Ontologies: What, Why, and Ontologies: What, Why, and How?How?

Jon Corson-Rikert, Mann Library

Metadata Working Group

4/18/03

What problems are we trying to What problems are we trying to solve?solve?• Problems with content

• Inconsistency• Incompatibility• Incompleteness• Unboundedness

• Need for Automation• Discovery• Filtering• Assembly• Interoperability

Why consider ontologies?Why consider ontologies?

• Sharing common understanding of the structure of information among people or software agents

• Codifying domain assumptions· Terminology· Relationships

• Reuse of domain knowledge

• Improving information retrieval success• Augmenting or refining search terms

· Preferred terminology· Discriminating among alternative meanings (e.g., WordNet)

• Language translation• Bridging across domains

The Evolution of Knowledge The Evolution of Knowledge ManagementManagement

Libraries/Archives/File Systems/Websites

Bibliographic Catalogues Machine Index Catalogues

Human Indexing Machine Indexing

Statistical Analysis by Machines

Bibliographies/Output from Fulltext Search Engines

Books, Magazines, Articles Databases, Webpages

Pre- Web Web Semantic Web

Electronic Repositories

Machine Readable Metadata Repositories

Machine Indexing Human Indexing

Semantical Analysis by Machines

Knowledge based specialized webportals

Defined Electronic Information Elements

Knowledge Mining

Ontologies

Libraries/Archives/File systems

Bibliographic Catalogues on Cards or Computers

Human Indexing

Bibliographies

Reviews

Human reading, checking and classifying

Books, Magazines, Articles, ….

Thesauri, Classification Schemes, Glossaries,

Johannes Keizer, FAO

What is an ontology? - 1What is an ontology? - 1

A thesaurus on steroids• Ordered terminology• Prescribed relationships among terms

What is an ontology? - 2What is an ontology? - 2

A shallow classification of basic categories

• Defines categories, and hence terminology

• Defines rules

(Soergel 1999)

What is an ontology? - 3What is an ontology? - 3

In information science:

A characterization, through formal, explicit knowledge, of the intended meanings and relationships of a vocabulary of concepts

(Gruber 1993)

What is an ontology? - 4What is an ontology? - 4

A formal explicit description of concepts in a domain of discourse (classes, or concepts),

with properties of each concept describing various features and attributes of the concepts (slots, roles, or properties)

and restrictions on slots (facets).

An ontology together with a set of individual instances of classes constitutes a knowledge base

(Ontology 101)

Ontologies have …Ontologies have …

ConceptsRelations between concepts

• Synonyms• Class/subclass (broader/narrower; dog is to mammal)• Membership (“is a”: Spot is a dog )• Part/whole (hand is part of arm, car has fender)• Inverse (e.g., pest damages plant so plant is damaged by pest)

Axioms (properties and attributes of concepts)• Definitions specifying both necessary and sufficient criteria

for membership• Constraints such as domain and range, minimum or maximum

number of values

Ontologies will (eventually) Ontologies will (eventually) support:support:

Automatic classification and query• Where does a target word or phrase fit into the ontology• Locating a concept or a cluster of concepts based on a

description and/or relationships• Vocabulary switching between domains

Inference• Using relationships to determine, given A and B, what C

might be and how you know it• Analysis to enhance navigation

Consistency checking

From common data to common From common data to common structurestructure• Controlled vocabulary

• Very simple structure (nearly flat)• The terms are the data

• Taxonomy• Primarily to define position within a hierarchy – e.g., species

• Thesaurus• More options for relationships• Often leverages retrieval and organization of additional data

• Meta-thesaurus• A federation of similar thesaurus structures to allow bridging data across

languages or across domains

• Ontology• Whatever can’t be done by the above

Typical thesaurus Typical thesaurus implementationimplementation

• A controlled vocabulary or thesaurus limited to the domain

• A set of separate database tables, each with predictable attributes• People• Departments• Resources

• Thesaurus cross-references this content for internal navigation

• Incoming keyword queries can provide a rich context of links to data tables

Website with thesaurusWebsite with thesaurus

Queries

People

Orgs

Projects

Publications

Crops

Genes

Thesaurus

http://mcknight.ccrp.cornell.edu

Thesaurus as leveraging agentThesaurus as leveraging agent

2nd thesaurusInput query

Refinement

thesaurus

3rd thesaurus

then search against

data warehouse

Gazetteer as leveraging agentGazetteer as leveraging agent

Scenario:• User finds library record (e.g., book or photo) with place name reference

(e.g., neighborhood in L.A.)• Place name and desired action sent to gazetteer (e.g., find other photos in

nearby L.A. neighborhoods using appropriate historical neighborhood names)

• Gazetteer matches incoming place name with coordinate footprint• Other place names near footprint and in L.A. retrieved• Records related to neighboring places returned to user

Requires:• Structured data (place names, coordinates)• Relationships (historical to modern names, neighborhoods to city)• Functionality (coordinate-based spatial analysis)

Agriculture Heritage ProjectAgriculture Heritage Project

• Wide variety of content from diverse organizations

• Open-ended content

• Time and place as first-order variables

• Data likely to cluster by theme, time, and place

• Many areas with sparse data

• Need to appeal to diverse audiences

• Need to produce independently functional results

• Goal: transform flat archives into dynamic context of people,

places, and events

ApproachApproach

• Simple underlying content model

• Adaptive relationships among content

• Sometimes very detailed

• Often very general

• Approachable from any viewpoint

• Time, space, originating organization, historical event, personalities,

crops, thematic interests

• Capability for encapsulation and export as curricular units

The ABC Ontology ModelThe ABC Ontology Model

• A rich model incorporating time, place, and events as well as information more traditionally encoded in metadata

• Designed for exchange and interoperability as RDF-XML metadata

• A set of generalized classes and canonical relationships among them

• An ontology framework independent of the data it accompanies

time place

agent artifact

item

action event situation

actuality temporalityabstraction

Entity

manifestation

work

ABC Ontology classesABC Ontology classes

ABC Ontology diagrams - 1ABC Ontology diagrams - 1

EV0 ST0 EV1 ST1

Events precede or follow situations

creation publication

EV2

acquisition

ABC Ontology diagrams - 2ABC Ontology diagrams - 2

EV0 ST0 EV1 ST1

creation publication

EV2

acquisition

Most agents, actions, times, and places modify events

AC0

AG0

hasAction

hasAgent

inPlace

atTime

AC1

photographer

photo taken

AG1

photo published

publishing house

ABC Ontology diagrams - 3ABC Ontology diagrams - 3

Manifestations exist in situations

EV0 ST0 EV1 ST1

creation publication

EV2

acquisition

MN1

the photo

color transparency original MN0 MN2

color print

poster

MN3

hasRealization

hasRealization

isPartOf

Kodak archive

collection

contains

contains

instanceOf

the poster

WK0Tulips

Complete ABC diagramComplete ABC diagram

Source: http://metadata.net/harmony/cimi_modelling.htm

Source: http://metadata.net/harmony/cimi_modelling.htm

ABC class-property relationshipsABC class-property relationships

• Set of canonical relationships• All bi-directional (inverses)• Provide a domain of possible connections• Serve as the basis for model traversal

ABC class-property relationships - 1ABC class-property relationships - 1

Entity-Entity contains - isPartOf

Entity-Place inPlace - isLocationOf

Actuality-Actuality hasPhase - isPhaseOf

Actuality-Situation inContext - isContextFor

Work-Manifestation hasRealization - isRealizationOf

Manifestation-Item hasCopy - isCopyOf

ABC class-property relationships - 2ABC class-property relationships - 2

Temporality-Agent hasParticipant - isParticipant

Temporality-Actuality involves - isInvolvedIn

transforms - isTransformedBy

usesTool – usedAsToolIn

destroys - isDestroyedBy

hasResult - isResultOf

creates – isCreatedBy

Event-Action hasAction – isActionOf

Event-Agent hasPresence – isPresentIn

Situation-Event precedes - isPrecededBy

follows - isFollowedBy

Work in progressWork in progress

Demo of Agriculture Heritage site prototype

Is it worth it?Is it worth it?

• It’s worth exploring

• Must be easier to build

• Useful to rethink typical site structure

• Not clear how to leverage all the potential power

• Need more use cases

• What does it mean for metadata?

ReferencesReferences

• “Indirect geospatial referencing through place names in the digital library: Alexandria Digital Library experience with developing and implementing gazetteers,” Linda L. Hill, Zi Zheng, Proceedings of the American Society for Information Science Annual Meeting, Washington, D.C., Oct. 31- Nov. 4, 1999, pp. 57-69.

• “Ontology Development 101: A Guide to Creating Your First Ontology”, Natalya F. Noy, Deborah L. McGuinness, Stanford University, Stanford, CA 94305

• “Science and the Semantic Web,” James Hendler, Science, vol. 299, 1/24/03

• “The ABC Ontology and Model,” Carl Lagoze and Jane Hunter, Journal of Digital Information, volume 2 issue 2, November, 2001.

• “The Rise of Ontologies or the Reinvention of Classification,” Dagobert Soergel, Journal of the American Society for Information Science, 50(12):1119-1120, 1999

• “Toward Principles for the Design of Ontologies Used for Knowledge Sharing,” Thomas R. Gruber, Revision: August 23, 1993, Stanford Knowledge Systems Laboratory