your holidays in Hawaii

Your famous report so many companies are willing to pay for

whether you take a private call when being at work

which tasks you perform everyday at work

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 13

Exercise 1Problem (I)

Now imagine a system application or software agent couldshould decide on your behalf How do you tell such an agent how it should do it

The way we make business take decisions etc Is dynamic that is often changesEvolves with the time

We cannot re-code re-compile re-install a new software agent every time we change the way we take decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 14

Exercise 1Problem (II)

Furthermore we need that the system acting on our behalfdoes what we want

How do we tell it What if we make a mistake and tell

something wrong is contextual that is depends on many factors is ldquointelligentrdquo (does things as we would do

them) is not reserved only to millionaires

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 15

IntroductionThe goal

Build applicationsagents whereBehaviour is flexible

Can be changedupdated without re-coding re-compiling re-

installing etchellip In a costless manner

Can be managed by administratorsusers without needing to be computer experts

Can be understood by normal users

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 16

OutlineWhy the Semantic Web

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 17

Why the Semantic Web HTML in your browser

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 18

Why the Semantic Web HTML Markup

lth2gt Topics lth2gtltpgtEducational Principles ltbrgtKnowledge Management ltbrgtEducation Process Modeling ltbrgtLearning Design ltbrgtCompetence Development ltbrgthellipltpgtlth2gt Lecturers lth2gtltpgtAlbert Angehrn INSEAD France ltbrgtBoyan Bontchev Sofia University Bulgaria ltbrgtAlexandar Dimov Sofia University Bulgaria ltbrgtDai Griffiths University of Bolton United Kingdom ltbrgthellipltpgt

Markup forpresentation only

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 19

Why the Semantic Web HTML Limitations

HTML deals only with formatting of data

It does not provide information about the data it contains

Query engines do a great job but queries like Give me the list of subjects that the winter school will

deal with Return the affiliations of the lecturers in the winter school

are not possible on the current Web

Search on current Web is based on syntactic matching

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 20

Why the Semantic Web Current Web

bull Downloadable Resources identified by URLs untyped

bull Links href src limited non-descriptive

bull User Exciting world

semantics of the resource however gleaned from content

bull Machine processable Very little information available

significance of the links only evident from the context around the anchor [Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 21

Why the Semantic Web Semantic Web Definition

ldquoThe Semantic Web is an extension of the current web in which information is given well-defined meaning better enabling computers and people to work in cooperationrdquo

Tim Berners-Lee James Hendler Ora LassilaThe Semantic Web Scientific American May 17 2001

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 22

Why the Semantic Web The Semantic Web

bull Resources (any resource) Globally Identified by URIs Extensible Relational

bull Links Identified by URIs Extensible Relational

bull User Even more exciting world

richer user experience bull Machine

More processable information is available (Data Web)

bull Computers and people Work learn and exchange

knowledge effectively

[Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 23

OutlineLast Year Lecture

Daniel Olmedilla

Last Year LectureThe Semantic Web Stack

XML Namespaces

URI UnicodeApr 3rd 2008 24Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF foundations

XML Namespaces

URI Unicode

bull Share basic syntax with other Web standards URI unique identifiers Namespaces organizegroup identifiers XML reuse syntax and data types

Apr 3rd 2008 25Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Model

XML Namespaces

URI Unicode

bull Data model facility Evolution of hyperlinks Open extensible (open world assumption) Graph model Easy interconnection of

distributed data

Apr 3rd 2008 26Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Schema

XML Namespaces

URI Unicode

bull Facility for shared vocabulary Properties to share link types Classes to share resource types

Apr 3rd 2008 27Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureSPARQL

XML Namespaces

URI Unicode

bull Querying facility Flexible pattern matching No reasoning

Some reasoning support via entailment regime

Apr 3rd 2008 28Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureOWL Description Logic

XML Namespaces

URI Unicode

bull Reasoning facility Support complex ontology models Reasoning on class and instance level

on

tolo

gy

com

ple

xity

amount of data

Apr 3rd 2008 29Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureThe Semantic Web Stack

XML Namespaces

URI Unicode

Part of this year lecture

Apr 3rd 2008 30Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureWarning (or clarification )

bull OWL Web Ontology Language

Ontology = OWL

Apr 3rd 2008 31Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 32

OutlineRule-Based Representation amp Reasoning

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 5: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 5

About this lectureInteractive

And also important This is not

a conference presentation a monologue

Each module partially builds on concepts from previous modules

Exercises are provided in order to strength understanding

You are also encouraged to interrupt and

ASK Questionswhenever you need it

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 6

About this lectureThe slides

Slides are wordy so they can be easily understood offline after the tutorial

More definitions and references are available in notes and hidden slides

Lecture is available from

httpwwwL3Sde~olmedillapresentations200820080403_UAM_Masterppt

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 7

OutlineLecture Overview

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 8

OutlineIntroduction

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 9

IntroductionWarming Up Problem

Institutions companies and people need to control the way they Make business Take decisions Offer their assets Etc hellip

Computers help us on our daily work performing tasks that we cannot perform (or we do it worse) automatically on our behalf

But generally we need to control how decisions and actions are taken

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 10

IntroductionWhat is a policy

In a very broad way a policy is defined as

a statement defining the behaviour of an entity

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 11

IntroductionPolicies are everywhere

B2B contracts eg quantity flexible contracts late delivery penalties

etc Negotiation

eg rules associated with auction mechanisms Security

eg access control policies Privacy

Information Collection Policies (aka ldquo P3P Privacy Policiesrdquo)

Obfuscation Policies Workflow management

What to do under different sets of conditions Context aware computing

What service to invoke to access a particular contextual attribute

Context-sensitive preferences[ by Norman Sadeh Semantic Web Policy Workshop panel ISWC 2005 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 12

Exercise 1Specify your own policies

How do you decide (in general terms) which transportation you use to come to the university

whether you share your

Homework

Pictures from your holidays in Hawaii

Your famous report so many companies are willing to pay for

whether you take a private call when being at work

which tasks you perform everyday at work

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 13

Exercise 1Problem (I)

Now imagine a system application or software agent couldshould decide on your behalf How do you tell such an agent how it should do it

The way we make business take decisions etc Is dynamic that is often changesEvolves with the time

We cannot re-code re-compile re-install a new software agent every time we change the way we take decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 14

Exercise 1Problem (II)

Furthermore we need that the system acting on our behalfdoes what we want

How do we tell it What if we make a mistake and tell

something wrong is contextual that is depends on many factors is ldquointelligentrdquo (does things as we would do

them) is not reserved only to millionaires

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 15

IntroductionThe goal

Build applicationsagents whereBehaviour is flexible

Can be changedupdated without re-coding re-compiling re-

installing etchellip In a costless manner

Can be managed by administratorsusers without needing to be computer experts

Can be understood by normal users

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 16

OutlineWhy the Semantic Web

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 17

Why the Semantic Web HTML in your browser

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 18

Why the Semantic Web HTML Markup

lth2gt Topics lth2gtltpgtEducational Principles ltbrgtKnowledge Management ltbrgtEducation Process Modeling ltbrgtLearning Design ltbrgtCompetence Development ltbrgthellipltpgtlth2gt Lecturers lth2gtltpgtAlbert Angehrn INSEAD France ltbrgtBoyan Bontchev Sofia University Bulgaria ltbrgtAlexandar Dimov Sofia University Bulgaria ltbrgtDai Griffiths University of Bolton United Kingdom ltbrgthellipltpgt

Markup forpresentation only

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 19

Why the Semantic Web HTML Limitations

HTML deals only with formatting of data

It does not provide information about the data it contains

Query engines do a great job but queries like Give me the list of subjects that the winter school will

deal with Return the affiliations of the lecturers in the winter school

are not possible on the current Web

Search on current Web is based on syntactic matching

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 20

Why the Semantic Web Current Web

bull Downloadable Resources identified by URLs untyped

bull Links href src limited non-descriptive

bull User Exciting world

semantics of the resource however gleaned from content

bull Machine processable Very little information available

significance of the links only evident from the context around the anchor [Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 21

Why the Semantic Web Semantic Web Definition

ldquoThe Semantic Web is an extension of the current web in which information is given well-defined meaning better enabling computers and people to work in cooperationrdquo

Tim Berners-Lee James Hendler Ora LassilaThe Semantic Web Scientific American May 17 2001

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 22

Why the Semantic Web The Semantic Web

bull Resources (any resource) Globally Identified by URIs Extensible Relational

bull Links Identified by URIs Extensible Relational

bull User Even more exciting world

richer user experience bull Machine

More processable information is available (Data Web)

bull Computers and people Work learn and exchange

knowledge effectively

[Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 23

OutlineLast Year Lecture

Daniel Olmedilla

Last Year LectureThe Semantic Web Stack

XML Namespaces

URI UnicodeApr 3rd 2008 24Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF foundations

XML Namespaces

URI Unicode

bull Share basic syntax with other Web standards URI unique identifiers Namespaces organizegroup identifiers XML reuse syntax and data types

Apr 3rd 2008 25Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Model

XML Namespaces

URI Unicode

bull Data model facility Evolution of hyperlinks Open extensible (open world assumption) Graph model Easy interconnection of

distributed data

Apr 3rd 2008 26Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Schema

XML Namespaces

URI Unicode

bull Facility for shared vocabulary Properties to share link types Classes to share resource types

Apr 3rd 2008 27Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureSPARQL

XML Namespaces

URI Unicode

bull Querying facility Flexible pattern matching No reasoning

Some reasoning support via entailment regime

Apr 3rd 2008 28Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureOWL Description Logic

XML Namespaces

URI Unicode

bull Reasoning facility Support complex ontology models Reasoning on class and instance level

on

tolo

gy

com

ple

xity

amount of data

Apr 3rd 2008 29Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureThe Semantic Web Stack

XML Namespaces

URI Unicode

Part of this year lecture

Apr 3rd 2008 30Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureWarning (or clarification )

bull OWL Web Ontology Language

Ontology = OWL

Apr 3rd 2008 31Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 32

OutlineRule-Based Representation amp Reasoning

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 6: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 6

About this lectureThe slides

Slides are wordy so they can be easily understood offline after the tutorial

More definitions and references are available in notes and hidden slides

Lecture is available from

httpwwwL3Sde~olmedillapresentations200820080403_UAM_Masterppt

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 7

OutlineLecture Overview

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 8

OutlineIntroduction

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 9

IntroductionWarming Up Problem

Institutions companies and people need to control the way they Make business Take decisions Offer their assets Etc hellip

Computers help us on our daily work performing tasks that we cannot perform (or we do it worse) automatically on our behalf

But generally we need to control how decisions and actions are taken

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 10

IntroductionWhat is a policy

In a very broad way a policy is defined as

a statement defining the behaviour of an entity

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 11

IntroductionPolicies are everywhere

B2B contracts eg quantity flexible contracts late delivery penalties

etc Negotiation

eg rules associated with auction mechanisms Security

eg access control policies Privacy

Information Collection Policies (aka ldquo P3P Privacy Policiesrdquo)

Obfuscation Policies Workflow management

What to do under different sets of conditions Context aware computing

What service to invoke to access a particular contextual attribute

Context-sensitive preferences[ by Norman Sadeh Semantic Web Policy Workshop panel ISWC 2005 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 12

Exercise 1Specify your own policies

How do you decide (in general terms) which transportation you use to come to the university

whether you share your

Homework

Pictures from your holidays in Hawaii

Your famous report so many companies are willing to pay for

whether you take a private call when being at work

which tasks you perform everyday at work

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 13

Exercise 1Problem (I)

Now imagine a system application or software agent couldshould decide on your behalf How do you tell such an agent how it should do it

The way we make business take decisions etc Is dynamic that is often changesEvolves with the time

We cannot re-code re-compile re-install a new software agent every time we change the way we take decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 14

Exercise 1Problem (II)

Furthermore we need that the system acting on our behalfdoes what we want

How do we tell it What if we make a mistake and tell

something wrong is contextual that is depends on many factors is ldquointelligentrdquo (does things as we would do

them) is not reserved only to millionaires

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 15

IntroductionThe goal

Build applicationsagents whereBehaviour is flexible

Can be changedupdated without re-coding re-compiling re-

installing etchellip In a costless manner

Can be managed by administratorsusers without needing to be computer experts

Can be understood by normal users

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 16

OutlineWhy the Semantic Web

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 17

Why the Semantic Web HTML in your browser

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 18

Why the Semantic Web HTML Markup

lth2gt Topics lth2gtltpgtEducational Principles ltbrgtKnowledge Management ltbrgtEducation Process Modeling ltbrgtLearning Design ltbrgtCompetence Development ltbrgthellipltpgtlth2gt Lecturers lth2gtltpgtAlbert Angehrn INSEAD France ltbrgtBoyan Bontchev Sofia University Bulgaria ltbrgtAlexandar Dimov Sofia University Bulgaria ltbrgtDai Griffiths University of Bolton United Kingdom ltbrgthellipltpgt

Markup forpresentation only

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 19

Why the Semantic Web HTML Limitations

HTML deals only with formatting of data

It does not provide information about the data it contains

Query engines do a great job but queries like Give me the list of subjects that the winter school will

deal with Return the affiliations of the lecturers in the winter school

are not possible on the current Web

Search on current Web is based on syntactic matching

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 20

Why the Semantic Web Current Web

bull Downloadable Resources identified by URLs untyped

bull Links href src limited non-descriptive

bull User Exciting world

semantics of the resource however gleaned from content

bull Machine processable Very little information available

significance of the links only evident from the context around the anchor [Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 21

Why the Semantic Web Semantic Web Definition

ldquoThe Semantic Web is an extension of the current web in which information is given well-defined meaning better enabling computers and people to work in cooperationrdquo

Tim Berners-Lee James Hendler Ora LassilaThe Semantic Web Scientific American May 17 2001

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 22

Why the Semantic Web The Semantic Web

bull Resources (any resource) Globally Identified by URIs Extensible Relational

bull Links Identified by URIs Extensible Relational

bull User Even more exciting world

richer user experience bull Machine

More processable information is available (Data Web)

bull Computers and people Work learn and exchange

knowledge effectively

[Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 23

OutlineLast Year Lecture

Daniel Olmedilla

Last Year LectureThe Semantic Web Stack

XML Namespaces

URI UnicodeApr 3rd 2008 24Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF foundations

XML Namespaces

URI Unicode

bull Share basic syntax with other Web standards URI unique identifiers Namespaces organizegroup identifiers XML reuse syntax and data types

Apr 3rd 2008 25Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Model

XML Namespaces

URI Unicode

bull Data model facility Evolution of hyperlinks Open extensible (open world assumption) Graph model Easy interconnection of

distributed data

Apr 3rd 2008 26Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Schema

XML Namespaces

URI Unicode

bull Facility for shared vocabulary Properties to share link types Classes to share resource types

Apr 3rd 2008 27Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureSPARQL

XML Namespaces

URI Unicode

bull Querying facility Flexible pattern matching No reasoning

Some reasoning support via entailment regime

Apr 3rd 2008 28Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureOWL Description Logic

XML Namespaces

URI Unicode

bull Reasoning facility Support complex ontology models Reasoning on class and instance level

on

tolo

gy

com

ple

xity

amount of data

Apr 3rd 2008 29Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureThe Semantic Web Stack

XML Namespaces

URI Unicode

Part of this year lecture

Apr 3rd 2008 30Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureWarning (or clarification )

bull OWL Web Ontology Language

Ontology = OWL

Apr 3rd 2008 31Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 32

OutlineRule-Based Representation amp Reasoning

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 7: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 7

OutlineLecture Overview

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 8

OutlineIntroduction

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 9

IntroductionWarming Up Problem

Institutions companies and people need to control the way they Make business Take decisions Offer their assets Etc hellip

Computers help us on our daily work performing tasks that we cannot perform (or we do it worse) automatically on our behalf

But generally we need to control how decisions and actions are taken

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 10

IntroductionWhat is a policy

In a very broad way a policy is defined as

a statement defining the behaviour of an entity

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 11

IntroductionPolicies are everywhere

B2B contracts eg quantity flexible contracts late delivery penalties

etc Negotiation

eg rules associated with auction mechanisms Security

eg access control policies Privacy

Information Collection Policies (aka ldquo P3P Privacy Policiesrdquo)

Obfuscation Policies Workflow management

What to do under different sets of conditions Context aware computing

What service to invoke to access a particular contextual attribute

Context-sensitive preferences[ by Norman Sadeh Semantic Web Policy Workshop panel ISWC 2005 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 12

Exercise 1Specify your own policies

How do you decide (in general terms) which transportation you use to come to the university

whether you share your

Homework

Pictures from your holidays in Hawaii

Your famous report so many companies are willing to pay for

whether you take a private call when being at work

which tasks you perform everyday at work

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 13

Exercise 1Problem (I)

Now imagine a system application or software agent couldshould decide on your behalf How do you tell such an agent how it should do it

The way we make business take decisions etc Is dynamic that is often changesEvolves with the time

We cannot re-code re-compile re-install a new software agent every time we change the way we take decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 14

Exercise 1Problem (II)

Furthermore we need that the system acting on our behalfdoes what we want

How do we tell it What if we make a mistake and tell

something wrong is contextual that is depends on many factors is ldquointelligentrdquo (does things as we would do

them) is not reserved only to millionaires

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 15

IntroductionThe goal

Build applicationsagents whereBehaviour is flexible

Can be changedupdated without re-coding re-compiling re-

installing etchellip In a costless manner

Can be managed by administratorsusers without needing to be computer experts

Can be understood by normal users

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 16

OutlineWhy the Semantic Web

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 17

Why the Semantic Web HTML in your browser

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 18

Why the Semantic Web HTML Markup

lth2gt Topics lth2gtltpgtEducational Principles ltbrgtKnowledge Management ltbrgtEducation Process Modeling ltbrgtLearning Design ltbrgtCompetence Development ltbrgthellipltpgtlth2gt Lecturers lth2gtltpgtAlbert Angehrn INSEAD France ltbrgtBoyan Bontchev Sofia University Bulgaria ltbrgtAlexandar Dimov Sofia University Bulgaria ltbrgtDai Griffiths University of Bolton United Kingdom ltbrgthellipltpgt

Markup forpresentation only

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 19

Why the Semantic Web HTML Limitations

HTML deals only with formatting of data

It does not provide information about the data it contains

Query engines do a great job but queries like Give me the list of subjects that the winter school will

deal with Return the affiliations of the lecturers in the winter school

are not possible on the current Web

Search on current Web is based on syntactic matching

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 20

Why the Semantic Web Current Web

bull Downloadable Resources identified by URLs untyped

bull Links href src limited non-descriptive

bull User Exciting world

semantics of the resource however gleaned from content

bull Machine processable Very little information available

significance of the links only evident from the context around the anchor [Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 21

Why the Semantic Web Semantic Web Definition

ldquoThe Semantic Web is an extension of the current web in which information is given well-defined meaning better enabling computers and people to work in cooperationrdquo

Tim Berners-Lee James Hendler Ora LassilaThe Semantic Web Scientific American May 17 2001

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 22

Why the Semantic Web The Semantic Web

bull Resources (any resource) Globally Identified by URIs Extensible Relational

bull Links Identified by URIs Extensible Relational

bull User Even more exciting world

richer user experience bull Machine

More processable information is available (Data Web)

bull Computers and people Work learn and exchange

knowledge effectively

[Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 23

OutlineLast Year Lecture

Daniel Olmedilla

Last Year LectureThe Semantic Web Stack

XML Namespaces

URI UnicodeApr 3rd 2008 24Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF foundations

XML Namespaces

URI Unicode

bull Share basic syntax with other Web standards URI unique identifiers Namespaces organizegroup identifiers XML reuse syntax and data types

Apr 3rd 2008 25Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Model

XML Namespaces

URI Unicode

bull Data model facility Evolution of hyperlinks Open extensible (open world assumption) Graph model Easy interconnection of

distributed data

Apr 3rd 2008 26Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Schema

XML Namespaces

URI Unicode

bull Facility for shared vocabulary Properties to share link types Classes to share resource types

Apr 3rd 2008 27Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureSPARQL

XML Namespaces

URI Unicode

bull Querying facility Flexible pattern matching No reasoning

Some reasoning support via entailment regime

Apr 3rd 2008 28Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureOWL Description Logic

XML Namespaces

URI Unicode

bull Reasoning facility Support complex ontology models Reasoning on class and instance level

on

tolo

gy

com

ple

xity

amount of data

Apr 3rd 2008 29Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureThe Semantic Web Stack

XML Namespaces

URI Unicode

Part of this year lecture

Apr 3rd 2008 30Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureWarning (or clarification )

bull OWL Web Ontology Language

Ontology = OWL

Apr 3rd 2008 31Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 32

OutlineRule-Based Representation amp Reasoning

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 8: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 8

OutlineIntroduction

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 9

IntroductionWarming Up Problem

Institutions companies and people need to control the way they Make business Take decisions Offer their assets Etc hellip

Computers help us on our daily work performing tasks that we cannot perform (or we do it worse) automatically on our behalf

But generally we need to control how decisions and actions are taken

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 10

IntroductionWhat is a policy

In a very broad way a policy is defined as

a statement defining the behaviour of an entity

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 11

IntroductionPolicies are everywhere

B2B contracts eg quantity flexible contracts late delivery penalties

etc Negotiation

eg rules associated with auction mechanisms Security

eg access control policies Privacy

Information Collection Policies (aka ldquo P3P Privacy Policiesrdquo)

Obfuscation Policies Workflow management

What to do under different sets of conditions Context aware computing

What service to invoke to access a particular contextual attribute

Context-sensitive preferences[ by Norman Sadeh Semantic Web Policy Workshop panel ISWC 2005 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 12

Exercise 1Specify your own policies

How do you decide (in general terms) which transportation you use to come to the university

whether you share your

Homework

Pictures from your holidays in Hawaii

Your famous report so many companies are willing to pay for

whether you take a private call when being at work

which tasks you perform everyday at work

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 13

Exercise 1Problem (I)

Now imagine a system application or software agent couldshould decide on your behalf How do you tell such an agent how it should do it

The way we make business take decisions etc Is dynamic that is often changesEvolves with the time

We cannot re-code re-compile re-install a new software agent every time we change the way we take decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 14

Exercise 1Problem (II)

Furthermore we need that the system acting on our behalfdoes what we want

How do we tell it What if we make a mistake and tell

something wrong is contextual that is depends on many factors is ldquointelligentrdquo (does things as we would do

them) is not reserved only to millionaires

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 15

IntroductionThe goal

Build applicationsagents whereBehaviour is flexible

Can be changedupdated without re-coding re-compiling re-

installing etchellip In a costless manner

Can be managed by administratorsusers without needing to be computer experts

Can be understood by normal users

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 16

OutlineWhy the Semantic Web

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 17

Why the Semantic Web HTML in your browser

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 18

Why the Semantic Web HTML Markup

lth2gt Topics lth2gtltpgtEducational Principles ltbrgtKnowledge Management ltbrgtEducation Process Modeling ltbrgtLearning Design ltbrgtCompetence Development ltbrgthellipltpgtlth2gt Lecturers lth2gtltpgtAlbert Angehrn INSEAD France ltbrgtBoyan Bontchev Sofia University Bulgaria ltbrgtAlexandar Dimov Sofia University Bulgaria ltbrgtDai Griffiths University of Bolton United Kingdom ltbrgthellipltpgt

Markup forpresentation only

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 19

Why the Semantic Web HTML Limitations

HTML deals only with formatting of data

It does not provide information about the data it contains

Query engines do a great job but queries like Give me the list of subjects that the winter school will

deal with Return the affiliations of the lecturers in the winter school

are not possible on the current Web

Search on current Web is based on syntactic matching

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 20

Why the Semantic Web Current Web

bull Downloadable Resources identified by URLs untyped

bull Links href src limited non-descriptive

bull User Exciting world

semantics of the resource however gleaned from content

bull Machine processable Very little information available

significance of the links only evident from the context around the anchor [Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 21

Why the Semantic Web Semantic Web Definition

ldquoThe Semantic Web is an extension of the current web in which information is given well-defined meaning better enabling computers and people to work in cooperationrdquo

Tim Berners-Lee James Hendler Ora LassilaThe Semantic Web Scientific American May 17 2001

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 22

Why the Semantic Web The Semantic Web

bull Resources (any resource) Globally Identified by URIs Extensible Relational

bull Links Identified by URIs Extensible Relational

bull User Even more exciting world

richer user experience bull Machine

More processable information is available (Data Web)

bull Computers and people Work learn and exchange

knowledge effectively

[Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 23

OutlineLast Year Lecture

Daniel Olmedilla

Last Year LectureThe Semantic Web Stack

XML Namespaces

URI UnicodeApr 3rd 2008 24Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF foundations

XML Namespaces

URI Unicode

bull Share basic syntax with other Web standards URI unique identifiers Namespaces organizegroup identifiers XML reuse syntax and data types

Apr 3rd 2008 25Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Model

XML Namespaces

URI Unicode

bull Data model facility Evolution of hyperlinks Open extensible (open world assumption) Graph model Easy interconnection of

distributed data

Apr 3rd 2008 26Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Schema

XML Namespaces

URI Unicode

bull Facility for shared vocabulary Properties to share link types Classes to share resource types

Apr 3rd 2008 27Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureSPARQL

XML Namespaces

URI Unicode

bull Querying facility Flexible pattern matching No reasoning

Some reasoning support via entailment regime

Apr 3rd 2008 28Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureOWL Description Logic

XML Namespaces

URI Unicode

bull Reasoning facility Support complex ontology models Reasoning on class and instance level

on

tolo

gy

com

ple

xity

amount of data

Apr 3rd 2008 29Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureThe Semantic Web Stack

XML Namespaces

URI Unicode

Part of this year lecture

Apr 3rd 2008 30Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureWarning (or clarification )

bull OWL Web Ontology Language

Ontology = OWL

Apr 3rd 2008 31Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 32

OutlineRule-Based Representation amp Reasoning

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 9: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 9

IntroductionWarming Up Problem

Institutions companies and people need to control the way they Make business Take decisions Offer their assets Etc hellip

Computers help us on our daily work performing tasks that we cannot perform (or we do it worse) automatically on our behalf

But generally we need to control how decisions and actions are taken

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 10

IntroductionWhat is a policy

In a very broad way a policy is defined as

a statement defining the behaviour of an entity

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 11

IntroductionPolicies are everywhere

B2B contracts eg quantity flexible contracts late delivery penalties

etc Negotiation

eg rules associated with auction mechanisms Security

eg access control policies Privacy

Information Collection Policies (aka ldquo P3P Privacy Policiesrdquo)

Obfuscation Policies Workflow management

What to do under different sets of conditions Context aware computing

What service to invoke to access a particular contextual attribute

Context-sensitive preferences[ by Norman Sadeh Semantic Web Policy Workshop panel ISWC 2005 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 12

Exercise 1Specify your own policies

How do you decide (in general terms) which transportation you use to come to the university

whether you share your

Homework

Pictures from your holidays in Hawaii

Your famous report so many companies are willing to pay for

whether you take a private call when being at work

which tasks you perform everyday at work

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 13

Exercise 1Problem (I)

Now imagine a system application or software agent couldshould decide on your behalf How do you tell such an agent how it should do it

The way we make business take decisions etc Is dynamic that is often changesEvolves with the time

We cannot re-code re-compile re-install a new software agent every time we change the way we take decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 14

Exercise 1Problem (II)

Furthermore we need that the system acting on our behalfdoes what we want

How do we tell it What if we make a mistake and tell

something wrong is contextual that is depends on many factors is ldquointelligentrdquo (does things as we would do

them) is not reserved only to millionaires

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 15

IntroductionThe goal

Build applicationsagents whereBehaviour is flexible

Can be changedupdated without re-coding re-compiling re-

installing etchellip In a costless manner

Can be managed by administratorsusers without needing to be computer experts

Can be understood by normal users

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 16

OutlineWhy the Semantic Web

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 17

Why the Semantic Web HTML in your browser

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 18

Why the Semantic Web HTML Markup

lth2gt Topics lth2gtltpgtEducational Principles ltbrgtKnowledge Management ltbrgtEducation Process Modeling ltbrgtLearning Design ltbrgtCompetence Development ltbrgthellipltpgtlth2gt Lecturers lth2gtltpgtAlbert Angehrn INSEAD France ltbrgtBoyan Bontchev Sofia University Bulgaria ltbrgtAlexandar Dimov Sofia University Bulgaria ltbrgtDai Griffiths University of Bolton United Kingdom ltbrgthellipltpgt

Markup forpresentation only

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 19

Why the Semantic Web HTML Limitations

HTML deals only with formatting of data

It does not provide information about the data it contains

Query engines do a great job but queries like Give me the list of subjects that the winter school will

deal with Return the affiliations of the lecturers in the winter school

are not possible on the current Web

Search on current Web is based on syntactic matching

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 20

Why the Semantic Web Current Web

bull Downloadable Resources identified by URLs untyped

bull Links href src limited non-descriptive

bull User Exciting world

semantics of the resource however gleaned from content

bull Machine processable Very little information available

significance of the links only evident from the context around the anchor [Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 21

Why the Semantic Web Semantic Web Definition

ldquoThe Semantic Web is an extension of the current web in which information is given well-defined meaning better enabling computers and people to work in cooperationrdquo

Tim Berners-Lee James Hendler Ora LassilaThe Semantic Web Scientific American May 17 2001

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 22

Why the Semantic Web The Semantic Web

bull Resources (any resource) Globally Identified by URIs Extensible Relational

bull Links Identified by URIs Extensible Relational

bull User Even more exciting world

richer user experience bull Machine

More processable information is available (Data Web)

bull Computers and people Work learn and exchange

knowledge effectively

[Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 23

OutlineLast Year Lecture

Daniel Olmedilla

Last Year LectureThe Semantic Web Stack

XML Namespaces

URI UnicodeApr 3rd 2008 24Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF foundations

XML Namespaces

URI Unicode

bull Share basic syntax with other Web standards URI unique identifiers Namespaces organizegroup identifiers XML reuse syntax and data types

Apr 3rd 2008 25Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Model

XML Namespaces

URI Unicode

bull Data model facility Evolution of hyperlinks Open extensible (open world assumption) Graph model Easy interconnection of

distributed data

Apr 3rd 2008 26Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Schema

XML Namespaces

URI Unicode

bull Facility for shared vocabulary Properties to share link types Classes to share resource types

Apr 3rd 2008 27Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureSPARQL

XML Namespaces

URI Unicode

bull Querying facility Flexible pattern matching No reasoning

Some reasoning support via entailment regime

Apr 3rd 2008 28Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureOWL Description Logic

XML Namespaces

URI Unicode

bull Reasoning facility Support complex ontology models Reasoning on class and instance level

on

tolo

gy

com

ple

xity

amount of data

Apr 3rd 2008 29Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureThe Semantic Web Stack

XML Namespaces

URI Unicode

Part of this year lecture

Apr 3rd 2008 30Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureWarning (or clarification )

bull OWL Web Ontology Language

Ontology = OWL

Apr 3rd 2008 31Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 32

OutlineRule-Based Representation amp Reasoning

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 10: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 10

IntroductionWhat is a policy

In a very broad way a policy is defined as

a statement defining the behaviour of an entity

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 11

IntroductionPolicies are everywhere

B2B contracts eg quantity flexible contracts late delivery penalties

etc Negotiation

eg rules associated with auction mechanisms Security

eg access control policies Privacy

Information Collection Policies (aka ldquo P3P Privacy Policiesrdquo)

Obfuscation Policies Workflow management

What to do under different sets of conditions Context aware computing

What service to invoke to access a particular contextual attribute

Context-sensitive preferences[ by Norman Sadeh Semantic Web Policy Workshop panel ISWC 2005 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 12

Exercise 1Specify your own policies

How do you decide (in general terms) which transportation you use to come to the university

whether you share your

Homework

Pictures from your holidays in Hawaii

Your famous report so many companies are willing to pay for

whether you take a private call when being at work

which tasks you perform everyday at work

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 13

Exercise 1Problem (I)

Now imagine a system application or software agent couldshould decide on your behalf How do you tell such an agent how it should do it

The way we make business take decisions etc Is dynamic that is often changesEvolves with the time

We cannot re-code re-compile re-install a new software agent every time we change the way we take decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 14

Exercise 1Problem (II)

Furthermore we need that the system acting on our behalfdoes what we want

How do we tell it What if we make a mistake and tell

something wrong is contextual that is depends on many factors is ldquointelligentrdquo (does things as we would do

them) is not reserved only to millionaires

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 15

IntroductionThe goal

Build applicationsagents whereBehaviour is flexible

Can be changedupdated without re-coding re-compiling re-

installing etchellip In a costless manner

Can be managed by administratorsusers without needing to be computer experts

Can be understood by normal users

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 16

OutlineWhy the Semantic Web

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 17

Why the Semantic Web HTML in your browser

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 18

Why the Semantic Web HTML Markup

lth2gt Topics lth2gtltpgtEducational Principles ltbrgtKnowledge Management ltbrgtEducation Process Modeling ltbrgtLearning Design ltbrgtCompetence Development ltbrgthellipltpgtlth2gt Lecturers lth2gtltpgtAlbert Angehrn INSEAD France ltbrgtBoyan Bontchev Sofia University Bulgaria ltbrgtAlexandar Dimov Sofia University Bulgaria ltbrgtDai Griffiths University of Bolton United Kingdom ltbrgthellipltpgt

Markup forpresentation only

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 19

Why the Semantic Web HTML Limitations

HTML deals only with formatting of data

It does not provide information about the data it contains

Query engines do a great job but queries like Give me the list of subjects that the winter school will

deal with Return the affiliations of the lecturers in the winter school

are not possible on the current Web

Search on current Web is based on syntactic matching

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 20

Why the Semantic Web Current Web

bull Downloadable Resources identified by URLs untyped

bull Links href src limited non-descriptive

bull User Exciting world

semantics of the resource however gleaned from content

bull Machine processable Very little information available

significance of the links only evident from the context around the anchor [Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 21

Why the Semantic Web Semantic Web Definition

ldquoThe Semantic Web is an extension of the current web in which information is given well-defined meaning better enabling computers and people to work in cooperationrdquo

Tim Berners-Lee James Hendler Ora LassilaThe Semantic Web Scientific American May 17 2001

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 22

Why the Semantic Web The Semantic Web

bull Resources (any resource) Globally Identified by URIs Extensible Relational

bull Links Identified by URIs Extensible Relational

bull User Even more exciting world

richer user experience bull Machine

More processable information is available (Data Web)

bull Computers and people Work learn and exchange

knowledge effectively

[Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 23

OutlineLast Year Lecture

Daniel Olmedilla

Last Year LectureThe Semantic Web Stack

XML Namespaces

URI UnicodeApr 3rd 2008 24Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF foundations

XML Namespaces

URI Unicode

bull Share basic syntax with other Web standards URI unique identifiers Namespaces organizegroup identifiers XML reuse syntax and data types

Apr 3rd 2008 25Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Model

XML Namespaces

URI Unicode

bull Data model facility Evolution of hyperlinks Open extensible (open world assumption) Graph model Easy interconnection of

distributed data

Apr 3rd 2008 26Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Schema

XML Namespaces

URI Unicode

bull Facility for shared vocabulary Properties to share link types Classes to share resource types

Apr 3rd 2008 27Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureSPARQL

XML Namespaces

URI Unicode

bull Querying facility Flexible pattern matching No reasoning

Some reasoning support via entailment regime

Apr 3rd 2008 28Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureOWL Description Logic

XML Namespaces

URI Unicode

bull Reasoning facility Support complex ontology models Reasoning on class and instance level

on

tolo

gy

com

ple

xity

amount of data

Apr 3rd 2008 29Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureThe Semantic Web Stack

XML Namespaces

URI Unicode

Part of this year lecture

Apr 3rd 2008 30Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureWarning (or clarification )

bull OWL Web Ontology Language

Ontology = OWL

Apr 3rd 2008 31Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 32

OutlineRule-Based Representation amp Reasoning

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 11: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 11

IntroductionPolicies are everywhere

B2B contracts eg quantity flexible contracts late delivery penalties

etc Negotiation

eg rules associated with auction mechanisms Security

eg access control policies Privacy

Information Collection Policies (aka ldquo P3P Privacy Policiesrdquo)

Obfuscation Policies Workflow management

What to do under different sets of conditions Context aware computing

What service to invoke to access a particular contextual attribute

Context-sensitive preferences[ by Norman Sadeh Semantic Web Policy Workshop panel ISWC 2005 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 12

Exercise 1Specify your own policies

How do you decide (in general terms) which transportation you use to come to the university

whether you share your

Homework

Pictures from your holidays in Hawaii

Your famous report so many companies are willing to pay for

whether you take a private call when being at work

which tasks you perform everyday at work

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 13

Exercise 1Problem (I)

Now imagine a system application or software agent couldshould decide on your behalf How do you tell such an agent how it should do it

The way we make business take decisions etc Is dynamic that is often changesEvolves with the time

We cannot re-code re-compile re-install a new software agent every time we change the way we take decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 14

Exercise 1Problem (II)

Furthermore we need that the system acting on our behalfdoes what we want

How do we tell it What if we make a mistake and tell

something wrong is contextual that is depends on many factors is ldquointelligentrdquo (does things as we would do

them) is not reserved only to millionaires

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 15

IntroductionThe goal

Build applicationsagents whereBehaviour is flexible

Can be changedupdated without re-coding re-compiling re-

installing etchellip In a costless manner

Can be managed by administratorsusers without needing to be computer experts

Can be understood by normal users

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 16

OutlineWhy the Semantic Web

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 17

Why the Semantic Web HTML in your browser

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 18

Why the Semantic Web HTML Markup

lth2gt Topics lth2gtltpgtEducational Principles ltbrgtKnowledge Management ltbrgtEducation Process Modeling ltbrgtLearning Design ltbrgtCompetence Development ltbrgthellipltpgtlth2gt Lecturers lth2gtltpgtAlbert Angehrn INSEAD France ltbrgtBoyan Bontchev Sofia University Bulgaria ltbrgtAlexandar Dimov Sofia University Bulgaria ltbrgtDai Griffiths University of Bolton United Kingdom ltbrgthellipltpgt

Markup forpresentation only

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 19

Why the Semantic Web HTML Limitations

HTML deals only with formatting of data

It does not provide information about the data it contains

Query engines do a great job but queries like Give me the list of subjects that the winter school will

deal with Return the affiliations of the lecturers in the winter school

are not possible on the current Web

Search on current Web is based on syntactic matching

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 20

Why the Semantic Web Current Web

bull Downloadable Resources identified by URLs untyped

bull Links href src limited non-descriptive

bull User Exciting world

semantics of the resource however gleaned from content

bull Machine processable Very little information available

significance of the links only evident from the context around the anchor [Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 21

Why the Semantic Web Semantic Web Definition

ldquoThe Semantic Web is an extension of the current web in which information is given well-defined meaning better enabling computers and people to work in cooperationrdquo

Tim Berners-Lee James Hendler Ora LassilaThe Semantic Web Scientific American May 17 2001

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 22

Why the Semantic Web The Semantic Web

bull Resources (any resource) Globally Identified by URIs Extensible Relational

bull Links Identified by URIs Extensible Relational

bull User Even more exciting world

richer user experience bull Machine

More processable information is available (Data Web)

bull Computers and people Work learn and exchange

knowledge effectively

[Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 23

OutlineLast Year Lecture

Daniel Olmedilla

Last Year LectureThe Semantic Web Stack

XML Namespaces

URI UnicodeApr 3rd 2008 24Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF foundations

XML Namespaces

URI Unicode

bull Share basic syntax with other Web standards URI unique identifiers Namespaces organizegroup identifiers XML reuse syntax and data types

Apr 3rd 2008 25Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Model

XML Namespaces

URI Unicode

bull Data model facility Evolution of hyperlinks Open extensible (open world assumption) Graph model Easy interconnection of

distributed data

Apr 3rd 2008 26Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Schema

XML Namespaces

URI Unicode

bull Facility for shared vocabulary Properties to share link types Classes to share resource types

Apr 3rd 2008 27Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureSPARQL

XML Namespaces

URI Unicode

bull Querying facility Flexible pattern matching No reasoning

Some reasoning support via entailment regime

Apr 3rd 2008 28Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureOWL Description Logic

XML Namespaces

URI Unicode

bull Reasoning facility Support complex ontology models Reasoning on class and instance level

on

tolo

gy

com

ple

xity

amount of data

Apr 3rd 2008 29Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureThe Semantic Web Stack

XML Namespaces

URI Unicode

Part of this year lecture

Apr 3rd 2008 30Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureWarning (or clarification )

bull OWL Web Ontology Language

Ontology = OWL

Apr 3rd 2008 31Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 32

OutlineRule-Based Representation amp Reasoning

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 12: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 12

Exercise 1Specify your own policies

How do you decide (in general terms) which transportation you use to come to the university

whether you share your

Homework

Pictures from your holidays in Hawaii

Your famous report so many companies are willing to pay for

whether you take a private call when being at work

which tasks you perform everyday at work

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 13

Exercise 1Problem (I)

Now imagine a system application or software agent couldshould decide on your behalf How do you tell such an agent how it should do it

The way we make business take decisions etc Is dynamic that is often changesEvolves with the time

We cannot re-code re-compile re-install a new software agent every time we change the way we take decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 14

Exercise 1Problem (II)

Furthermore we need that the system acting on our behalfdoes what we want

How do we tell it What if we make a mistake and tell

something wrong is contextual that is depends on many factors is ldquointelligentrdquo (does things as we would do

them) is not reserved only to millionaires

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 15

IntroductionThe goal

Build applicationsagents whereBehaviour is flexible

Can be changedupdated without re-coding re-compiling re-

installing etchellip In a costless manner

Can be managed by administratorsusers without needing to be computer experts

Can be understood by normal users

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 16

OutlineWhy the Semantic Web

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 17

Why the Semantic Web HTML in your browser

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 18

Why the Semantic Web HTML Markup

lth2gt Topics lth2gtltpgtEducational Principles ltbrgtKnowledge Management ltbrgtEducation Process Modeling ltbrgtLearning Design ltbrgtCompetence Development ltbrgthellipltpgtlth2gt Lecturers lth2gtltpgtAlbert Angehrn INSEAD France ltbrgtBoyan Bontchev Sofia University Bulgaria ltbrgtAlexandar Dimov Sofia University Bulgaria ltbrgtDai Griffiths University of Bolton United Kingdom ltbrgthellipltpgt

Markup forpresentation only

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 19

Why the Semantic Web HTML Limitations

HTML deals only with formatting of data

It does not provide information about the data it contains

Query engines do a great job but queries like Give me the list of subjects that the winter school will

deal with Return the affiliations of the lecturers in the winter school

are not possible on the current Web

Search on current Web is based on syntactic matching

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 20

Why the Semantic Web Current Web

bull Downloadable Resources identified by URLs untyped

bull Links href src limited non-descriptive

bull User Exciting world

semantics of the resource however gleaned from content

bull Machine processable Very little information available

significance of the links only evident from the context around the anchor [Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 21

Why the Semantic Web Semantic Web Definition

ldquoThe Semantic Web is an extension of the current web in which information is given well-defined meaning better enabling computers and people to work in cooperationrdquo

Tim Berners-Lee James Hendler Ora LassilaThe Semantic Web Scientific American May 17 2001

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 22

Why the Semantic Web The Semantic Web

bull Resources (any resource) Globally Identified by URIs Extensible Relational

bull Links Identified by URIs Extensible Relational

bull User Even more exciting world

richer user experience bull Machine

More processable information is available (Data Web)

bull Computers and people Work learn and exchange

knowledge effectively

[Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 23

OutlineLast Year Lecture

Daniel Olmedilla

Last Year LectureThe Semantic Web Stack

XML Namespaces

URI UnicodeApr 3rd 2008 24Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF foundations

XML Namespaces

URI Unicode

bull Share basic syntax with other Web standards URI unique identifiers Namespaces organizegroup identifiers XML reuse syntax and data types

Apr 3rd 2008 25Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Model

XML Namespaces

URI Unicode

bull Data model facility Evolution of hyperlinks Open extensible (open world assumption) Graph model Easy interconnection of

distributed data

Apr 3rd 2008 26Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Schema

XML Namespaces

URI Unicode

bull Facility for shared vocabulary Properties to share link types Classes to share resource types

Apr 3rd 2008 27Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureSPARQL

XML Namespaces

URI Unicode

bull Querying facility Flexible pattern matching No reasoning

Some reasoning support via entailment regime

Apr 3rd 2008 28Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureOWL Description Logic

XML Namespaces

URI Unicode

bull Reasoning facility Support complex ontology models Reasoning on class and instance level

on

tolo

gy

com

ple

xity

amount of data

Apr 3rd 2008 29Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureThe Semantic Web Stack

XML Namespaces

URI Unicode

Part of this year lecture

Apr 3rd 2008 30Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureWarning (or clarification )

bull OWL Web Ontology Language

Ontology = OWL

Apr 3rd 2008 31Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 32

OutlineRule-Based Representation amp Reasoning

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 13: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 13

Exercise 1Problem (I)

Now imagine a system application or software agent couldshould decide on your behalf How do you tell such an agent how it should do it

The way we make business take decisions etc Is dynamic that is often changesEvolves with the time

We cannot re-code re-compile re-install a new software agent every time we change the way we take decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 14

Exercise 1Problem (II)

Furthermore we need that the system acting on our behalfdoes what we want

How do we tell it What if we make a mistake and tell

something wrong is contextual that is depends on many factors is ldquointelligentrdquo (does things as we would do

them) is not reserved only to millionaires

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 15

IntroductionThe goal

Build applicationsagents whereBehaviour is flexible

Can be changedupdated without re-coding re-compiling re-

installing etchellip In a costless manner

Can be managed by administratorsusers without needing to be computer experts

Can be understood by normal users

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 16

OutlineWhy the Semantic Web

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 17

Why the Semantic Web HTML in your browser

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 18

Why the Semantic Web HTML Markup

lth2gt Topics lth2gtltpgtEducational Principles ltbrgtKnowledge Management ltbrgtEducation Process Modeling ltbrgtLearning Design ltbrgtCompetence Development ltbrgthellipltpgtlth2gt Lecturers lth2gtltpgtAlbert Angehrn INSEAD France ltbrgtBoyan Bontchev Sofia University Bulgaria ltbrgtAlexandar Dimov Sofia University Bulgaria ltbrgtDai Griffiths University of Bolton United Kingdom ltbrgthellipltpgt

Markup forpresentation only

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 19

Why the Semantic Web HTML Limitations

HTML deals only with formatting of data

It does not provide information about the data it contains

Query engines do a great job but queries like Give me the list of subjects that the winter school will

deal with Return the affiliations of the lecturers in the winter school

are not possible on the current Web

Search on current Web is based on syntactic matching

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 20

Why the Semantic Web Current Web

bull Downloadable Resources identified by URLs untyped

bull Links href src limited non-descriptive

bull User Exciting world

semantics of the resource however gleaned from content

bull Machine processable Very little information available

significance of the links only evident from the context around the anchor [Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 21

Why the Semantic Web Semantic Web Definition

ldquoThe Semantic Web is an extension of the current web in which information is given well-defined meaning better enabling computers and people to work in cooperationrdquo

Tim Berners-Lee James Hendler Ora LassilaThe Semantic Web Scientific American May 17 2001

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 22

Why the Semantic Web The Semantic Web

bull Resources (any resource) Globally Identified by URIs Extensible Relational

bull Links Identified by URIs Extensible Relational

bull User Even more exciting world

richer user experience bull Machine

More processable information is available (Data Web)

bull Computers and people Work learn and exchange

knowledge effectively

[Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 23

OutlineLast Year Lecture

Daniel Olmedilla

Last Year LectureThe Semantic Web Stack

XML Namespaces

URI UnicodeApr 3rd 2008 24Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF foundations

XML Namespaces

URI Unicode

bull Share basic syntax with other Web standards URI unique identifiers Namespaces organizegroup identifiers XML reuse syntax and data types

Apr 3rd 2008 25Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Model

XML Namespaces

URI Unicode

bull Data model facility Evolution of hyperlinks Open extensible (open world assumption) Graph model Easy interconnection of

distributed data

Apr 3rd 2008 26Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Schema

XML Namespaces

URI Unicode

bull Facility for shared vocabulary Properties to share link types Classes to share resource types

Apr 3rd 2008 27Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureSPARQL

XML Namespaces

URI Unicode

bull Querying facility Flexible pattern matching No reasoning

Some reasoning support via entailment regime

Apr 3rd 2008 28Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureOWL Description Logic

XML Namespaces

URI Unicode

bull Reasoning facility Support complex ontology models Reasoning on class and instance level

on

tolo

gy

com

ple

xity

amount of data

Apr 3rd 2008 29Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureThe Semantic Web Stack

XML Namespaces

URI Unicode

Part of this year lecture

Apr 3rd 2008 30Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureWarning (or clarification )

bull OWL Web Ontology Language

Ontology = OWL

Apr 3rd 2008 31Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 32

OutlineRule-Based Representation amp Reasoning

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 14: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 14

Exercise 1Problem (II)

Furthermore we need that the system acting on our behalfdoes what we want

How do we tell it What if we make a mistake and tell

something wrong is contextual that is depends on many factors is ldquointelligentrdquo (does things as we would do

them) is not reserved only to millionaires

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 15

IntroductionThe goal

Build applicationsagents whereBehaviour is flexible

Can be changedupdated without re-coding re-compiling re-

installing etchellip In a costless manner

Can be managed by administratorsusers without needing to be computer experts

Can be understood by normal users

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 16

OutlineWhy the Semantic Web

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 17

Why the Semantic Web HTML in your browser

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 18

Why the Semantic Web HTML Markup

lth2gt Topics lth2gtltpgtEducational Principles ltbrgtKnowledge Management ltbrgtEducation Process Modeling ltbrgtLearning Design ltbrgtCompetence Development ltbrgthellipltpgtlth2gt Lecturers lth2gtltpgtAlbert Angehrn INSEAD France ltbrgtBoyan Bontchev Sofia University Bulgaria ltbrgtAlexandar Dimov Sofia University Bulgaria ltbrgtDai Griffiths University of Bolton United Kingdom ltbrgthellipltpgt

Markup forpresentation only

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 19

Why the Semantic Web HTML Limitations

HTML deals only with formatting of data

It does not provide information about the data it contains

Query engines do a great job but queries like Give me the list of subjects that the winter school will

deal with Return the affiliations of the lecturers in the winter school

are not possible on the current Web

Search on current Web is based on syntactic matching

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 20

Why the Semantic Web Current Web

bull Downloadable Resources identified by URLs untyped

bull Links href src limited non-descriptive

bull User Exciting world

semantics of the resource however gleaned from content

bull Machine processable Very little information available

significance of the links only evident from the context around the anchor [Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 21

Why the Semantic Web Semantic Web Definition

ldquoThe Semantic Web is an extension of the current web in which information is given well-defined meaning better enabling computers and people to work in cooperationrdquo

Tim Berners-Lee James Hendler Ora LassilaThe Semantic Web Scientific American May 17 2001

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 22

Why the Semantic Web The Semantic Web

bull Resources (any resource) Globally Identified by URIs Extensible Relational

bull Links Identified by URIs Extensible Relational

bull User Even more exciting world

richer user experience bull Machine

More processable information is available (Data Web)

bull Computers and people Work learn and exchange

knowledge effectively

[Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 23

OutlineLast Year Lecture

Daniel Olmedilla

Last Year LectureThe Semantic Web Stack

XML Namespaces

URI UnicodeApr 3rd 2008 24Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF foundations

XML Namespaces

URI Unicode

bull Share basic syntax with other Web standards URI unique identifiers Namespaces organizegroup identifiers XML reuse syntax and data types

Apr 3rd 2008 25Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Model

XML Namespaces

URI Unicode

bull Data model facility Evolution of hyperlinks Open extensible (open world assumption) Graph model Easy interconnection of

distributed data

Apr 3rd 2008 26Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Schema

XML Namespaces

URI Unicode

bull Facility for shared vocabulary Properties to share link types Classes to share resource types

Apr 3rd 2008 27Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureSPARQL

XML Namespaces

URI Unicode

bull Querying facility Flexible pattern matching No reasoning

Some reasoning support via entailment regime

Apr 3rd 2008 28Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureOWL Description Logic

XML Namespaces

URI Unicode

bull Reasoning facility Support complex ontology models Reasoning on class and instance level

on

tolo

gy

com

ple

xity

amount of data

Apr 3rd 2008 29Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureThe Semantic Web Stack

XML Namespaces

URI Unicode

Part of this year lecture

Apr 3rd 2008 30Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureWarning (or clarification )

bull OWL Web Ontology Language

Ontology = OWL

Apr 3rd 2008 31Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 32

OutlineRule-Based Representation amp Reasoning

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 15: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 15

IntroductionThe goal

Build applicationsagents whereBehaviour is flexible

Can be changedupdated without re-coding re-compiling re-

installing etchellip In a costless manner

Can be managed by administratorsusers without needing to be computer experts

Can be understood by normal users

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 16

OutlineWhy the Semantic Web

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 17

Why the Semantic Web HTML in your browser

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 18

Why the Semantic Web HTML Markup

lth2gt Topics lth2gtltpgtEducational Principles ltbrgtKnowledge Management ltbrgtEducation Process Modeling ltbrgtLearning Design ltbrgtCompetence Development ltbrgthellipltpgtlth2gt Lecturers lth2gtltpgtAlbert Angehrn INSEAD France ltbrgtBoyan Bontchev Sofia University Bulgaria ltbrgtAlexandar Dimov Sofia University Bulgaria ltbrgtDai Griffiths University of Bolton United Kingdom ltbrgthellipltpgt

Markup forpresentation only

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 19

Why the Semantic Web HTML Limitations

HTML deals only with formatting of data

It does not provide information about the data it contains

Query engines do a great job but queries like Give me the list of subjects that the winter school will

deal with Return the affiliations of the lecturers in the winter school

are not possible on the current Web

Search on current Web is based on syntactic matching

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 20

Why the Semantic Web Current Web

bull Downloadable Resources identified by URLs untyped

bull Links href src limited non-descriptive

bull User Exciting world

semantics of the resource however gleaned from content

bull Machine processable Very little information available

significance of the links only evident from the context around the anchor [Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 21

Why the Semantic Web Semantic Web Definition

ldquoThe Semantic Web is an extension of the current web in which information is given well-defined meaning better enabling computers and people to work in cooperationrdquo

Tim Berners-Lee James Hendler Ora LassilaThe Semantic Web Scientific American May 17 2001

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 22

Why the Semantic Web The Semantic Web

bull Resources (any resource) Globally Identified by URIs Extensible Relational

bull Links Identified by URIs Extensible Relational

bull User Even more exciting world

richer user experience bull Machine

More processable information is available (Data Web)

bull Computers and people Work learn and exchange

knowledge effectively

[Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 23

OutlineLast Year Lecture

Daniel Olmedilla

Last Year LectureThe Semantic Web Stack

XML Namespaces

URI UnicodeApr 3rd 2008 24Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF foundations

XML Namespaces

URI Unicode

bull Share basic syntax with other Web standards URI unique identifiers Namespaces organizegroup identifiers XML reuse syntax and data types

Apr 3rd 2008 25Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Model

XML Namespaces

URI Unicode

bull Data model facility Evolution of hyperlinks Open extensible (open world assumption) Graph model Easy interconnection of

distributed data

Apr 3rd 2008 26Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Schema

XML Namespaces

URI Unicode

bull Facility for shared vocabulary Properties to share link types Classes to share resource types

Apr 3rd 2008 27Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureSPARQL

XML Namespaces

URI Unicode

bull Querying facility Flexible pattern matching No reasoning

Some reasoning support via entailment regime

Apr 3rd 2008 28Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureOWL Description Logic

XML Namespaces

URI Unicode

bull Reasoning facility Support complex ontology models Reasoning on class and instance level

on

tolo

gy

com

ple

xity

amount of data

Apr 3rd 2008 29Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureThe Semantic Web Stack

XML Namespaces

URI Unicode

Part of this year lecture

Apr 3rd 2008 30Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureWarning (or clarification )

bull OWL Web Ontology Language

Ontology = OWL

Apr 3rd 2008 31Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 32

OutlineRule-Based Representation amp Reasoning

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 16: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 16

OutlineWhy the Semantic Web

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 17

Why the Semantic Web HTML in your browser

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 18

Why the Semantic Web HTML Markup

lth2gt Topics lth2gtltpgtEducational Principles ltbrgtKnowledge Management ltbrgtEducation Process Modeling ltbrgtLearning Design ltbrgtCompetence Development ltbrgthellipltpgtlth2gt Lecturers lth2gtltpgtAlbert Angehrn INSEAD France ltbrgtBoyan Bontchev Sofia University Bulgaria ltbrgtAlexandar Dimov Sofia University Bulgaria ltbrgtDai Griffiths University of Bolton United Kingdom ltbrgthellipltpgt

Markup forpresentation only

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 19

Why the Semantic Web HTML Limitations

HTML deals only with formatting of data

It does not provide information about the data it contains

Query engines do a great job but queries like Give me the list of subjects that the winter school will

deal with Return the affiliations of the lecturers in the winter school

are not possible on the current Web

Search on current Web is based on syntactic matching

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 20

Why the Semantic Web Current Web

bull Downloadable Resources identified by URLs untyped

bull Links href src limited non-descriptive

bull User Exciting world

semantics of the resource however gleaned from content

bull Machine processable Very little information available

significance of the links only evident from the context around the anchor [Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 21

Why the Semantic Web Semantic Web Definition

ldquoThe Semantic Web is an extension of the current web in which information is given well-defined meaning better enabling computers and people to work in cooperationrdquo

Tim Berners-Lee James Hendler Ora LassilaThe Semantic Web Scientific American May 17 2001

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 22

Why the Semantic Web The Semantic Web

bull Resources (any resource) Globally Identified by URIs Extensible Relational

bull Links Identified by URIs Extensible Relational

bull User Even more exciting world

richer user experience bull Machine

More processable information is available (Data Web)

bull Computers and people Work learn and exchange

knowledge effectively

[Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 23

OutlineLast Year Lecture

Daniel Olmedilla

Last Year LectureThe Semantic Web Stack

XML Namespaces

URI UnicodeApr 3rd 2008 24Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF foundations

XML Namespaces

URI Unicode

bull Share basic syntax with other Web standards URI unique identifiers Namespaces organizegroup identifiers XML reuse syntax and data types

Apr 3rd 2008 25Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Model

XML Namespaces

URI Unicode

bull Data model facility Evolution of hyperlinks Open extensible (open world assumption) Graph model Easy interconnection of

distributed data

Apr 3rd 2008 26Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Schema

XML Namespaces

URI Unicode

bull Facility for shared vocabulary Properties to share link types Classes to share resource types

Apr 3rd 2008 27Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureSPARQL

XML Namespaces

URI Unicode

bull Querying facility Flexible pattern matching No reasoning

Some reasoning support via entailment regime

Apr 3rd 2008 28Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureOWL Description Logic

XML Namespaces

URI Unicode

bull Reasoning facility Support complex ontology models Reasoning on class and instance level

on

tolo

gy

com

ple

xity

amount of data

Apr 3rd 2008 29Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureThe Semantic Web Stack

XML Namespaces

URI Unicode

Part of this year lecture

Apr 3rd 2008 30Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureWarning (or clarification )

bull OWL Web Ontology Language

Ontology = OWL

Apr 3rd 2008 31Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 32

OutlineRule-Based Representation amp Reasoning

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 17: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 17

Why the Semantic Web HTML in your browser

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 18

Why the Semantic Web HTML Markup

lth2gt Topics lth2gtltpgtEducational Principles ltbrgtKnowledge Management ltbrgtEducation Process Modeling ltbrgtLearning Design ltbrgtCompetence Development ltbrgthellipltpgtlth2gt Lecturers lth2gtltpgtAlbert Angehrn INSEAD France ltbrgtBoyan Bontchev Sofia University Bulgaria ltbrgtAlexandar Dimov Sofia University Bulgaria ltbrgtDai Griffiths University of Bolton United Kingdom ltbrgthellipltpgt

Markup forpresentation only

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 19

Why the Semantic Web HTML Limitations

HTML deals only with formatting of data

It does not provide information about the data it contains

Query engines do a great job but queries like Give me the list of subjects that the winter school will

deal with Return the affiliations of the lecturers in the winter school

are not possible on the current Web

Search on current Web is based on syntactic matching

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 20

Why the Semantic Web Current Web

bull Downloadable Resources identified by URLs untyped

bull Links href src limited non-descriptive

bull User Exciting world

semantics of the resource however gleaned from content

bull Machine processable Very little information available

significance of the links only evident from the context around the anchor [Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 21

Why the Semantic Web Semantic Web Definition

ldquoThe Semantic Web is an extension of the current web in which information is given well-defined meaning better enabling computers and people to work in cooperationrdquo

Tim Berners-Lee James Hendler Ora LassilaThe Semantic Web Scientific American May 17 2001

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 22

Why the Semantic Web The Semantic Web

bull Resources (any resource) Globally Identified by URIs Extensible Relational

bull Links Identified by URIs Extensible Relational

bull User Even more exciting world

richer user experience bull Machine

More processable information is available (Data Web)

bull Computers and people Work learn and exchange

knowledge effectively

[Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 23

OutlineLast Year Lecture

Daniel Olmedilla

Last Year LectureThe Semantic Web Stack

XML Namespaces

URI UnicodeApr 3rd 2008 24Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF foundations

XML Namespaces

URI Unicode

bull Share basic syntax with other Web standards URI unique identifiers Namespaces organizegroup identifiers XML reuse syntax and data types

Apr 3rd 2008 25Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Model

XML Namespaces

URI Unicode

bull Data model facility Evolution of hyperlinks Open extensible (open world assumption) Graph model Easy interconnection of

distributed data

Apr 3rd 2008 26Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Schema

XML Namespaces

URI Unicode

bull Facility for shared vocabulary Properties to share link types Classes to share resource types

Apr 3rd 2008 27Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureSPARQL

XML Namespaces

URI Unicode

bull Querying facility Flexible pattern matching No reasoning

Some reasoning support via entailment regime

Apr 3rd 2008 28Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureOWL Description Logic

XML Namespaces

URI Unicode

bull Reasoning facility Support complex ontology models Reasoning on class and instance level

on

tolo

gy

com

ple

xity

amount of data

Apr 3rd 2008 29Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureThe Semantic Web Stack

XML Namespaces

URI Unicode

Part of this year lecture

Apr 3rd 2008 30Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureWarning (or clarification )

bull OWL Web Ontology Language

Ontology = OWL

Apr 3rd 2008 31Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 32

OutlineRule-Based Representation amp Reasoning

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 18: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 18

Why the Semantic Web HTML Markup

lth2gt Topics lth2gtltpgtEducational Principles ltbrgtKnowledge Management ltbrgtEducation Process Modeling ltbrgtLearning Design ltbrgtCompetence Development ltbrgthellipltpgtlth2gt Lecturers lth2gtltpgtAlbert Angehrn INSEAD France ltbrgtBoyan Bontchev Sofia University Bulgaria ltbrgtAlexandar Dimov Sofia University Bulgaria ltbrgtDai Griffiths University of Bolton United Kingdom ltbrgthellipltpgt

Markup forpresentation only

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 19

Why the Semantic Web HTML Limitations

HTML deals only with formatting of data

It does not provide information about the data it contains

Query engines do a great job but queries like Give me the list of subjects that the winter school will

deal with Return the affiliations of the lecturers in the winter school

are not possible on the current Web

Search on current Web is based on syntactic matching

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 20

Why the Semantic Web Current Web

bull Downloadable Resources identified by URLs untyped

bull Links href src limited non-descriptive

bull User Exciting world

semantics of the resource however gleaned from content

bull Machine processable Very little information available

significance of the links only evident from the context around the anchor [Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 21

Why the Semantic Web Semantic Web Definition

ldquoThe Semantic Web is an extension of the current web in which information is given well-defined meaning better enabling computers and people to work in cooperationrdquo

Tim Berners-Lee James Hendler Ora LassilaThe Semantic Web Scientific American May 17 2001

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 22

Why the Semantic Web The Semantic Web

bull Resources (any resource) Globally Identified by URIs Extensible Relational

bull Links Identified by URIs Extensible Relational

bull User Even more exciting world

richer user experience bull Machine

More processable information is available (Data Web)

bull Computers and people Work learn and exchange

knowledge effectively

[Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 23

OutlineLast Year Lecture

Daniel Olmedilla

Last Year LectureThe Semantic Web Stack

XML Namespaces

URI UnicodeApr 3rd 2008 24Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF foundations

XML Namespaces

URI Unicode

bull Share basic syntax with other Web standards URI unique identifiers Namespaces organizegroup identifiers XML reuse syntax and data types

Apr 3rd 2008 25Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Model

XML Namespaces

URI Unicode

bull Data model facility Evolution of hyperlinks Open extensible (open world assumption) Graph model Easy interconnection of

distributed data

Apr 3rd 2008 26Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Schema

XML Namespaces

URI Unicode

bull Facility for shared vocabulary Properties to share link types Classes to share resource types

Apr 3rd 2008 27Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureSPARQL

XML Namespaces

URI Unicode

bull Querying facility Flexible pattern matching No reasoning

Some reasoning support via entailment regime

Apr 3rd 2008 28Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureOWL Description Logic

XML Namespaces

URI Unicode

bull Reasoning facility Support complex ontology models Reasoning on class and instance level

on

tolo

gy

com

ple

xity

amount of data

Apr 3rd 2008 29Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureThe Semantic Web Stack

XML Namespaces

URI Unicode

Part of this year lecture

Apr 3rd 2008 30Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureWarning (or clarification )

bull OWL Web Ontology Language

Ontology = OWL

Apr 3rd 2008 31Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 32

OutlineRule-Based Representation amp Reasoning

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 19: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 19

Why the Semantic Web HTML Limitations

HTML deals only with formatting of data

It does not provide information about the data it contains

Query engines do a great job but queries like Give me the list of subjects that the winter school will

deal with Return the affiliations of the lecturers in the winter school

are not possible on the current Web

Search on current Web is based on syntactic matching

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 20

Why the Semantic Web Current Web

bull Downloadable Resources identified by URLs untyped

bull Links href src limited non-descriptive

bull User Exciting world

semantics of the resource however gleaned from content

bull Machine processable Very little information available

significance of the links only evident from the context around the anchor [Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 21

Why the Semantic Web Semantic Web Definition

ldquoThe Semantic Web is an extension of the current web in which information is given well-defined meaning better enabling computers and people to work in cooperationrdquo

Tim Berners-Lee James Hendler Ora LassilaThe Semantic Web Scientific American May 17 2001

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 22

Why the Semantic Web The Semantic Web

bull Resources (any resource) Globally Identified by URIs Extensible Relational

bull Links Identified by URIs Extensible Relational

bull User Even more exciting world

richer user experience bull Machine

More processable information is available (Data Web)

bull Computers and people Work learn and exchange

knowledge effectively

[Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 23

OutlineLast Year Lecture

Daniel Olmedilla

Last Year LectureThe Semantic Web Stack

XML Namespaces

URI UnicodeApr 3rd 2008 24Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF foundations

XML Namespaces

URI Unicode

bull Share basic syntax with other Web standards URI unique identifiers Namespaces organizegroup identifiers XML reuse syntax and data types

Apr 3rd 2008 25Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Model

XML Namespaces

URI Unicode

bull Data model facility Evolution of hyperlinks Open extensible (open world assumption) Graph model Easy interconnection of

distributed data

Apr 3rd 2008 26Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Schema

XML Namespaces

URI Unicode

bull Facility for shared vocabulary Properties to share link types Classes to share resource types

Apr 3rd 2008 27Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureSPARQL

XML Namespaces

URI Unicode

bull Querying facility Flexible pattern matching No reasoning

Some reasoning support via entailment regime

Apr 3rd 2008 28Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureOWL Description Logic

XML Namespaces

URI Unicode

bull Reasoning facility Support complex ontology models Reasoning on class and instance level

on

tolo

gy

com

ple

xity

amount of data

Apr 3rd 2008 29Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureThe Semantic Web Stack

XML Namespaces

URI Unicode

Part of this year lecture

Apr 3rd 2008 30Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureWarning (or clarification )

bull OWL Web Ontology Language

Ontology = OWL

Apr 3rd 2008 31Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 32

OutlineRule-Based Representation amp Reasoning

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 20: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 20

Why the Semantic Web Current Web

bull Downloadable Resources identified by URLs untyped

bull Links href src limited non-descriptive

bull User Exciting world

semantics of the resource however gleaned from content

bull Machine processable Very little information available

significance of the links only evident from the context around the anchor [Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 21

Why the Semantic Web Semantic Web Definition

ldquoThe Semantic Web is an extension of the current web in which information is given well-defined meaning better enabling computers and people to work in cooperationrdquo

Tim Berners-Lee James Hendler Ora LassilaThe Semantic Web Scientific American May 17 2001

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 22

Why the Semantic Web The Semantic Web

bull Resources (any resource) Globally Identified by URIs Extensible Relational

bull Links Identified by URIs Extensible Relational

bull User Even more exciting world

richer user experience bull Machine

More processable information is available (Data Web)

bull Computers and people Work learn and exchange

knowledge effectively

[Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 23

OutlineLast Year Lecture

Daniel Olmedilla

Last Year LectureThe Semantic Web Stack

XML Namespaces

URI UnicodeApr 3rd 2008 24Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF foundations

XML Namespaces

URI Unicode

bull Share basic syntax with other Web standards URI unique identifiers Namespaces organizegroup identifiers XML reuse syntax and data types

Apr 3rd 2008 25Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Model

XML Namespaces

URI Unicode

bull Data model facility Evolution of hyperlinks Open extensible (open world assumption) Graph model Easy interconnection of

distributed data

Apr 3rd 2008 26Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Schema

XML Namespaces

URI Unicode

bull Facility for shared vocabulary Properties to share link types Classes to share resource types

Apr 3rd 2008 27Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureSPARQL

XML Namespaces

URI Unicode

bull Querying facility Flexible pattern matching No reasoning

Some reasoning support via entailment regime

Apr 3rd 2008 28Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureOWL Description Logic

XML Namespaces

URI Unicode

bull Reasoning facility Support complex ontology models Reasoning on class and instance level

on

tolo

gy

com

ple

xity

amount of data

Apr 3rd 2008 29Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureThe Semantic Web Stack

XML Namespaces

URI Unicode

Part of this year lecture

Apr 3rd 2008 30Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureWarning (or clarification )

bull OWL Web Ontology Language

Ontology = OWL

Apr 3rd 2008 31Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 32

OutlineRule-Based Representation amp Reasoning

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 21: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 21

Why the Semantic Web Semantic Web Definition

ldquoThe Semantic Web is an extension of the current web in which information is given well-defined meaning better enabling computers and people to work in cooperationrdquo

Tim Berners-Lee James Hendler Ora LassilaThe Semantic Web Scientific American May 17 2001

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 22

Why the Semantic Web The Semantic Web

bull Resources (any resource) Globally Identified by URIs Extensible Relational

bull Links Identified by URIs Extensible Relational

bull User Even more exciting world

richer user experience bull Machine

More processable information is available (Data Web)

bull Computers and people Work learn and exchange

knowledge effectively

[Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 23

OutlineLast Year Lecture

Daniel Olmedilla

Last Year LectureThe Semantic Web Stack

XML Namespaces

URI UnicodeApr 3rd 2008 24Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF foundations

XML Namespaces

URI Unicode

bull Share basic syntax with other Web standards URI unique identifiers Namespaces organizegroup identifiers XML reuse syntax and data types

Apr 3rd 2008 25Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Model

XML Namespaces

URI Unicode

bull Data model facility Evolution of hyperlinks Open extensible (open world assumption) Graph model Easy interconnection of

distributed data

Apr 3rd 2008 26Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Schema

XML Namespaces

URI Unicode

bull Facility for shared vocabulary Properties to share link types Classes to share resource types

Apr 3rd 2008 27Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureSPARQL

XML Namespaces

URI Unicode

bull Querying facility Flexible pattern matching No reasoning

Some reasoning support via entailment regime

Apr 3rd 2008 28Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureOWL Description Logic

XML Namespaces

URI Unicode

bull Reasoning facility Support complex ontology models Reasoning on class and instance level

on

tolo

gy

com

ple

xity

amount of data

Apr 3rd 2008 29Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureThe Semantic Web Stack

XML Namespaces

URI Unicode

Part of this year lecture

Apr 3rd 2008 30Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureWarning (or clarification )

bull OWL Web Ontology Language

Ontology = OWL

Apr 3rd 2008 31Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 32

OutlineRule-Based Representation amp Reasoning

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 22: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 22

Why the Semantic Web The Semantic Web

bull Resources (any resource) Globally Identified by URIs Extensible Relational

bull Links Identified by URIs Extensible Relational

bull User Even more exciting world

richer user experience bull Machine

More processable information is available (Data Web)

bull Computers and people Work learn and exchange

knowledge effectively

[Eric Miller Weaving Meaning An Overview of The Semantic Web 2003 ]

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 23

OutlineLast Year Lecture

Daniel Olmedilla

Last Year LectureThe Semantic Web Stack

XML Namespaces

URI UnicodeApr 3rd 2008 24Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF foundations

XML Namespaces

URI Unicode

bull Share basic syntax with other Web standards URI unique identifiers Namespaces organizegroup identifiers XML reuse syntax and data types

Apr 3rd 2008 25Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Model

XML Namespaces

URI Unicode

bull Data model facility Evolution of hyperlinks Open extensible (open world assumption) Graph model Easy interconnection of

distributed data

Apr 3rd 2008 26Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Schema

XML Namespaces

URI Unicode

bull Facility for shared vocabulary Properties to share link types Classes to share resource types

Apr 3rd 2008 27Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureSPARQL

XML Namespaces

URI Unicode

bull Querying facility Flexible pattern matching No reasoning

Some reasoning support via entailment regime

Apr 3rd 2008 28Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureOWL Description Logic

XML Namespaces

URI Unicode

bull Reasoning facility Support complex ontology models Reasoning on class and instance level

on

tolo

gy

com

ple

xity

amount of data

Apr 3rd 2008 29Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureThe Semantic Web Stack

XML Namespaces

URI Unicode

Part of this year lecture

Apr 3rd 2008 30Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureWarning (or clarification )

bull OWL Web Ontology Language

Ontology = OWL

Apr 3rd 2008 31Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 32

OutlineRule-Based Representation amp Reasoning

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 23: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 23

OutlineLast Year Lecture

Daniel Olmedilla

Last Year LectureThe Semantic Web Stack

XML Namespaces

URI UnicodeApr 3rd 2008 24Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF foundations

XML Namespaces

URI Unicode

bull Share basic syntax with other Web standards URI unique identifiers Namespaces organizegroup identifiers XML reuse syntax and data types

Apr 3rd 2008 25Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Model

XML Namespaces

URI Unicode

bull Data model facility Evolution of hyperlinks Open extensible (open world assumption) Graph model Easy interconnection of

distributed data

Apr 3rd 2008 26Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Schema

XML Namespaces

URI Unicode

bull Facility for shared vocabulary Properties to share link types Classes to share resource types

Apr 3rd 2008 27Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureSPARQL

XML Namespaces

URI Unicode

bull Querying facility Flexible pattern matching No reasoning

Some reasoning support via entailment regime

Apr 3rd 2008 28Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureOWL Description Logic

XML Namespaces

URI Unicode

bull Reasoning facility Support complex ontology models Reasoning on class and instance level

on

tolo

gy

com

ple

xity

amount of data

Apr 3rd 2008 29Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureThe Semantic Web Stack

XML Namespaces

URI Unicode

Part of this year lecture

Apr 3rd 2008 30Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureWarning (or clarification )

bull OWL Web Ontology Language

Ontology = OWL

Apr 3rd 2008 31Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 32

OutlineRule-Based Representation amp Reasoning

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 24: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla

Last Year LectureThe Semantic Web Stack

XML Namespaces

URI UnicodeApr 3rd 2008 24Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF foundations

XML Namespaces

URI Unicode

bull Share basic syntax with other Web standards URI unique identifiers Namespaces organizegroup identifiers XML reuse syntax and data types

Apr 3rd 2008 25Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Model

XML Namespaces

URI Unicode

bull Data model facility Evolution of hyperlinks Open extensible (open world assumption) Graph model Easy interconnection of

distributed data

Apr 3rd 2008 26Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Schema

XML Namespaces

URI Unicode

bull Facility for shared vocabulary Properties to share link types Classes to share resource types

Apr 3rd 2008 27Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureSPARQL

XML Namespaces

URI Unicode

bull Querying facility Flexible pattern matching No reasoning

Some reasoning support via entailment regime

Apr 3rd 2008 28Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureOWL Description Logic

XML Namespaces

URI Unicode

bull Reasoning facility Support complex ontology models Reasoning on class and instance level

on

tolo

gy

com

ple

xity

amount of data

Apr 3rd 2008 29Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureThe Semantic Web Stack

XML Namespaces

URI Unicode

Part of this year lecture

Apr 3rd 2008 30Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureWarning (or clarification )

bull OWL Web Ontology Language

Ontology = OWL

Apr 3rd 2008 31Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 32

OutlineRule-Based Representation amp Reasoning

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 25: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla

Last year lectureRDF foundations

XML Namespaces

URI Unicode

bull Share basic syntax with other Web standards URI unique identifiers Namespaces organizegroup identifiers XML reuse syntax and data types

Apr 3rd 2008 25Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Model

XML Namespaces

URI Unicode

bull Data model facility Evolution of hyperlinks Open extensible (open world assumption) Graph model Easy interconnection of

distributed data

Apr 3rd 2008 26Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Schema

XML Namespaces

URI Unicode

bull Facility for shared vocabulary Properties to share link types Classes to share resource types

Apr 3rd 2008 27Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureSPARQL

XML Namespaces

URI Unicode

bull Querying facility Flexible pattern matching No reasoning

Some reasoning support via entailment regime

Apr 3rd 2008 28Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureOWL Description Logic

XML Namespaces

URI Unicode

bull Reasoning facility Support complex ontology models Reasoning on class and instance level

on

tolo

gy

com

ple

xity

amount of data

Apr 3rd 2008 29Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureThe Semantic Web Stack

XML Namespaces

URI Unicode

Part of this year lecture

Apr 3rd 2008 30Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureWarning (or clarification )

bull OWL Web Ontology Language

Ontology = OWL

Apr 3rd 2008 31Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 32

OutlineRule-Based Representation amp Reasoning

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 26: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla

Last year lectureRDF Model

XML Namespaces

URI Unicode

bull Data model facility Evolution of hyperlinks Open extensible (open world assumption) Graph model Easy interconnection of

distributed data

Apr 3rd 2008 26Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureRDF Schema

XML Namespaces

URI Unicode

bull Facility for shared vocabulary Properties to share link types Classes to share resource types

Apr 3rd 2008 27Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureSPARQL

XML Namespaces

URI Unicode

bull Querying facility Flexible pattern matching No reasoning

Some reasoning support via entailment regime

Apr 3rd 2008 28Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureOWL Description Logic

XML Namespaces

URI Unicode

bull Reasoning facility Support complex ontology models Reasoning on class and instance level

on

tolo

gy

com

ple

xity

amount of data

Apr 3rd 2008 29Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureThe Semantic Web Stack

XML Namespaces

URI Unicode

Part of this year lecture

Apr 3rd 2008 30Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureWarning (or clarification )

bull OWL Web Ontology Language

Ontology = OWL

Apr 3rd 2008 31Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 32

OutlineRule-Based Representation amp Reasoning

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 27: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla

Last year lectureRDF Schema

XML Namespaces

URI Unicode

bull Facility for shared vocabulary Properties to share link types Classes to share resource types

Apr 3rd 2008 27Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureSPARQL

XML Namespaces

URI Unicode

bull Querying facility Flexible pattern matching No reasoning

Some reasoning support via entailment regime

Apr 3rd 2008 28Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureOWL Description Logic

XML Namespaces

URI Unicode

bull Reasoning facility Support complex ontology models Reasoning on class and instance level

on

tolo

gy

com

ple

xity

amount of data

Apr 3rd 2008 29Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureThe Semantic Web Stack

XML Namespaces

URI Unicode

Part of this year lecture

Apr 3rd 2008 30Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureWarning (or clarification )

bull OWL Web Ontology Language

Ontology = OWL

Apr 3rd 2008 31Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 32

OutlineRule-Based Representation amp Reasoning

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 28: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla

Last year lectureSPARQL

XML Namespaces

URI Unicode

bull Querying facility Flexible pattern matching No reasoning

Some reasoning support via entailment regime

Apr 3rd 2008 28Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureOWL Description Logic

XML Namespaces

URI Unicode

bull Reasoning facility Support complex ontology models Reasoning on class and instance level

on

tolo

gy

com

ple

xity

amount of data

Apr 3rd 2008 29Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureThe Semantic Web Stack

XML Namespaces

URI Unicode

Part of this year lecture

Apr 3rd 2008 30Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureWarning (or clarification )

bull OWL Web Ontology Language

Ontology = OWL

Apr 3rd 2008 31Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 32

OutlineRule-Based Representation amp Reasoning

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 29: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla

Last year lectureOWL Description Logic

XML Namespaces

URI Unicode

bull Reasoning facility Support complex ontology models Reasoning on class and instance level

on

tolo

gy

com

ple

xity

amount of data

Apr 3rd 2008 29Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureThe Semantic Web Stack

XML Namespaces

URI Unicode

Part of this year lecture

Apr 3rd 2008 30Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureWarning (or clarification )

bull OWL Web Ontology Language

Ontology = OWL

Apr 3rd 2008 31Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 32

OutlineRule-Based Representation amp Reasoning

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 30: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla

Last year lectureThe Semantic Web Stack

XML Namespaces

URI Unicode

Part of this year lecture

Apr 3rd 2008 30Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Last year lectureWarning (or clarification )

bull OWL Web Ontology Language

Ontology = OWL

Apr 3rd 2008 31Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 32

OutlineRule-Based Representation amp Reasoning

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 31: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla

Last year lectureWarning (or clarification )

bull OWL Web Ontology Language

Ontology = OWL

Apr 3rd 2008 31Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 32

OutlineRule-Based Representation amp Reasoning

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 32: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 32

OutlineRule-Based Representation amp Reasoning

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 33: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 33

Rule-Based Representation and ReasoningWho uses logic

Aristoteles

Spock

Mathematicians

Computer scientists

You

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 34: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 34

Exercise 1Revisited (I)

Were your policies

declarative

That is they specify the what (conditions) but not the how (algorithm or process to satisfy them)

Eg HTML pages describe what the page should contain but not how to actually display the page on a computer screen

Eg a SQL select statement specifies the properties of the data to be extracted from a DB not the process of extracting the data

using inference rules

Eg If destination is in Europe then max price is hellip

Eg If distance is less than hellip then go by train

if not do you think they are more naturally modelled as rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 35: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 35

Rule-Based Representation and ReasoningRules are everywhere (I)

Rules of ethics for robots

1 A robot may not injure a human being or through inaction allow a human being to come to harm

2 A robot must obey orders given to it by human beings except where such orders would conflict with the First Law

3 A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

[Isaac Asimov Runaround 1942 ]

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 36: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 36

Rule-Based Representation and ReasoningRules are everywhere (II)

Declarative

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 37: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 37

Rule-Based Representation and ReasoningRules are everywhere (III)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 38: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 38

Rule-Based Representation and ReasoningInference Rule (I)

Relation holding between premises (antecedent) and conclusions (consequent)

The conclusion is said to be inferable (or derivable or deducible) from the premises

We can infer new knowledge

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 39: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 39

Rule-Based Representation and ReasoningDeductive vs Inductive Reasoning

Deductive proceeds from general principles or premises to derive particular information (conclusions)

Example All apples are fruit All fruits grow on trees Therefore all apples grow on treesRemember Sherlock Holmes

Inductive the premises of an argument are believed to support the conclusion but do not ensure its truth

Makes generalizations (from empirical observations)

Example All observed crows are black Therefore all crows are black

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 40: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla

Rule-Based Representation and ReasoningSyntax of First Order Predicate Logic (FOL)

Logical Symbols punctuation connectives quantifiers variables

Signature Symbols n-ary function symbols (0-ary = constant) n-ary relation symbols

Termx Mary founder (x) founder (Web50)

Atommarried(Mary Tom) married(founder (y)Tom)

Formulaperson(Mary ) person(Tom) company(Web50)

x (company(x) person(founder (x) )

Apr 3rd 2008 40Universidad Autoacutenoma de Madrid

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 41: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla

Rule-Based Representation and ReasoningStandard Notions (FOL)

Boundfree1048576

( x [x p(x) q(x) ] [ r (x) x s(x)] )

Closed no free variables

Ground no variables

Propositional1048576

[p q] [ r s]

Apr 3rd 2008 41Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 42: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 42

Rule-Based Representation and ReasoningInference Rule (II)

Rule notation consequent larr antecedent

Stands for antecedent consequentthat is IF antecedent THEN consequent

Examples If someone is a man then he is mortal

mortal(X) larr man(X) If someone is in this lecture then heshe is a researcher

researcher(X) larr inThisLecture(X)It does not matter what X is the rule is always valid

Base for deductive reasoning

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 43: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Feb 21st 2008TENCompetence WS 43

Rule-Based Representation and ReasoningLogic Programming

Literalatom A negated atom A

ClauseA1 hellip Ak larr L1 hellip Ln atoms Ai literals Lj k ge 0 n ge 0

Apr 3rd 2008 43Universidad Autoacutenoma de Madrid

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 44: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 44

Rule-Based Representation and ReasoningExample information about your family

Assume an agent needs to know all the information about your closest relatives

How do you inform your agent about such information

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 45: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 45

Rule-Based Representation and ReasoningPossibility 1 Enumerate all the facts

Try to enumerate all that information for your agent

Tom is the father of MaryTom is the parent of MaryAlice is the sister of MaryMary is the sister of AliceClara is the sister of MaryMary is the sister of ClaraMary is the mother of AnneMary is the parent of Anne

Tom is the grandparent of AnneAlice is the aunt of AnneClara is the aunt of AnneClara is the mother of BobAlice is the aunt of BobMary is the aunt of BobTom is the grandparent of Bobhellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 46: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 46

Rule-Based Representation and ReasoningPossibility 2 facts + rules + deduction

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

AxiomsFacts

Inference Rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 47: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 47

Rule-Based Representation and ReasoningExercise 2 deductive reasoning

Given such a program write down the inferred new knowledge

Tom is the father of Mary father(lsquoTomrsquorsquoMaryrsquo) Alice is the sister of Mary sister(lsquoAlicersquorsquoMaryrsquo) Clara is the sister of Mary sister(lsquoClararsquorsquoMaryrsquo) Mary is the mother of Anne mother(lsquoMaryrsquolsquoAnnersquo) Clara is the mother of Bob mother(lsquoClararsquolsquoBobrsquo)

A parent is either a father or a motherparent(PC) larr father(PC) mother(PC)

The parent of your sister is your parentparent(PC) larr parent(PX) sister(XC)

The parent of a parent is a grandparentgrandparent(PC) larr parent(PX)

parent(XC) An aunt is the sister of a parent

aunt(AC) larr sister(AX) parent(XC)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 48: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 48

Rule-Based Representation and ReasoningExercise 2 solution

Given such a program write down the inferred new knowledge

From first rule Tom is the parent of Mary parent(lsquoTomrsquorsquoMaryrsquo) Mary is the parent of Anne parent(lsquoMaryrsquorsquoAnnersquo) Clara is the parent of Bob parent(lsquoClararsquorsquoBobrsquo)

From second rule (+ the first rule) Tom is the parent of Alice parent(lsquoTomrsquorsquoAlicersquo) Tom is the parent of Clara parent(lsquoTomrsquorsquoClararsquo)

From the third rule (+ the first and second) Tom is the grandparent of Anne

grandparent(lsquoTomrsquorsquoAnnersquo) Tom is the grandparent of Bob

grandparent(lsquoTomrsquorsquoBobrsquo)

From the forth rule (+ the first rule) Alice is the aunt of Anne aunt(lsquoAlicersquorsquoAnnersquo) Clara is the aunt of Anne aunt(lsquoClararsquorsquoAnnersquo) Mary is the aunt of Bob aunt(lsquoMaryrsquorsquoBobrsquo) Alice is the aunt of Bob aunt(lsquoAlicersquorsquoBobrsquo)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 49: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 49

Rule-Based Representation and ReasoningAdvantages

Declarative Infer implicit knowledgeCompact representationWell-defined semanticsAvailable proofsTruths that it establishes are absolute

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 50: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 50

Rule-Based Representation and ReasoningDisadvantages

Wrongly specified rules wrong implicit knowledge It must have some truths in hand before starting

Sometimes you donrsquot have them all Sometimes not all is true or false You need to specify all right rules

Otherwise underspecified programs

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 51: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 51

OutlineSemantic Web Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 52: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 52

Semantic Web PoliciesWhat is a policy Definitions

A statement defining the behaviour of an entity

An enforceable well-specified constraint on the performance of a machine-executable action by a subject in a given situation

A deliberate plan of action to guide decisions and achieve rational outcome(s)

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 53: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 53

Semantic Web PoliciesA broader notion of policy

The term policy covers SecurityPrivacy policies Trust management

Business rules

Quality of Service directives

Service-level agreements

Communication and conversation policies and more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 54: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 54

Semantic Web PoliciesAn e-learning scenario (I)

Exploiting agents to support collaborative learning in an on-line learning community

They offer means to handle this complex setting as we will learn from the following four scenarios

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 55: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 55

Semantic Web PoliciesAn e-learning scenario (II)

ldquoOnly my tutor is able to access myhomework My fellow students are able to access my lecture notes but not my homeworkrdquo

Access control

Security

Trust management

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 56: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 56

Semantic Web PoliciesAn e-learning scenario (III)

ldquoI want to be reminded two days before my homework is duerdquo

ldquoI want to get an SMS if my tutor extends a homeworkrsquos deadlinerdquo

Reactive Agentsbull Events (eg deadline

extension) trigger agent decisions

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 57: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 57

Semantic Web PoliciesAn e-learning scenario (IV)

ldquoWhile using my e-learning tool I only want to receive chat messages from my fellow students and my tutor Others get an automatic reply lsquoPlease contact me later I am busyrsquordquo

Communication Control

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 58: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 58

Semantic Web PoliciesAn e-learning scenario (V)

ldquoIn order to purchase learning material I use my Credit Card only with parties providing the lsquoOnline Security Certificatersquordquo

Agent NegotiationsPrivacy

Step 4

Step 1

Step 3

Step 2

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 59: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 59

Semantic Web PoliciesAn e-learning scenario Using policies

bull the whole system becomes more flexiblebull for different behavior change the policy (not the whole

software)bull communication in the community gets more

personalizedbull ldquoMy fellow students should not disturb

me when I am at workrdquobull automatically generated explanations

bull ldquoYou cannot send me a chat message because helliprdquo

bull ldquoYour tutoring agent alerts because helliprdquobull ldquoYou cannot access your fellowrsquos

homework because helliprdquobull policies are reactive

bull ldquoAs soon as I idle for two days send me helliprdquobull ldquoIf a deadline is extended then helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 60: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 60

Semantic Web PoliciesNaturally expressed as rules

If customers are younger than 26 give a 20 discount on international tickets

Up to 15 of network bandwidth can reserved if payment is done with an accepted credit card

Customers can rent a car if they are 18 or older and exhibit a driving license and a valid credit card

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 61: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 61

Semantic Web PoliciesBenefits

Explicit license for autonomous behaviourReusabilityEfficiencyExtensibilityContext-sensitivityVerifiabilitySupport for simple as well as sophisticated

agentsProtection from poorly-designed buggy or

malicious agentsReasoning about agent behaviour

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 62: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 62

Semantic Web PoliciesRequirements

Many policies one framework Integration with external sourcesPolicies as active objects

Executing actionsNegotiationsUser awareness and controlCooperative enforcement

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 63: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 63

Semantic Web PoliciesMany policies one framework

It is appealing to integrate all policies in one framework

One common infrastructure for interoperability and decision

making

Where policies can be harmonized amp coordinated

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 64: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 64

Exercise 1Revisited (II)

Were your policies requiring extra knowledge

Who are your colleagues and your professors

Who works in your project

What a valid credit card is

Distance between XYZ and the university is hellip XYZ is in Madrid I can not take the car if hellip time required for the trip from XYZ to the university would be hellip

referencing to properties of requesters

Sources of this information

All in our knowledge base

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 65: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 65

Semantic Web PoliciesIntegration with external systems

Policies are not islands

Decisions need data information and knowledge

Each organization has its own

Already available through legacy software and data

A realistic solution must interoperate with them

Third parties

Credit card sites for validity checking

External databases Variety of web resources

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 66: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 66

Semantic Web PoliciesPolicies are not only passive objects

Policies may specify Exchange of signed information (eg digital credentials) Event logging

Failed transactions must be logged Log downloads of new articles for one week

Communications and notifications Notify the administrator about repeated login failures

Workflow triggering such as (partly) manual registration procedures

ie Policies may specify actions To be interleaved with the decision process

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 67: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 67

Semantic Web PoliciesNegotiations

Step 1 Alice requests a service from Bob

Step 5 Alice discloses her VISA card credential

Step 4 Bob discloses his BBB credential

Step 6 Bob grants access to the serviceService

BobAlice

Step 2 Bob discloses his policy for the service

Step 3 Alice discloses her policy for VISA

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 68: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 68

Exercise 1Revisited (III)

Suppose

Your policy is given to you by your employer

You have to explain your policy

You submit a paper and you get ldquoRejectedrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 69: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 69

Semantic Web PoliciesUser awareness and control

Explain policies and system decisions Make rules amp reasoning intelligible to the common

user

Encourage people to personalize their policies Make it easy for users to write their own rules

Use natural language

ldquoAcademic users can download the files in folder historical_data whenever their creation date precedes 1942rdquo

Suitably restricted to avoid ambiguities

Fortunately users spontaneously formulate rules

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 70: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 70

Semantic Web PoliciesCooperative Policy Enforcement

Crucial for the success of a service

Never say (only) ldquonordquo

Encourage first-time users

Who dont know how to use your service

Explain policy decisions

Especially failures

Advanced queries Why not

Advanced queries How-to What-if

You canrsquot open this door but

you can ask Alice for permission

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 71: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 71

Semantic Web PoliciesSome solutions already available

Features available out of the boxExpressive policy languages and frameworks Integrated relational databases RDF stores

file systems requests time and location-aware packages etc

Execution of actions such as logging facilities exchange of credentials etc

Policy driven negotiations and preferencesAutomatically generated explanations

Demo at httppolicyL3Suni-hannoverde

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 72: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 72

OutlineReactive Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 73: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 73

Reactive PoliciesEvent-Condition-Action (ECA) Policies

provide a more flexible notion of policies so far policies were not able to react

ie to handle events so far actions where only included as internal or

provisional actions not as a re-action usually of the form

ON eventIF conditionDO action

ON receiving new call IF user not availableDO automatic reply

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 74: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 74

Reactive PoliciesEvents

trigger the execution of a rule can be simple events

eg ldquoON receiving new callrdquo or more complex

ON receiving new calland at the same time another call comes inand there were no calls in the last 10 minutes

to define complex events we need an event algebra

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 75: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 75

Reactive PoliciesEvent algebra

Assume events happen at a certain point of time The algebra allows us to combine events to create more

complex ones Example operators

Both E1 and E2 happens at the same time E1 happened before E2 m events out of n happened in an arbitrary order E1 and E2 occurred and E2 did not occur hellip

the complexity of the event algebra used depends on the purpose of the ECA-based system

events have to be stored in a history in order to check against complex combination of events

algorithms for the detection and tracing of complex events are non trivial

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 76: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 76

Reactive PoliciesConditions

bull handled like the policies we had so farbull they may include external actions to prove the

conditionsuch as a database or web service queryeg ldquohellip if the there is snow in Innsbruck hellip

rdquobull they may include negotiations to prove the

condition such as ldquohellipif Credit Card is valid helliprdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 77: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 77

Reactive PoliciesActions

bull could be single actionsbull could also be combinations of actions

Sequential execution Do Action1 and then Action2 and then

Action3 Parallel execution

Do Action1 and Action2 at the same time More complex combinations possible

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 78: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 78

Reactive PoliciesDo you use them

Do you think this is nothing you need to know about

Do you think you have never used this

Do you think this is too complicated for any user to use

Does this sound familiar to you

ON new e-mail arrivalIF subject contains ldquo[SPAM]rdquoDO move e-mail to folder ldquofiltered_spamrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 79: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 79

Reactive PoliciesMany other applications

bull DB triggers incremental maintenance of data (databases XML RDF etc)

bull cleansing of input data streamsbull automatic repairs in case of constraint violationbull broadcasting of changes in documents to subscribersbull maintaining statistics about website usagebull Active databases (update correlated fields in case

others are updated)bull network managementbull business processes (specification and

implementation)bull And many more

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 80: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 80

Reactive PoliciesA communication example

Problem The behavior of a messenger is not well adjustable

Most of you probably know this

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 81: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 81

Reactive PoliciesProblem

bull arbitrary people bother you with chat messagesbull they may even call youbull for some of them you want to offer an answering

machinebull some you just want to block bull people send you files ndash how could you trust thembull the messenger allows other calls while you are

currently answering a callbull although your messenger stores the

birthdays of your friends you forget about them because it does not remind you

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 82: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 82

Reactive PoliciesA possible solution with ECA-policies (I)

Why not use ECA-policies to let your agent solve the problem for you

ON new receiving callIF caller is a friend of mine

ANDthere is no other currently ongoing call

DO accept call AND put it on the speakers

ON new receiving fileIF sender is a friend of mine

ORsender provides a certificate AND certificate is valid

DO accept file AND store it on folder ldquoreceived_filesrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 83: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 83

Reactive PoliciesA possible solution with ECA-policies (II)

Even an automatic birthday reminder

ON new day (timer raised once per day)

IF there is a person in the winter school list

AND

it is hisher birthday today

DO send a chat message with text ldquoHappy Birthdayrdquo

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 84: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 84

Reactive PoliciesExercise 3 ECA Policies

See given exercise sheet

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 85: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 85

Reactive PoliciesExercise 3 Solution

Actions executed

Pop up window with a reminder about the exam registration

First call to my skype client Second call to my wifersquos phone

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 86: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla

Whythe Semantic Web

Introduction

Semantic Web Overview

Rule-Based Representation amp Reasoning

Semantic Web Policies

Reactive Policies

ConclusionsSummary

Apr 3rd 2008Universidad Autoacutenoma de Madrid 86

OutlineConclusionsSummary

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 87: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 87

ConclusionsSummary (I)

Hopefully this tutorial helped you to get a brief idea about

reasons that motivated Semantic Web Research a basic understanding of rule-based representation a basic introduction to reasoning techniques a basic understanding of requirements of current

distributed systems a motivation for the use of policies a basic introduction to rule-based policies and their

applications a basic introduction to reactive policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 88: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 88

ConclusionsSummary (II)

Everyday systemsagents take over new tasks we would otherwise perform ourselves

They can do somemany of them faster and better than us

But they are not ldquointelligentrdquo as we are

We need to tell them what to dohow to behaveRule-based Policies + reasoning help you to do that Dynamically and allowing evolution Flexibly With well defined semantics and interoperability At low cost

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 89: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 89

ConclusionsSummary (III)

But

That brings in many new issues like Required expressiveness for an application

scenario Usability problems User Awareness Verificationvalidation of policies hellip

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 90: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 90

ConclusionsFinal message

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 91: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 91

References

bull RDF Primerhttpwwww3orgTRrdf-primer

bull Antoniou et al Rule-based policy specification Secure Data Management in Decentralized Systems Springer 2007httpwwwl3sde~olmedillapub20072007_bookDDMS_rule_policiespdf

bull Bonatti Olmedilla Rule-based policy representation and reasoning for the semantic web In Reasoning Web Third International Summer School 2007 Springerhttpwwwl3sde~olmedillapub20072007_ReasoningWeb-policiespdf

bull Antoniou et al (Eds) Reasoning Web 2007 Springer LNCS 4636 pp1ndash153

bull Bradshaw et al Making Agents Acceptable to people Intelligent technologies for information analysis Advances in agents data mining and statistical learning SpringerhttpwwwihmcusresearchprojectsKAoSbiit-jeffpdf

bull De Coi et al Exploiting policies in an open infrastructure for lifelong learning In EC-TEL Crete Greece Sep 2007 Springer httpwwwl3sde~olmedillapub20072007_ec-tel_policiespdf

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies
Page 92: Introduction to  Semantic Web Rules & Policies

Daniel Olmedilla Apr 3rd 2008Universidad Autoacutenoma de Madrid 92

Questions

olmedillaL3Sde ndash httpwwwolmedillainfo

Thanks

  • Introduction to Semantic Web Rules amp Policies