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Ontologies

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What are ontologies?

•originally, the filed dedicated to study the nature of everything

•sometimes referred to simply as knowledge bases

•aim to provide a common language to support knowledge sharing

•systems that implements tasks that use knowledge (and thus somehow perform knowledge sharing) should all guarantee a common language

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Catalog/ ID

Terms/ glossary

Thesauri "narrow term"

relations

Informal is-a

Formal is-a

Formal instance

(is-an-example of?)

Frames (properties)

Value Restrictions

General Logical constraints

Disjointedness Inverse, part-of

A Spectrum of Ontologies (from Lassila & McGuinness)

"Simple" vocabulary control Definitions, semantic links logical propositions supported

increasing complexity

Ref: O. Lassila & D. L. McGuinness. The Role of Frame-Based Representation on the Semantic Web. Knowledge Systems Laboratory, January, 2001. Available at: http://www.ksl.stanford.edu/KSL_Abstracts/KSL-01-02.html

WHAT IS AN ONTOLOGY?

From K. McCain presentation March, 2002

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Ontologies in AI• Artificial intelligence researchers have

adopted ontologies as a comprehensive knowledge representation formalism to provide commonsense reasoning in support of knowledge tasks such as knowledge acquisition and reuse.

• Lenat DB (1976) AM: An Artificial Intelligence Approach to Discovery in Mathematics as Heuristic Search. PhD thesis, Stanford University

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What are ontologies (in AI)?

“Ontologies are explicit specifications of

conceptualizations.”

most cited definition from Gruber (1993)

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What are ontologies (in AI)?

Ontologies are explicit descriptions of shared conceptualization:

1. explicit 2. descriptions3. shared4. conceptualization

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1. explicit

• Has to be explicitly defined through descriptions

• types and constraints are explicitly defined

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2. descriptions

• concepts (or classes) in a domain• properties of each concept

describing various features and attributes

• and restrictions on the attributes (facets)

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3. shared

• Common to members of a domain/field

• Consensual knowledge– not private to one individual, accepted

by a group

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4. conceptualization

– Interpreted concepts– conceptual (abstract) model of a

domain through its relevant concepts

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Types of Information

concepts, atomic typescardinality of constraintsis-a hierarchy among

conceptsrelationships between

concepts

taxonomies of relations

reified statementsaxiomssemantic

entailments

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Universal Semantic Relationships

STRICT INCLUSION – X is a kind of Y SPATIAL – X is a place in Y; X is a part of Y CAUSE-EFFECT – X is a result of Y; X is a cause of Y RATIONALE – X is a reason for doing Y LOCATION FOR ACTION – X is a place for doing Y FUNCTION – X is used for Y MEANS-END – X is a way to do Y SEQUENCE – X is a step (stage) in Y ATRTRIBUTION – X is an attribute (characteristic)

of Y

From Spradling, The Ethnographic Interview

From K. McCain presentation March, 2002

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Types of Ontologies

• Domain– Additional specializations are possible

• applications, tasks

• Linguistic– Account for grammar and meanings in a

natural language e.g., WordNet for American English

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Uses of domain ontologies

•interoperability among information systems

•semantic web: link, coordinate software agents

•sharing knowledge bases among KBS•intelligent retrieval, search

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Why ontologies for KBS?

• identify specific classes of objects and relations that exist in some specific domain

• need to understand and share common concepts of a domain by different systems

• multiple systems can use one same ontology and exchange knowledge and information without conflict

• ontological analysis captures the intrinsic conceptual structure of a domain and is the essential step in building coherent knowledge bases

• represent facts (propositions) in a domain by combining terms and concepts

• represent attitudes, e.g., hypothesize, believe, expect, hope, desire, fear, predicts, plans

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Ontologies vs. knowledge bases

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

•ontology is a basic structure around which a KB can be built

•knowledge bases represents what is true about a domain by using terms and concepts defined in the ontologies

•building an ontology implies that the representation language and the ontological analysis can be reused

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Ontologies supporting NLU• natural language understanding

– Syntactic Analysis (Parsing)– Semantic Analysis– Pragmatic Analysis

• natural language interfaces• information systems, Artificial Intelligence systems• search engines• machine translation• developing an ontology with ML from a collection of

documents and the end-user to support domain-independent information extraction (IJCAI 01)

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ES methodology

knowledgebase

(e.g.,framesand methods)

knowledgebase

(e.g.,framesand methods)

explanationexplanation

generalknowledgegeneral

knowledge

userInterface

userInterface

expertproblemexpert

problem

expertsolutionexpert

solution

inferenceengine

(agenda)

inferenceengine

(agenda)

working memory(short-term mem/information)

working memory(short-term mem/information)

Knowledge acquisitionKnowledge acquisition

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ES supported by ontologies

knowledgebase

(e.g.,framesand methods)

knowledgebase

(e.g.,framesand methods)

explanationexplanation

expertproblem

expertproblem

expertsolution

expertsolution

inferenceengine

inferenceengine

workingmemoryworkingmemory user

Interface

userInterface

domain specific

application specific top level

natural language

Knowledge acquisitionKnowledge acquisition

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Ontologies supporting ES

domain specific

application specific

top level

natural language

expert problem

expert solution

reasoning

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ontologies supporting CBR

domain specific

application specific

top level

natural language

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Development steps • Determine the domain and scope • Consider reusing existing ontologies • Enumerate important terms in the

ontology • Define the classes and the class

hierarchy• Define the attributes of classes (slots) • Define the facets of the slots • Create instances

from Noy & McGuinness

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Ontologies development process

• ontology development is an iterative process

determinescope

considerreuse

enumerateterms

defineclasses

considerreuse

enumerateterms

defineclasses

defineproperties

createinstances

defineclasses

defineproperties

defineconstraints

createinstances

defineclasses

considerreuse

defineproperties

defineconstraints

createinstances

from Noy & McGuinness

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Some challenges•hugeness

–amount of knowledge is overwhelming

•interaction–nature of problem to be solved–type of inference strategy to use

•multiple views–difficult consensus

•dynamic world–reorganization, maintenance

•context (not represented)•all impact on construction, reusability,

interfacing

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Ontology editors(development environments)

• ONTOLINGUA http://ontolingua.nici.kun.nl• WEBONTO* http://kmi.open.ac.uk/projects/webonto/• PROTEGEWIN http://smi-web.stanford.edu/projects/prot-

nt/

• ONTOSAURUS* http://www.isi.edu/isd/ontosaurus.html

• ODE• KADS22Duineveld, A.J., Stoter, R., Weiden, M.R., Kenepa, B. and

Benjamins, V.R. (2000). WonderTools? A comparative study of ontological engineering tools. International Journal of Human-

Computer Studies 52(6): 1111-1133.

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Du

ineveld

et a

l.,20

00

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Looking at some ontologies• Open University• http://kmi.open.ac.uk/projects/webonto

/

• http://www.isi.edu/isd/ontosaurus.html• USC/Information Sciences Institute

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These slides were built mainly based on:

• Noy, Natalya F. and McGuinness, Deborah L. . Ontology Development 101: A Guide to Creating Your First Ontology. Stanford Knowledge Systems Laboratory Technical Report KSL-01-05 and Stanford Medical Informatics Technical Report SMI-2001-0880, March 2001. Online:http://protege.stanford.edu/publications/ ontology_development/ontology101.html

• B. Chandrasekaran, John R. Josephson, and V. Richard Benjamins What Are Ontologies, and Why Do We Need Them? Intelligent Systems & their applications Vol. 14, No. 1, January/February 1999

• Tautz, C. empolis

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Further Reading• van Heijst, G. (1995) The Role of

Ontologies in Knowledge Engineering, PhD thesis, University of Amsterdam.

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Bibliography (i)1          IntroductoryChandrasekaran, B.; Josephson, John R. and Benjamins, V.

Richard. What Are Ontologies, and Why Do We Need Them? Intelligent Systems & their applications Vol. 14, No. 1, January/February 1999 .

Gruninger, M. and Lee, Jintae. Ontology Applications and Design. Guest Editors. Communications of the ACM, Vol. 45, No. 2 February, 2002.

Guarino, N. and Poli, R. The role of ontology in the information technology. Int’l J. Human-Computer Studies, Vol. 43, Nos. 5/6, Nov-Dec. 1995, pp. 623-965.

Heijst, G. van Schreiber, A. Th. and Wielinga, B. J. Using explicit ontologies for KBS development. International Journal of Human-Computer Studies, 46(2/3):183-292, 1997.

Swartout, William and Tate, Austin Guest Editors' Introduction: Ontologies Intelligent Systems & their applications Vol. 14, No. 1, January/February 1999

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Bibliography (ii)Gruber, T. A translational approach to portable ontologies. Knowledge

acquisition, vol. 5, no.2, 1993, pp. 199-220.Tautz, C. Tutorial on Practical Ontology Construction. ,Bertelsmann

Mohn Media Group, empolis, Germany (unpublished slides).

2          ApplicationsAndre Valente, Thomas Russ, Robert MacGregor, and William Swartout

Building and (Re)Using an Ontology of Air Campaign Planning Intelligent Systems & their applications Vol. 14, No. 1, January/February 1999

Mariano Fernández López, Asunción Gómez-Pérez, Juan Pazos Sierra, and Alejandro Pazos Sierra Building a Chemical Ontology Using Methontology and the Ontology Design Environment Intelligent Systems & their applications Vol. 14, No. 1, January/February 1999

Gleb Frank, Adam Farquhar, and Richard Fikes Building a Large Knowledge Base from a Structured Source Intelligent Systems & their applications Vol. 14, No. 1, January/February 1999

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2.1        Ontologies and Knowledge ManagementV.R. Benjamins, D. Fensel, A. Gómez Pérez  link Knowledge Management

through Ontologies  Ulrich Reimer (ed.) PAKM 98 Practical Aspects of Knowledge Management. Proceedings of the Second International Conference  Basel, Switzerland, October 29-30, 1998.

Motta,Enrico; Shum, Simon Buckingham and Domingue, John. Ontology-Driven Document Enrichment: Principles, Tools and Applications. International Journal of Human-Computer Studies, 52, (6), 1071-1109.

O’Leary, D. E. (1998). Using AI in Knowledge Management: Knowledge Bases and Ontologies. Intelligent Systems, 13, 3, pp. 34-39.

2.1.1        Web portalsStaab, S.; Jürgen, A.; Decker, S.; Erdmann, E.; Hotho, A.; Maedche, A.;

Schnurr, H.P.; Studer, R.; Sure, Y. (2000). AI for the Web - Ontology-based Community Web Portals. Proceedings of the 17th National Conference on Artificial Intelligence and 12th Innovative Applications of Artificial Intelligence Conference, AAAI 2000/IAAI 2000, Menlo Park/CA, Cambridge/MA, AAAI Press/MIT Press.

Bibliography (iii)

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3. Design and development of ontologies

Benjamin, J., Borst, P., Akkermans, J., & Wielinga, B. (1996). Ontology construction for technical domains. In Shadbolt, N., editor, Proceedings 9th European Knowledge Acquisition Workshop EKAW'96, pages 98-114, Berlin. Springer-Verlag. Lecture Notes in Artificial Intelligence No. 1076.

Borst,P.,Akkermans,H. and Top,J., Engineering Ontologies, International Journal of Human-Computer Studies, 46:365-406, 1997

Gómez-Pérez, A.; Fernandez, M.; De Vicente, A. Towards a Method to Conceptualize Domain Ontologies. Workshop on Ontological Engineering. ECAI'96. 1996. Pags. 41-51.

Gruber, T. (1995). Toward principles for the design of ontologies used for knowledge sharing. International Journal of Human-Computer Studies, 43:907-928.

Bibliography (iv)

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Noy, Natalya F. and McGuinness, Deborah L. . Ontology Development 101: A Guide to Creating Your First Ontology. Stanford Knowledge Systems Laboratory Technical Report KSL-01-05 and Stanford Medical Informatics Technical Report SMI-2001-0880, March 2001. Online:http://protege.stanford.edu/publications/ ontology_development/ontology101.html

3.1        Ontology editors

Duineveld, A.J., Stoter, R., Weiden, M.R., Kenepa, B. and Benjamins, V.R. (2000). WonderTools? A comparative study of ontological engineering tools. International Journal of Human-Computer Studies 52(6): 1111-1133.

Farquhar,A. Fikes,R. and Rice, J. The Ontolingua Server: a Tool for Collaborative Ontology Construction; Intl. Journal of Human-Computer Studies 46, 1997.

Bibliography (v)

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 4          Learning and acquisition of ontologies

Frank,Gleb; Farquhar, Adam and Fikes, Richard Building a Large Knowledge Base from a Structured Source Intelligent Systems & their applications Vol. 14, No. 1, January/February 1999

 5          Ontologies and knowledge-based systems

van Heijst, G.  (1995). The Role of Ontologies in Knowledge Engineering. PhD thesis, University of Amsterdam.

5.1.1        Ontologies and CBR systems

Díaz-Agudo, B. & González-Calero, P.A. (2000). An architecture for knowledge intensive CBR systems. Proceedings of the Fifth European Workshop on Case-Based Reasoning (pp. 37-48). Munich: Springer.

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