A Review of Ontology Research & Development

Ming Mao

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Ontology Definition Why ontology?

Ontology Applications

Typical Ontology look

Kinds of Ontology

Important Ontologies

Ontology Languages

Ontology Development

Ontology Projects Ontology Generation, Mapping & Evolving

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What is Ontology?

No Agreement on the definition :• « The word "ontology" seems to generate a lot of

controversy in discussion about AI.»T. R. Gruber. ’A translation approach to portable

ontologies’. Knowledge Acquisition, 5(2):199-220, 1993

• « Although “ontology” is currently a fashionable term, no agreement exists on the exact meaning of the term.»‘Framework and Formalism for Expressing Ontologies’KACTUS Esprit Project 8145

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Go back to etymology

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Computer Science View

• Ontology is a formal explicit specification of a shared conceptualization. It provides a shared and common understanding of a domain that can be communicated across people and application systems (Gruber, 1993).

• It’s meta data that explicitly represent semantics of data in machine processable way (Ding, 2001).

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Why do we need Ontology?

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Ontology Applications

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What does an Ontology look like?

• A typical ontology has a taxonomy defining the classes and their relations and a set of inference rules powering reasoning functions (Berners-Lee, Hendler and Lassila, 2001)

• In Greek, taxonomy means…• “taxon” = class• “onoma” = name

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Ontology example• Class hierarchy (12 classes defined):• Vehicle• Vehicle-For-Sale• Wheeled-Vehicle• Automobile• Ford• Ford-Mustang• Taurus• Lotus• Bus• Requires-Smog-Check• Vehicle-Model-Type• Wheel• 2 relations defined: Has-Wheel , Wheel-Of• 3 functions defined: Blue-Book-Value , Mileage , Model-Year• 1 individual defined: My-Very-Own-Lotus• 6 unnamed axioms defined.• 1 named axiom defined: Cars-After-1964-Require-Smog-Checks-Axiom

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Ontology example (cont.)Class Automobile

• Defined in Ontology: Vehicles• Source code: vehicles.lisp

Arity: 1Maximum-Cardinality: 1Value-Type: Integer

Documentation: Any old sort of car.Value-Type: String

Instance-Of: Class, Primitive, Relation, Set, ThingValue-Type: Class

Subclass-Of: Wheeled-Vehicle, Thing, VehicleSuperclass-Of: Ford, Ford-Mustang, Lotus, TaurusType-Of: My-Very-Own-Lotus

Template Slots:Has-Wheel: Minimum-Cardinality: 1

Value-Type: WheelModel-Year: Maximum-Cardinality: 1

Minimum-Cardinality: 0Axioms for Automobile:Implication Axioms mentioning Automobile:(=> (And (Automobile ?Automobile)

(> (Model-Year ?Automobile) 1964))(Requires-Smog-Check ?Automobile))

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Kinds of Ontology• Uschold & Gruninger (1996) classified the ontology from

three demensions:1.formality

• highly informal : expressed in natural language• semi-informal : expressed in a restricted and structured form of natural

language in order to reduce ambiguity, e.g. the text version of Enterprise Ontology (Fraser, 1995)

• semi-formal : expressed in an artificial formally defined language, e.g. Ontolingua version of the Enterprise Ontology

• Rigorously formal : precisely defined terms with formal semantics, e.g TOVE.

2.purpose• communication, inter-operability, systems engineering benefits,

reusability, knowledge acquisition, reliability, specification etc.

3.subject matter• domain ontology, task or problem solving ontology, representation

ontology or meta-ontology

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Important Ontologies

• Cyc (see fig.)• TOVE• Enterprise

Ontology• KRSL Plan

Ontology• WfMC• STEP• EL Ontology• SENSUS• WordNet

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Ontology languages• A lot of potential languages for ontology :

From natural languages for highly informal ontologies To formal languages for rigorously formal ontologies– KIF– OCML– LOOM– SHOE– RDF– RDFS– OIL– DAML…

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Ontology Development

A general overview of ontology generation, mapping and evolving.

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Ontology Generation

Methodology proposed by Uschold & Gruninger (1996)

1. Identify Purpose and Scope

2. Building the Ontology• ontology capture

• ontology coding

• integrating existing ontologies

3. Evaluation

4. Documentation

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The OK (Ontological Knowledge) Model

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Ontology Mapping

• Effective use or reuse of knowledge is essential.– A lot of different ontologies exist.– Simply combining knowledge from distinct domains

creates several problems.

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Ontology Mapping (2)

Source Target

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Ontology mapping approaches

• One-to-one approach, where for each ontology a set of translating functions is provided to allow the communication with the other ontologies without an intermediate ontology (Mena etc. 1999).

• Single-shared ontology (Visser & Cui, 1998).• Ontology clustering where resources are

clustered together on the basis of similarities. Additionally, ontology clusters can be organized in a hierarchical fashion (Visser & Tamma, 1999).

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Ontology Evolving (Maintenance)

• Fowler (1999) mentioned the need to maintain different versions of the same ontology is it is being scaled up.

• Ontology evolving requires the clarity of structure of ontologies so as to guarantee the accurate gauge of the maintenance.

• Some researches on semi-automatic or automatic ontology evolving have been carried out, but almost all are at a early stage and require manual intervention.

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Ontology Projects• InfoSleuth (Fowler et al, 1999)• Stanford’s ontology algebra (Mitra, Wiederhold, Kersten, 2000),

ONION (Ontology compositION), SKAT (Semantic Knowledge Articulation Tools)

• AIFB (Stumme, Studer & Sure, 2000)• ECAI2000 (Faatz, Kamps & Steinmetz, 2000)• ISI OntoMorph (Chalupsky, 2000)• KRAFT (Visser et al. 1999)• OntoSeek (Guarino, Masolo & Vetere, 1999)• OntoKnowledge (www.ontoknowledge.org)• OntoWeb (www.ontoweb.org)• OntoBroker (ontobroker.aifb.uni-karlsruhe.de)• Cyc (www.cyc.com)• TOVE (www.eil.utoronto.ca/tove/ontoTOC.html)• Enterprise (www.aia.ed.ac.uk/~enterprise/enterprise)• Others…

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References– M. Klein, Y. Ding, D.Fensel and B. Omelayenko (2002). Ontology techniques and

methodology: Ontology Library Systems (book chatper). In J.Davis, D.Fensel, F.van Hamelen: Towards the Semantic Web: Ontology-Driven Knowledge Management, Wiley.

– D. Fensel et al. On-To-Knowledge in a Nutshell. To appear: Special Issue of IEEE Computer on Web Intelligence (WI)

– D. Fensel, C. Bussler, Y. Ding, V. Kartseva, M. Klein, M. Korotkiy, B. Omelayenko, and R. Siebes: Semantic Web Application Areas. In Proceedings of the 7th International Workshop on Applications of Natural Language to Information Systems, Stockholm - Sweden, June 27-28, 2002.

– Ying Ding & Schubert Foo (2002). Ontology Research and Development: Part 1 – A Review of Ontology Generation. Journal of Information Science 28(2).

– Ying Ding & Schubert Foo (2002): Ontology Research and Development: Part 2 – A Review of Ontology mapping and evolving. Journal of Information Science28(4).

– Y.Kalfoglou, M.Schorlemmer. "Ontology mapping: the state of the art"The Knowledge Engineering Review 18(1):1--31, January 2003

– Christophe Roche « Ontology : a roadmap from theory to applications» – ICEIS 2003 – 23-26 April 2003