New Generation Computing, 22(2004)193-220
Ohmsha, Ltd. and Springer-Verlag

Tutorial on Ontological Engineering
Part 3: Advanced Course of Ontological Engineering

Riichiro MIZOGUCHI
The institute of Scientific and Industrial Research, Osaka University
8-1 Mihogaoka, Ibaraki, Osaka 567-0047, Japan

miz@ei.sanken.osaka-u.ac.jp

Received 18 August 2003

Abstract

This article deals with advanced topics of ontological engineering to convince readers ontology is more than a rule base of terminological problems and is worth to consider a promising methodology in the next generation knowledge processing research. Needless to say, ontology in AI is tightly connected to ontology in philosophy. The first topic here is on philosophical issues which are very important to properly understand what an ontology is. After defining class, instance and is-a relation, we point out some typical inappropriate uses of is-a relation in existing ontologies and analyze the reasons why. Other topics are basic ontological distinction, part-of relation, and so on. As an advanced example of ontology, an ontology of representation is extensively discussed. To conclude this tutorial, a success story of ontological engineering is presented. It is concerned with a new kind of application of ontology, that is, knowledge systematization. An ontology-based framework for functional knowledge sharing has been deployed into a company for two years and has been a great success. Finally, future of ontological engineering is discussed followed by concluding remarks.

1. Fundamental Issues
1.1 Background
1.2 Class Instance and is-a Relation
1.3 Ontological Distinction
1.4 Role Attribute
1.5 Instance vs. Occurrence
1.6 Kinds of a Part-of Relation
1.7 Data, Information and Knowledge
2. Ontology of Representation
2.1 Two Principles
2.2 A Conceptual Model of Representation
2.3 An Ontology of Representation
3. Guidelines of Ontology Building
4. A Success Story of Ontology Research
4.1 Systematization of Functional Knowledge
4.2 Deployment into the Production Division of an Industry
5. Future of Ontological Engineering
6. Concluding Remarks

Keywords:Bioinformatics, Grid, Adaptive Scheduling, Adaptive Execution..

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