Web-enabled Information Services for Engineering

Knowledge Management and Information Systems

Presentation at Telebalt conference, the 21st of October 2002

Jouni Meriluoto, Nokia Research Center

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WISE Project

Web-enabled Information Services for Engineering: Knowledge Management for Engineers [www.ist-wise.org]

European R&D project in IST programme

Duration 2001-2004

10 partners : Industrial: Airbus (France, Germany), Nokia Software providers: PACE, Interface, Cyberstream Universities (Helsinki, Berlin) Research institutes (Norske Regnesentral, Eurisco)

Approach: State of art, Requirements, Design, Implementation, Test

done

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WISE Keywords

Web-enabled - web technology is becoming the backbone for knowledge & information exchange. WISE intends to design a platform that enables easy integration of existing and future KM tools and approaches and making them easily accessible from everywhere.

Information - what is transferred among people: data, information and knowledge. Data is un-interpreted information, whereas knowledge is already processed information. Information is shared between systems and users. The scope of KM includes knowledge acquisition (education, training, purchase), formal and informal knowledge, knowledge maintenance, distribution and usage. KM is accomplished through changes in culture and process, supported by technology.

Services - In WISE, services are viewed as functions that need to be developed in order to empower the user – enabling them to design better product in shorter time, and more fluently.

Engineering - WISE supports engineers / designers – during their task of developing complex and safety critical products. Engineers produce a large amount of documents and knowledge. They interact among each other and with external bodies via documents. A goal of WISE is to ease this interaction process in order to improve the engineering processes. Engineering has special requirements towards Knowledge Management.

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Four Paradigms and Two Interpretations

Ontology (in philosophy) concerns beliefs about the form and nature of reality

Epistemology concerns the nature of knowledge and the relationship between those who know and knowing

Paradigms [Yolles]

1) Positivism2) Post-positivism3) Critical Theory

Postmodernism Poststructuralism

4) Constructivism Interpretations of Information [Virtanen]

1) Quantitative, based on probability2) Qualitative interpretation in a) Communication, b) Presentation,

and c) Processing

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Positivism

Ontology:

Reality can be apprehended,

Observer independent data: facts Epistemology:

Objectivity,

Possibility to find universal truths Simple belief in science in Western industrial history Mechanistic science extended to behaviourism in psychology Naïve systemic thinkers

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Post-positivism

Ontology: Objective realityApprehended imperfectly and probabilistically

Epistemology: Only a approximate image of reality is possible

"Engineering View" [Fivaz]

Observers can have their own perspective that can influence the way they see things.

Observers have consciousness which (in extension to simple behaviourism) is seen to be a set of engineering processes that converts information acquired as observation from "outside" into information implemented.

People can be better or worse at this engineering process, and at least fuzzy optimisation becomes relevant.

Mind is biased machine, reality is actually out there, and knowledge is objective.

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Critical Theory

Ontology:

Reality is virtual

Social, political, economic, ethnic and other factors shape reality Epistemology:

Subjectivist

Findings are value laden with respect to the world view of an inquirer

Inquiry is value determined in both postmodernism and poststructuralism

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Constructivism

There exists both local and specifically constructed realities Ontology:

Reality is relative phenomenon Epistemology:

Knowledge is created in interaction between inquirers in a situation and its participants

Subjectivist epistemology, relates to created findings

There are no observers, only viewers. Views, like behaviours are derived from worldview.

Interaction of different worldviews occurs through a semantic communication process [Luhmann]

Interaction occurs in a framework, "lifeworld" [Habermas] Cognitive oriented constructivist theories and Socially oriented

constructivist theories.

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Probability

Probability

SyntacticCommunication Semantic

Presentation in language

-novelty- content

- relative information

PhysicalExistence

Information Species based on probability – Quantitative interpretation

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Communication

Qualitative interpretation Pragmatic information

communication

ExpressiveTruth value

not necessary

-assumptions, moods, intuitions, beliefs

-absolute values, norms- questions, orders,

exclamations, requests…

Knowledge-relatedTruth value necessary

-singular,- general,

- explanatory,-instrumental,- evaluative

Value-novelty-utility

- exchange

Transmission-verbal

- non-verbal

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Presentation

Qualitative interpretation Presentation

DoxasticTruth value No evidence

- beliefs, intuitions, guesses…

Epistemic Truth value

Evidence

-singular- general

- explanatory- instrumental,

- evaluative

ModalNo truth value

- absolute values and norms

-experiences- commands, exclamations,

questions, advices…

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Processing

Qualitative interpretation Processing

Metadata Data-logicalData-derived

AlgorithmicNumeric

HeuristicSymbolic

Knowledge System

Procedural,declarative

DataNot processed

Media Data

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Semiotics

Knowledge resides in human beings - not in the media. However, in sociological constructivism the context is part of the knowledge.

KM system based on object-oriented analysis can utilise the concepts from qualitative information species.

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Semantics

Word

Significatio(meaning,sign)

Form Referent(Object)

Convention

Experience

Perception

Concept

Cognitive oriented constructivist theories emphasize the exploration and discovery on the part of each learner as explaining the learning process. Knowledge is still very much a symbolic, mental representation in the mind of the individual. But collaborative system for engineering needs a socially oriented approach.

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KM Systems as Technologies

Information technologies for managerial and professional workers evolved already several decades

Management Information Systems (MIS) Decision-Support Systems (DSS) Executive Information systems (EIS) Information Management Systems Artificial Intelligence Semantic Network Collaboration (Groupware…) (Re)engineering

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Information Systems as KM Tools

KNOWLEDGE MAPPING

ORGANIZATIONAL MEMORY

DOCUMENT MANAGEMENT SYSTEMS

KNOWLEDGE MANAGEMENT

INFORMATION RETRIEVAL

KNOWLEDGE DISCOVERY &DATA MINING

COLLABOR-ATION

ON-LINE TRAINING

UNDERLYING TECHNOLOGIES

Tools Survey

21.05.2002 - v4

IHMC Concept Map

Decision Explorer

Axon Idea Processor

OntoBroker / OntoEdit / OntoAnnotate

Cerebyte Infinos

QLoops Knowledge ManagementNetworks

Questmap

CyberDOCS

Documentum

Lotus Knowledge Discovery Server

Lotus K-station

Knowledge XChanger, Focus,Tribe

V66

Oculus CO

DioWeb Enterprise

dtSearch Engine

INQUERY

Omnidex

Verity K2

CART / MARS

SPSS tools

DataEngine

Darwin

OmniSpace Technologies

Caucus

Collaboration Fabricators

Communispace Corporation

KMTechnologies

Open Text - Livelink

LearnLinc

EduSystem

VCampus

Serf

LUVIT

Saba

Theorix

Learning Objectsstandardisation

Security Technology (Firewall Problem)

CAD-Systems and correspondinginterfaces

Middleware technology

KM Tool survey can be downloaded from www.ist-wise.org

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WISE System Architecture

WISE will support engineers with context-sensitiveknowledge management functions based on web technologies

DB1 DB2 DBn

knowledge base distribution mechanismknowledge base distribution mechanism

storagemanagement

modelling indexing

Eng. toolplug in 1

WISEKnowledgebase

WISEKnowledgeserver

Rulesdatabase

capture re-use monitoring

Process flowcontrol

Queryengine

display managementdisplay management

Mobileclient

Web Browser

WISEclients

Ad

min

istr

ati

ve

fun

cti

on

s

retrieval

Eng. toolplug in 2

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KM System as a Human Process

Knowledge management system, however, does not have to be a computer system. It can be a process of

finding, selecting, organizing, distilling and presenting information in a way that improves comprehension in a specific area of interest, and

acquiring, storing and utilizing knowledge for such things as problem solving, dynamic learning, strategic planning and

decision making.

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Human Factor Issues in Engineering

Knowledge = most important personal asset of an engineer in a quickly changing business environment

reluctance to share

Time pressure to get the job doneno time for documentation, making knowledge explicit,

abstraction…

Very high need for knowledge from previous experience, neighbouring departments

readiness to share?

The internet experience (easy access to tons of useful information)

experience that knowledge exchange works

Human factors form the basis for KM systems

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WISE Results

User interviews at three industrial sites what are the real needs of engineers regarding information and

knowledge? corporate KM strategies and instruments already in place 3 industrial scenarios with big common scope (80%!) High need for KM adapted to engineering needs Goal: Build a Knowledge Portal – get a focused access to all the

information you need, integrated with your work tools Challenges:

Multiple platforms & proprietary engineering tools Select information according to context Convince engineers and managers to share knowledge Provide methods and processes for practical KM

Holistic WISE approach: Looking at technological, organisational and human-factors issues

Thank you.www.ist-wise.org