Superimposed Information - INRIA - April 20011 Lois Delcambre Technology for Superimposed...

Superimposed Information - INRIA - April 2001 1Lois Delcambre (lmd@cse.ogi.edu)

Technology for

SuperimposedInformation

Lois Delcambre

with Shawn Bowers, David Maier, Mat Weaver

Database and Object Technology LabComputer Science and Engineering Department

Oregon Graduate Institute

Outline

• introduction to superimposed information

• a superimposed application: SLIMPad (DLI2 Project)

• model-based representation and transformation of information

• harvesting information to sustain our forests (NSF Digital Government project)

What is Superimposed Information?

data “placed over” existing information sources to:

highlight annotate elaborate select collect organize connect reuse information elements often to support new applications, beyond the original

Examples of Superimposed Information

Non-electronic examples:

Commentaries on religious texts, law, literature Concordances, citation indexes

Electronic examples:

Your bookmark file in your web browser RDF metadata

Why work on it now?

• Broadening range of digital information

• Accessibility/addressability to base information– Reference (e.g., URL) can be resolved quickly– Addressing at various levels of granularity

• Emerging Standards: RDF, Topic Maps, Xlink

• Emerging Applications: – Third Voice, Multi-Valent Documents, ...

The superimposed and base layers with marks

Superimposed Layer

BaseLayer

Information Source1

Information Source2

Information Sourcen

Focus: building generic technology

Superimposed Applications

enhanced base layerapplication

simultaneous use of base and

superimposedapplications

web browser(with extra functions such as annotation)

superimposedapplication

baseapplication1

baseapplication2

Outline

Paul Gorman, MD Lois Delcambre, PhDDavid Maier, PhD

Bundles in the wild………..Observational team:

Paul GormanJoan AshMary LavelleJason Lyman

…………..Bundles in captivityComputer science team:

Lois DelcambreDave MaierShawn BowersLongxing DengMathew Weaver

Let’s take a trip to the ICU

(Wild) Bundles

• manage information for diverse, complex tasks• contain selected, collected, structured, annotated• are often used in settings with:

– high uncertainty– low predictability– potentially grave outcomes– time & attention are highly constrained

(Wild) Bundles

• There is benefit in creating (active processing of information)

• There is benefit in reusing (trigger memory)

• There is benefit in sharing (establish collective, situated awareness)

Given….

• bundles are everywhere! • access to bundles provides access to important

information• information in bundles is often copied from other

information sources

• we can keep copied/referenced information linked through the use of marks

(Captive) Bundles

• SLIMPad - a scratchpad application to create bundles but….with marks linked electronically

• built using our architectural for building superimposed applications

• inspired by the observational work (but not focused on a specific medical task)

• a very simple tool … with minimal interface to base layer

SLIMPad demo

Superimposed Layer Information Manager (SLIM):Contributions of the Architecture

• Mark Management - to create/resolve marks

• SLIM DMI (data manipulation interface) - for the application developer

• TRIM store - for generic storage of superimposed information

Mark Management

SLIMPad

Mark Manager

Mark DB

XML Documents

PDF files

Web Pages

Excel Spreadsheets

PPT Files

Superimposed Information Management

XML Viewer

PDF Viewer

IE Explorer

MS Excel

MS PowerPoint

HTML Module

Excel Module

PowerPoint Module

XML Module

PDF Module

SuperimposedApplication

The general architecture for managingsuperimposed information

Superimposed Information ManagementApplication

ApplicationSpecific

GenericManagement

TRIMStore

creates and manages

Mark Management

SLIM API: as seen by application

Bundle

bundleName : StringbundleXPos : NumberbundleYPos : NumberbundleHeight : NumberbundleWidth : Number

scrapName : StringscrapXPos : NumberscrapYPos : Number

SLIMPad

padName : String Mark

markId : String

Structured Bundle Model for SLIMPad.

AbstractBundle

What’s Next for this Project?

• Validation - cardiologists, ICU nurses, …

• Extend the informational model of SLIMPad

• Extend SLIMPad to suit a selected medical task

• Validation of observational work and SLIMPad technology in another domain (forest information - preparation of a watershed assessment)

Outline

Schema Data

Instance Data with Marks

InformationSource1

InformationSource2

SuperimposedLayer

BaseLayer

marksmarks

Model-Based Superimposed Information

But the model and schema are optionalBut the model and schema are optional

Our Goals

• Represent superimposed information generically, for various data models (with the schema optional)

• Build a single management system for superimposed information

• Mix information from various models

• Convert information from one representation scheme to another

Transforming Information

Generic Rep. (XML model)

convert

Generic Rep.(Topic Map model)

XML Viewer

TM BrowserPainting Painter

by painter

Influenced by

mentioned biographymentionedcritiqued

convert

Generic Rep.(Relational model)

Our Approach

• Metamodel – to represent multiple data models

• Generic, Uniform Representation Scheme– to store model, schema, and instances for model-based

information

• Mapping Formalism – to transform between representation schemes

The Metamodel

• Provides a level of abstraction above models• Describes the structural features of models

Topic Map

Topic Map Defintions

Topic Map Instances

XML Document

Basic Set of Abstractions

Model Constructs and Relationships

Schema-LevelData

Instance-LevelData

Metamodel

XML Model, Schema, and Instance• Elements, Element Types, Attributes, Attribute Types• Elements contain Attributes• Elements can be nested

<!ELEMENT schedule (flight*)><!ELEMENT flight (from, to, price)><!ATTLIST flight name CDATA #REQUIRED>

XMLModel

XML DTD(Schema)

XML Document

(Instances)

Model constructs and relationships defined using the metamodel

Topic Map Example

Painting Painterby painter

Influenced by

“Captive” “Paul Klee”by painter influenced by

“Francisco de Goya”

“1914”by painter

mentioned biographymentioned

mentionedhttp://...

biography biography

http://...http://...

critiqued

mentioned

http://...

Topic Map Model in UML

TopicType

ttypename : String

TopicRelType

relType : String

AnchorType

anchorRole : String

TopicInstance

title : StringtopicInsID : Number

TopicRelInst

AnchorInst

<<Mark>>Address

markID : String

<<conformance>>topic_instOf

<<conformance>>rel_instOf

<<conformance>>anchor_instOf

address

topicInstopicType

topicType1

topicType2 1 1

topicIns1

topicIns2

Generic, Uniform Representation

• We use RDF and RDF Schema to represent model, schema, and instance uniformly

http://…/~johncreator (creator, ‘http://…/~john’, person1)

(name, ‘person1’, ‘John Smith’)

ClassProperty

creator

Person

WebPagetype

domain

(type, ‘creator’, Property)(domain, ‘creator’, WebPage)(range, ‘creator’, Person)(type, ‘Person’, Class)(type, ‘WebPage’, Class)

person1 ‘John Smith’name

RDF TriplesRDF Graph

RDF Schema TriplesRDF Schema Graph

The Metamodel Definition

Construct StructuralConnector

Mark Lexical Conformance Generalization

connects 2 constructsBasic

MetamodelElements

Special Elements

Construct: A basic structural unit

Mark: A connection-point to the base-layer

Lexical: A primitive-value type

Connector: A relationship between 2 constructs

Conformance: A schema-instance relationship

Generalization: An inheritance relationship

Representing Models

(instanceOf, “TopicType”, Construct)(instanceOf, “TopicInstance”, Construct)

(instanceOf, “topic_instOf”, Conformance)(domain, “topic_instOf”, TopicInstance)(range, “topic_instOf”, TopicType)(domainMult, “topic_instOf”, “*”)(rangeMult, “topic_instOf”, “1”)

(instanceOf, “ttypename”, Connector)(domain, “ttypename”, TopicType)(range, “ttypename”, String)(domainMult, “ttypename”, “*”)(rangeMult, “ttypename”, “1”)

TopicType

ttypename : String

TopicInstance

<<conformance>>

topic_instOf

Representing Schema(instanceOf, “painting_tt”, TopicType)(ttypename, “painting_tt”, “painting”)(instanceOf, “painter_tt”, TopicType)(ttypename, “painter_tt”, “painter”)

(instanceOf, “byPainter_rt”, TopicRelType)(relType, “byPainter_rt”, “by painter”)(topicType1, “byPainter_rt”, painting_tt)(topicType2, “byPainter_rt”, painter_tt)

(instanceOf, “biography_at”, AnchorType)(anchorRole, “biography_at”, “biography”)(topicType, “biography_at”, painter_tt)

Topic Types (schema):painting, painter

Topic Rel Types (schema):by painter

Anchor Types (schema):biography

painting painterby painter

biography

Representing Instances(instanceOf, “painter1”, TopicInstance)(title, “painter1”, “Paul Klee”)(topicInsID, “painter1”, “5”)(topic_instOf, “painter1”, painter_tt)(instanceOf, “painting1”, TopicInstance)(title, “painting1”, “Captive”)(topicInsID, “painting1”, “19”)(topic_instOf, “painting1”, painting_tt)

(instanceOf, “byPainter1”, TopicRelInst)(rel_instOf, “byPainter1”, byPainter_rt)(topicIns1, “byPainter1”, painting1)(topicIns2, “byPainter1”, painter1)

(instanceOf, “biography1”, AnchorInst)(anchor_instOf, “biography1”, biography_at)(address, “biography1”, a1)

(instanceOf, “a1”, Address)(markID, “a1”, “URLMarkManager@954308545”)

Topic (instances):Paul Klee, Captive

Topic Relationship (instance):a by painter relationship

Anchor (instance):a biography anchor

Address (instance):mark to URL

Basic Types of MappingsMapped

Converted

Inter-Model

Inter-Schema

Model-to-Schema

Model2

Schema1

Instances1

Model1

Schema1

Instances1

Model1

Schema1

Instances1

Model1

Schema1

Instances1

Model1

Schema2

Instances1

Model2

Schema2

Instances2

Mapped

S(‘source’, (‘instanceOf’, X, ‘TopicInstance’))S(‘target’, (‘instanceOf’, X, ‘XMLElem’))

XMLElemTopicInstanceMapped

Mapping Rules

Simple production rules over triples

Mapping Rules (cont.)

XMLElemTopicInstance

XMLElemTypeTopicType

Mapped elem_instOftopic_instOf

S(‘source’, (‘topic_instOf’, X, Y))S(‘target’, (‘instanceOf’, X, ‘XMLElem’))S(‘target’, (‘instanceOf’, Y, ‘XMLElemType’))S(‘target’, (‘elem_instOf’, X, Y))

SuperimposedApplication

The general architecture for managingsuperimposed information

Superimposed Information ManagementApplication

ApplicationSpecific

GenericManagement

TRIMStore

creates and manages

Mark Management

Applications

• SLIM Pad– Scratchpad application with Bundle-Scrap model

(uses superimposed information)

• XML Extractor– “Extracts” XML information and transforms it into a Topic Map for

searching/browsing

• Translation among message formats:IDMEF - Intrusion Detection, CISL, SNMP v3, ...

XML FilesGeneric Rep.(XML model)

Generic Rep.(TM model)

Topic Map Browser

XML Extractor

out mapped storedin

What’s Next for this Work?

• Extending the metamodel - to accommodate broader range of models

• Formalizing the metamodel

• Develop abstract addressing modes (for canonical marks - with translation to various instantiations)

Harvesting Information to Harvesting Information to Sustain our Forests:Sustain our Forests:

Creating anCreating anAdaptive Management PortalAdaptive Management Portal

NSF DIGITAL GOVERNMENT PROGRAMNSF DIGITAL GOVERNMENT PROGRAM

Tim Tolle & Lois DelcambreTim Tolle & Lois Delcambrettolle@fs.fed.us lmd@cse.ogi.eduttolle@fs.fed.us lmd@cse.ogi.edu

Co-Project DirectorsCo-Project Directors

Project focuses on the:

Adaptive Management

USDA Forest ServiceUSDI Bureau of Land

ManagementUSDI Fish and Wildlife Service

Adaptive Management Portal: a value-added, Internet-based service

• Provide multiple access paths to forest information.

• Preserve local autonomy and local focus of each site.

• Support diverse users and types of information.

• Use proposed, existing, and de facto standards for content, classification, and technology.

• Be low-cost, scalable, extensible.

Project Funding

• Duration: 3 years

• Budget: $1.5 million

• Principal financial sponsors– National Science Foundation– Bureau of Land Management (Oregon State Office)– Forest Service (R-6 and PNW Station)– National Park Service (Western Region)

Team MembersTeam Members

Tim Tolle Tim Tolle Regional Coordinator for AMA, US Forest ServiceRegional Coordinator for AMA, US Forest Service

Eric LandisEric Landis Forest Information System Specialist, ConsultantForest Information System Specialist, Consultant

Craig PalmerCraig Palmer Natural Resources Monitoring Expert, UNLVNatural Resources Monitoring Expert, UNLV

Fred PhillipsFred Phillips Professor, Head, Mgt. of Science and Tech., OGIProfessor, Head, Mgt. of Science and Tech., OGI

Patty ToccalinoPatty Toccalino Asst. Prof., Environmental Science and Eng., OGIAsst. Prof., Environmental Science and Eng., OGI

Lois DelcambreLois Delcambre Professor, Computer Science and Eng., OGIProfessor, Computer Science and Eng., OGI

David MaierDavid Maier Professor, Computer Science and Eng., OGIProfessor, Computer Science and Eng., OGI

Shawn BowersShawn Bowers PhD Student, Computer Science and Eng., OGIPhD Student, Computer Science and Eng., OGI

Mat WeaverMat Weaver PhD Student, Computer Science and Eng., OGIPhD Student, Computer Science and Eng., OGIForest/environmental expertiseForest/environmental expertise Computer science expertiseComputer science expertise

Staff Scientist, Pacific Northwest National LaboratoryMark Whiting

Science Advisor, USDI, National Park ServiceRegina Rochefort

Communications Director, USDA Forest Service, PNW Research StationCynthia L. Miner

Chief, Office of Technical Support, Forest Resources, USDI Fish and Wildlife ServiceMonty Knudsen

Executive Director, IMFN SecretariatFred Johnson

MD, Asst. Professor, Division of Medical Informatics and Outcomes Research, OHSU Paul Gorman

Sustainable NorthwestMartin Goebel

USDA Forest Service, Pacific NW RegionRobert Devlin

President, IUFRO, Oxford Forestry Institute, Dept of Plant SciencesJeff Burley

Co-Inventor of the Topic Map ModelMichel BiezunskiAdvisory Board

Forest/environmental expertiseForest/environmental expertise Computer science expertiseComputer science expertise

Task 1 – Status• Workshops @ Snoqualmie Pass Adaptive Management Area,

Cle Elum, WA (June and July)

• Interviews with Forest Service Corvallis Forest Sciences Lab and USGS FRESC, Corvallis (August)

• Interviews with Central Cascades Adaptive Management Area, Eugene (August)

• Interviews with the Applegate Partnership and its associated agencies (August)

• Rainier National Park (planned for October)

Things we’ve learned from Task 1 NSF Digital Government

• work is project-based

• multiple agencies are involved

• each agency serves as information gatherer; information broker; information consumer

• primary product is information: assessments, studies, surveys, environmental impact statements

• even though information is a primary product, information technology is secondary (stewardship of the land is the primary mission)

Building the Sandbox …to support similarity search

across multiple domains

Documents

•“Document” used very loosely – could be just about anything•Vary in format (text, map, dataset, …)•Vary in purpose (formal assessment, informal letter, …)

Traditional Metadata

Author: Parley PrattPurpose: Environmental AssessmentLocation: Wenatchee National ForestKeyword: Interstate 90Keyword: Snoqualmie Pass

•Fields with values•May or may not use “controlled vocabulary”•Allows for basic searches

Enhanced Metadata

Parley Pratt

Author

Environmental Assessment

PurposeWenatchee

National Forest

Location

Interstate 90

Snoqualmie Pass

Keyword

• Instead of fields and values, we use explicit properties and terms

• Metadata is represented by connecting a document with a term via a property

Enhanced Metadata

Parley PrattAuthor

Purpose

WenatcheeNational Forest

Location

Interstate 90

Snoqualmie Pass Keyword

Editor

Cle ElumRanger District

Super Enhanced Metadata

Parley PrattAuthor

Purpose

Location

Interstate 90

Editor

Explicit hierarchy of properties and terms allows for enhanced

searching.

Super-Duper Enhanced Metadata

Parley PrattAuthor

Purpose

Location

Interstate 90

Editor

WesternHemlock

Additional relationships of various types between terms allow for super-

duper enhanced searching (i.e. similarity

search, …)

For More Information

• www.cse.ogi.edu/footprints

• www.cse.ogi.edu/forest

• lmd@cse.ogi.edu Lois Delcambre• maier@cse.ogi.edu Dave Maier• shawn@cse.ogi.edu Shawn Bowers• mweaver@cse.ogi.edu Mat Weaver

Research Issues

• Models for the superimposed layer• How does the superimposed model influence the

capabilities it supports?• How does the form of superimposed information

affect the effort to construct and maintain it?– Are some forms more robust to updates in the base layer– What forms map onto current information management tools

Research Issues (2)

• Challenges when superimposed and base layer have different models– E.g., structured over unstructured, or vice versa

• Bi-level tools– Browsing between layers– Queries over both layers

• How do we delimit the universe of discourse in the base layer?

• Is it easier to fuse superimposed information than base information?

Research Issues (3)

• Variations on the conceptual architecture– Commingled layers– “Super-superimposed information”

• How do capabilities of base layer affect structure and operations over superimposed information?– Addressing modes– Address comparison– Querying

• Addressing for non-web sources– Relational, object-oriented DBs

Research Issues (4)

• How to extend DBMSs to better deal with information they don’t store.

• How to help population superimposed information spaces.

• What are good formats for representation and exchange of superimposed information?

Why Databases Don’t (Currently) Solve It

• Seems closely related to view and data integration• However

– Superimposed information can’t always be derived from the base data

– DB approaches assume schema and common model– DBs like to work with data they control– Traditional approaches are heavy weight

• semantic analysis• schema integration• query mapping• On a source-by-source basis

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