Ontology, Knowledge Management, Knowledge Engineering and the ACM Classification Scheme

  • John Kingston

Abstract

The purpose of this paper is to test the theory of multiple perspectives being necessary for completeness in ontologies by applying it to the task of placing “knowledge management” and “knowledge engineering” within the ACM classification scheme. The thesis of this paper is that a multi-perspective analysis of the ACM classification scheme, along with a published extension for AI subjects, should demonstrate some of the principles on which the classification is based, and therefore help in deciding where knowledge management and knowledge engineering (and knowledge acquisition) should appear in the classification. Some implications for ontology building are discussed.

Keywords

Diesel Petrol 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Kingston J.K.C., Multi-Perspective Modelling: A Framework for Re-usable Knowledge. Forthcoming.Google Scholar
  2. 2.
    Kingston J.K.C. and Macintosh A.L., Knowledge Management through Multi-Perspective Modelling: Representing and Distributing Organizational Memory. Proceedings of ES ’99, Cambridge, 1999.Google Scholar
  3. 3.
    Waltz D.L., Scientific Datalink’s Artificial Intelligence Classification Scheme. The AI Magazine, Spring 1985, pp. 58 – 63.Google Scholar
  4. 4.
    N. Coulter et al, Report of the CCS Update Committee.http://www.acm.orp/class/1998/ccsup.pdf, 1998.Google Scholar
  5. 5.
    Kingston J.K.C., Developing a Reference Ontology for Scientific Knowledge Management. Proceedings of AAAI-02 Workshop on Ontologies and the Semantic Web, AAAI-02, Edmonton, Canada, 29 July 2002.Google Scholar
  6. 6.
    Wilkins J., Natural and Artificial Classification,http://www.users.bigpond:com/ thewilkins/papers/artifnat.html, 1997.Google Scholar
  7. 7.
    Rosch E., Natural categories. Cognitive Psychology 4: 328 – 350, 1973.CrossRefGoogle Scholar
  8. 8.
    Artale A., Franconi E., Guarino N. & Pazzi, L. Part-Whole Relations in Object-Centered Systems: an Overview. Data and Knowledge Engineering, 20 (3): 347 – 383. 1996.MATHCrossRefGoogle Scholar
  9. 9.
    Schreiber A.Th., Akkermans J.M. et al, Engineering and Managing Knowledge: The CommonKADS Methodology. University of Amsterdam, Amsterdam, 1998.Google Scholar
  10. 10.
    Binney D.,The knowledge management spectrum - understanding the KM landscape. Journal of Knowledge Management, 2001, 5(1):33–42.CrossRefGoogle Scholar
  11. 11.
    Breuker, J.A., Model Driven Knowledge Acquisition. ESPRIT project 1098 KADS, Deliverable, Al, 1987.Google Scholar
  12. 12.
    Breuker J.A., Problems in Indexing Problem-Solving Methods, Proceedings of the Workshop on Problem Solving Methods, IJCAI-97, Nagoya, Japan, August 1997.Google Scholar

Copyright information

© Springer-Verlag London Limited 2003

Authors and Affiliations

  • John Kingston
    • 1
  1. 1.AIAI, School Of InformaticsUniversity of EdinburghEdinburghScotland

Personalised recommendations