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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 software agents and web services exchanging meaningful and unambiguous messages. A prerequisite for this kind of interoperability is the usage of an ontology. Currently, not many ontology engineering methodologies exist. This paper describes some basic issues to be taken into account when using the ORM methodology for ontology engineering from the DOGMA ontology framework point of view.

Keywords

Conceptual Schema Derivation Rule Ontology Engineering Ontology Base Local Ontology 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Aberer, K., Catarci, T., Cudré-Mauroux, P., et al.: Emergent Semantics Systems. In: Bouzeghoub, M., Goble, C.A., Kashyap, V., Spaccapietra, S. (eds.) ICSNW 2004. LNCS, vol. 3226, pp. 14–44. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  2. 2.
    Bouquet, P., Giunchiglia, F., van Harmelen, F., Serafini, L., Stuckenschmidt, H.: Contextualizing Ontologies. Journal of Web Semantics 26, 1–19 (2004)Google Scholar
  3. 3.
    Calvanese, C., De Giacomo, G., Lenzerini, M.: A Framework for Ontology Integration. In: Proceedings of the 2001 International Semantic Web Working Symposium (2001)Google Scholar
  4. 4.
    Cunningham, H., Ding, Y., Kiryakov, A.: In: Proceedings of the ISWC 2003 Workshop on Human Language Technology for the Semantic Web and Web Services (2004)Google Scholar
  5. 5.
    De Bo, J., Spyns, P.: Refining the notion of context within the DOGMA framework. Technical Report 12, STAR Lab, Brussel (2003)Google Scholar
  6. 6.
    De Bo, J., Spyns, P., Meersman, R.: Creating a “DOGMAtic” multilingual ontology infrastructure to support a semantic portal. In: Meersman, R., Tari, Z. (eds.) OTM-WS 2003. LNCS, vol. 2889, pp. 253–266. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  7. 7.
    De Leenheer, P., de Moor, A.: Context-driven Disambiguation in Ontology Elicitation. In: Shvaiko, P., Euzenat, J. (eds.) Context and Ontologies: Theory, Practice and Applications: AAAI 2005 Workshop, AAAI Technical Report WS-05-01, pp. 17–24. AAAI Press, Menlo Park (2005)Google Scholar
  8. 8.
    Farrugia, J.: Model-Theoretic Semantics for the Web. In: Proceedings of the 12th International Conference on the WWW, pp. 29–38. ACM, New York (2003)Google Scholar
  9. 9.
    Genesereth, M., Nilsson, N.: Logical Foundations of Artificial Intelligence. Morgan Kaufmann, San Francisco (1987)zbMATHGoogle Scholar
  10. 10.
    Giunchiglia, F., Yatskevich, M., Giunchiglia, E.: Efficient Semantic Matching. In: Gómez-Pérez, A., Euzenat, J. (eds.) ESWC 2005. LNCS, vol. 3532, pp. 272–289. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  11. 11.
    Guarino, N.: Formal Ontologies and Information Systems. In: Guarino, N. (ed.) Proc. of FOIS 1998, pp. 3–15. IOS Press, Amsterdam (1998)Google Scholar
  12. 12.
    Halpin, T.: Information Modeling and Relational Databases: from conceptual analysis to logical design. Morgan-Kaufmann, San Francisco (2001)Google Scholar
  13. 13.
    Jarrar, M., Meersman, R.: Formal Ontology Engineering in the DOGMA Approach. In: Meersman, R., Tari, Z., et al. (eds.) CoopIS 2002, DOA 2002, and ODBASE 2002. LNCS, vol. 2519, pp. 1238–1254. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  14. 14.
    Kerremans, K., Temmerman, R.: Towards Multilingual, Termontological Support in Ontology Engineering. In: Proceedings Workshop on Terminology, Ontology and Knowledge représentation, Lyon, France (January 22-23 2004)Google Scholar
  15. 15.
    Magnini, B., Serafini, L., Speranza, M.: Using NLP Techniques for Meaning Negotiation. In: Proceedings of the Ottavo Convegno dell’Associazione Italiana per l’Intelligenza Artificiale (2002), http://www-dii.ing.unisi.it/aiia2002/paper/NLP/serafini-aiia02.pdf
  16. 16.
    Martinet, A.: Economie des changements phonétiques, Berne Francke (1955)Google Scholar
  17. 17.
    Meersman, R.: The Use of Lexicons and Other Computer-Linguistic Tools. In: Zhang, Y., Rusinkiewicz, M., Kambayashi, Y. (eds.) Semantics, Design and Cooperation of Database Systems; The International Symposium on Cooperative Database Systems for Advanced Applications (CODAS 1999), pp. 1–14. Springer, Heidelberg (1999)Google Scholar
  18. 18.
    Meersman, R.: Ontologies and Databases: More than a Fleeting Resemblance. In: d’Atri, A., Missikoff, M. (eds.) OES/SEO 2001 Rome Workshop. Luiss Publications (2001)Google Scholar
  19. 19.
    Meersman, R.: Semantic Web and Ontologies: Playtime or Business at the Last Frontier in Computing? In: NSF-EU Workshop on Database and Information Systems Research for Semantic Web and Enterprises, pp. 61–67 (2002)Google Scholar
  20. 20.
    Morris, C.: Writings of the General Theory of Signs. The Hague, Mouton (1971)Google Scholar
  21. 21.
    Métais, E.: Enhancing information systems with natural language processing techniques. Data and Knowledge Engineering 41, 247–272 (2002)zbMATHCrossRefGoogle Scholar
  22. 22.
    Navigli, R., Velardi, P.: Learning Domain Ontologies from Document Warehouses and Dedicated Web Sites. Computational Linguistics 2, 151–179 (2004)CrossRefGoogle Scholar
  23. 23.
    Noy, N.: Semantic Integration: A Survey of Ontology-Based Approaches. SIGMOD Record Special Issue 33 (2004) [in print] Google Scholar
  24. 24.
    Reinberger, M.-L., Spyns, P.: Unsupervised Text Mining for the learning of DOGMA-inspired ontologies. In: Buitelaar, P., Cimiano, P., Magnini, B. (eds.) Ontology Learning from Text: Methods, Applications and Evaluation, pp. 29–43. IOS Press, Amsterdam (2005)Google Scholar
  25. 25.
    Sowa, J.F.: Knowledge Representation: Logical, Philosophical, and Computational Foundations. Brooks Cole Publishing Co., Pacific Grove (2000)Google Scholar
  26. 26.
    Spyns, P., Meersman, R., Jarrar, M.: Data modelling versus Ontology engineering. In: Sheth, A., Meersman, R. (eds.) SIGMOD Record Special Issue, 31th edn., pp. 12–17 (2002)Google Scholar
  27. 27.
    Spyns, P., Meersman, R.: From knowledge to Interaction: from the Semantic to the Pragmatic Web. Technical report 05, STAR Lab, Brussel (2003)Google Scholar
  28. 28.
    Spyns, P., De Bo, J.: Ontologies: a revamped cross-disciplinary buzzword or a truly promising interdisciplinary research topic? Linguistica Antverpiensia NS 3, 279–292 (2004)Google Scholar
  29. 29.
    Spyns, P.: Adapting the Object Role Modelling method for Ontology Modelling. In: Hacid, M.-S., Murray, N.V., Raś, Z.W., Tsumoto, S. (eds.) ISMIS 2005. LNCS (LNAI), vol. 3488, pp. 276–284. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  30. 30.
    Spyns, P., Reinberger, M.-L.: Evaluating ontology triples generated automatically from texts. In: Gómez-Pérez, A., Euzenat, J. (eds.) ESWC 2005. LNCS, vol. 3532, pp. 563–577. Springer, Heidelberg (2005)Google Scholar
  31. 31.
    Stuckenschmidt, H., van Harmelen, F.: Information Sharing on the Web. Springer, Heidelberg (2005)zbMATHGoogle Scholar
  32. 32.
    van de Meersman, R. (ed.): Linguistic Instruments in Knowledge Engineering. North Holland, Amsterdam (1992)zbMATHGoogle Scholar
  33. 33.
    Verheyden, P., De Bo, J., Meersman, R.: Semantically Unlocking Database Content through Ontology-based Mediation. In: Bussler, C.J., Tannen, V., Fundulaki, I. (eds.) SWDB 2004. LNCS, vol. 3372, pp. 109–126. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  34. 34.
    Zhao, G., Kingston, J., Kerremans, K., Coppens, F., Verlinden, R., Temmerman, R., Meersman, R.: Engineering an Ontology of Financial Securities Fraud. In: Meersman, R., Tari, Z., Corsaro, A. (eds.) OTM-WS 2004. LNCS, vol. 3292, pp. 605–620. Springer, Heidelberg (2004)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Peter Spyns
    • 1
  1. 1.STAR LabVrije Universiteit BrusselBrusselBelgium

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