Towards Automated Reasoning on ORM Schemes

Mapping ORM into the \(\mathcal{DLR}_{idf}\) Description Logic
  • Mustafa Jarrar
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4801)


The goal of this article is to formalize Object Role Modeling (ORM) using the \(\mathcal{DLR}\) description logic. This would enable automated reasoning on the formal properties of ORM diagrams, such as detecting constraint contradictions and implications. In addition, the expressive, methodological, and graphical capabilities of ORM make it a good candidate for use as a graphical notation for most description logic languages. In this way, industrial experts who are not IT savvy will still be able to build and view axiomatized theories (such as ontologies, business rules, etc.) without needing to know the logic or reasoning foundations underpinning them. Our formalization in this paper is structured as 29 formalization rules, that map all ORM primitives and constraints into \(\mathcal{DLR}\), and 2 exceptions of complex cases. To this end, we illustrate the implementation of our formalization as an extension to DogmaModeler, which automatically maps ORM into DIG and uses Racer as a background reasoning engine to reason about ORM diagrams.


Description Logic Object Type Uniqueness Constraint Automate Reasoning Business Rule 
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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  1. 1.
    Baader, F., Calvanese, D., McGuinness, D., Patel-Schneider, D.N.P.: The Description Logic Handbook: Theory, Implementation and Applications. Cambridge University Press, Cambridge (2003)zbMATHGoogle Scholar
  2. 2.
    Berardi, D., Calvanese, D., Giacomo, G.D.: Reasoning on uml class diagrams. Artificial Intelligence 168(1), 70–118 (2005)MathSciNetCrossRefzbMATHGoogle Scholar
  3. 3.
    Calvanese, D., De Giacomo, G., Lembo, D., Lenzerini, M., Rosati, R.: Data complexity of query answering in description logics. In: Doherty, P., Mylopoulos, J., Welty, C. (eds.) Proceedings of the 10th International Conference on Principles of KnowledgeRepresentation and Reasoning (KR2006), Menlo Park, California, pp. 178–218. AAAI Press, Stanford, California, USA (2006)Google Scholar
  4. 4.
    Calvanese, D., De Giacomo, G., Lenzerini, M.: Identification constraints and functional dependencies in description logics. In: Proceedings of the 17th Int. Joint Conf. on Artificial Intelligence (IJCAI2001), pp. 155–160 (2001)Google Scholar
  5. 5.
    de Troyer, O.: A formalization of the binary object-role model based on logic. Data and Knowledge Engineering 19, 1–37 (1996)CrossRefzbMATHGoogle Scholar
  6. 6.
    Franconi, E., Ng, G.: The tool for intelligent conceptual modelling. In: 7th Int. WS on Knowledge Representation meets Databases(KRDB’00), Springer, Heidelberg (2000)Google Scholar
  7. 7.
    Halpin, T.: A logical analysis of information systems: static aspects of the data-oriented perspective. PhD thesis, University of Queensland, Brisbane, Australia (1989)Google Scholar
  8. 8.
    Halpin, T.: Information Modeling and Relational Databases. Morgan Kaufmann, San Francisco (2001)Google Scholar
  9. 9.
    Halpin, T.: Join constraints. In: Halpin, T., Siau, K., Krogstie, J. (eds.) Proceedings of the 7th International IFIP WG8.1 Workshop on Evaluation ofModeling Methods in Systems Analysis and Design ( EMMSAD’02) (June 2002)Google Scholar
  10. 10.
    Halpin, T.: Objectification. In: Pastor, Ó., Falcão e Cunha, J. (eds.) CAiSE 2005. LNCS, vol. 3520, Springer, Heidelberg (2005)Google Scholar
  11. 11.
    Halpin, T., Curland, M.: Automated verbalization for orm 2. In: Meersman, R., Tari, Z. (eds.) OTM 2006, Springer, Heidelberg (2006)Google Scholar
  12. 12.
    Halpin, T., Proper, E.: Subtyping and polymorphism in object-role modelling. Data and Knowledge Engineering 15(3), 251–281 (1995)CrossRefzbMATHGoogle Scholar
  13. 13.
    Horrocks, I., Kutz, O., Sattler, U.: The even more irresistible \(\mathcal{SROIQ}\). In: Proceeding of the 10th International Conference on Principles of Knowledge Representation and Reasoning (KR 2006) (2006)Google Scholar
  14. 14.
    Horrocks, I., Sattler, U., Tobies, S.: Practical reasoning for expressive description logics. In: Ganzinger, H., McAllester, D., Voronkov, A. (eds.) LPAR 1999. LNCS, vol. 1705, pp. 161–180. Springer, Heidelberg (1999)CrossRefGoogle Scholar
  15. 15.
    Jarrar, M.: Towards Methodological Principles for Ontology Engineering. PhD thesis, Vrije Universiteit Brussel, Brussels, Belgium (May 2005)Google Scholar
  16. 16.
    Jarrar, M.: Towards the notion of gloss, and the adoption of linguistic resources informal ontology engineering. In: Proceedings of the 15th international conference on World Wide Web (WWW2006), May 2006, pp. 497–503. ACM Press, New York (2006)Google Scholar
  17. 17.
    Jarrar, M., Demey, J., Meersman, R.: On using conceptual data modeling for ontology engineering. Journal on Data Semantics (Special issue on Best papers from the ER/ODBASE/COOPIS2002 Conferences) 2800, 185–207 (2003)Google Scholar
  18. 18.
    Jarrar, M., Eldammagh, M.: Reasoning on orm using racer. Technical report, Vrije Universiteit Brussel, Brussels, Belgium (August 2006)Google Scholar
  19. 19.
    Jarrar, M., Heymans, S.: Unsatisfiability reasoning in orm conceptual schemes. In: Illarramendi, A., Srivastava, D. (eds.) Proceeeding of International Conference on Semantics of a Networked World, Munich, Germany, March 2006, vol. LNCS, Springer, Heidelberg (2006)Google Scholar
  20. 20.
    Jarrar, M., Heymans, S.: On pattern-based ontological reasoning. International Journal on Artificial Intelligence Tools  (2007)Google Scholar
  21. 21.
    Jarrar, M., Keet, M., Dongilli, P.: Multilingual verbalization of orm conceptual models and axiomatized ontologies. Technical report, Vrije Universiteit Brussel, Brussels, Belgium (February 2006)Google Scholar
  22. 22.
    Jarrar, M., Meersman, R.: Formal ontology engineering in the dogma approach. In: Meersman, R., Tari, Z. (eds.) OTM 2002. LNCS, vol. 2519, pp. 1238–1254. Springer, Heidelberg (2002)Google Scholar
  23. 23.
    Jarrar, M., Verlinden, R., Meersman, R.: Ontology-based customer complaint management. In: Meersman, R., Tari, Z. (eds.) OTM 2003. LNCS, vol. 2889, pp. 594–606. Springer, Heidelberg (2003)Google Scholar
  24. 24.
    Cranefield, P.S., Hart, L., Dutra, M., Baclawski, K., Kokar, M., Smith, J.: Uml for ontology development. Knowl. Eng. Rev. 17(1), 61–64 (2002)Google Scholar
  25. 25.
    Simmonds, J., Bastarrica, M.C.: A tool for automatic uml model consistency checking. In: Proceedings of the 20th IEEE/ACM international Conference on Automated softwareengineering, pp. 431–432. ACM Press, New York (2005)CrossRefGoogle Scholar
  26. 26.
    van Bommel, P., ter Hofstede, A.H.M., van der Weide, T.P.: Semantics and verification of object-role models. Information Systems 16(5), 471–495 (1991)CrossRefGoogle Scholar
  27. 27.
    van der Weide, T.P., ter Hofstede, A.H.M., van Bommel, P.: Uniquest: determining the semantics of complex uniqueness constraints. Comput. J. 35(2), 148–156 (1992)CrossRefzbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Mustafa Jarrar
    • 1
  1. 1.STARLab, Vrije Universiteit Brussels, Belgium, Department of Computer Science, University of CyprusBelgium

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