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Adapting the Object Role Modelling Method for Ontology Modelling

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Foundations of Intelligent Systems (ISMIS 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3488))

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Abstract

A recent evolution in the areas of artificial intelligence, database semantics and information systems is the advent of the Semantic Web that requires that software agents and web services exchange meaningful and unambiguous messages. A prerequisite for this kind of interoperability is the usage of an ontology. Currently, not many step-wise ontology engineering methodologies exist. This paper describes an outline of such a methodology based on ORM, a DB conceptual modelling method. The new methodology is to be situated in the ontology engineering framework of DOGMA, developed at VUB STAR Lab. One of the distinctive characteristics is that language related issues are taken into account from the on-set.

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Author information

Authors and Affiliations

  1. STAR Lab, Vrije Universiteit Brussel, Pleinlaan, 2, Gebouw G-10, B-1050, Brussel, Belgium

    Peter Spyns

Authors
  1. Peter Spyns
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Editor information

Editors and Affiliations

  1. LIRIS - UFR d’Informatique, Université Claude Bernard Lyon 1, 43, boulevard du 11 novembre 1918, 69622, Villeurbanne, France

    Mohand-Said Hacid

  2. Department of Computer Science, State University of New York, 12222, Albany, NY, USA

    Neil V. Murray

  3. Department of Computer Science, University of North Carolina, 28223, Charlotte, NC, USA

    Zbigniew W. Raś

  4. Shimane University, 89-1 Enya-cho Izumo, 6938501, Shimane, Japan

    Shusaku Tsumoto

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Spyns, P. (2005). Adapting the Object Role Modelling Method for Ontology Modelling. In: Hacid, MS., Murray, N.V., Raś, Z.W., Tsumoto, S. (eds) Foundations of Intelligent Systems. ISMIS 2005. Lecture Notes in Computer Science(), vol 3488. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11425274_29

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  • DOI: https://doi.org/10.1007/11425274_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25878-0

  • Online ISBN: 978-3-540-31949-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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