On the Importance of Truly Ontological Distinctions for Ontology Representation Languages: An Industrial Case Study in the Domain of Oil and Gas

  • Giancarlo Guizzardi
  • Mauro Lopes
  • Fernanda Baião
  • Ricardo Falbo
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 29)


Ontologies are commonly used in computer science either as a reference model to support semantic interoperability, or as an artifact that should be efficiently represented to support tractable automated reasoning. This duality poses a tradeoff between expressivity and computational tractability that should be addressed in different phases of an ontology engineering process. The inadequate choice of a modeling language, disregarding the goal of each ontology engineering phase, can lead to serious problems in the deployment of the resulting model. This article discusses these issues by making use of an industrial case study in the domain of Oil and Gas. We make explicit the differences between two different representations in this domain, and highlight a number of concepts and ideas that were implicit in an original OWL-DL model and that became explicit by applying the methodological directives underlying an ontologically well-founded modeling language.


Ontology Ontology Languages Conceptual modelling Oil and Gas domain 


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  1. 1.
    Mealy, G.H.: Another Look at Data. In: Proceedings of the Fall Joint Computer Conference, Anaheim, California, November 14–16. AFIPS Conference Proceedings, vol. 31, pp. 525–534. Thompson Books, Academic Press, Washington, London (1967)Google Scholar
  2. 2.
    Burek, P., et al.: A top-level ontology of functions and its application in the Open Biomedical Ontologies. Bioinformatics 22(14), e66–e73 (2006)Google Scholar
  3. 3.
    Fielding, J., et al.: Ontological Theory for Ontology Engineering. In: International Conf. on the Principles of Knowledge Representation and Reasoning (KR 2004), 9th, Whistler, Canada, Proceedings (2004)Google Scholar
  4. 4.
    Guarino, N.: Formal Ontology and Information Systems. In: 1st International Conference on Formal Ontologies in Information Systems, Trento, Italy, June 1998, pp. 3–15 (1998)Google Scholar
  5. 5.
    Guizzardi, G.: Ontological Foundations for Structural Conceptual Models, Telematica Instituut Fundamental Research Series No. 15. Universal Press, The Netherlands (2005)Google Scholar
  6. 6.
    Levesque, H., Brachman, R.: Expressiveness and Tractability in Knowledge Representation and Reasoning. Computational Intelligence 3(1), 78–93 (1987)CrossRefGoogle Scholar
  7. 7.
    Guizzardi, G., Halpin, T.: Ontological Foundations for Conceptual Modeling. Applied Ontology 3(1-2), 91–110 (2008)Google Scholar
  8. 8.
    Chum, F.: Use Case: Ontology-Driven Information Integration and Delivery - A Survey of Semantic Web Technology in the Oil and Gas Industry, W3C (April 2007), (accessed in Decemeber 2007)
  9. 9.
    Cappelli, C., Baião, F., Santoro, F., Iendrike, H., Lopes, M., Nunes, V.T.: An Approach for Constructing Domain Ontologies from Business Process Models. In: II Workshop on Ontologies and Metamodeling in Software and Data Engineering (WOMSDE) (2007) (in Portuguese)Google Scholar
  10. 10.
    Baião, F., Santoro, F., Iendrike, H., Cappelli, C., Lopes, M., Nunes, V.T., Dumont, A.P.: Towards a Data Integration Approach based on Business Process Models and Domain Ontologies. In: 10th International Conference on Enterprise Information Systems (ICEIS 2008), Barcelona, pp. 338–342 (2008)Google Scholar
  11. 11.
    Thomas, J.E.: Fundamentals of Petroleum Engineering. Rio de Janeiro, Interciência (2001) (in Portuguese)Google Scholar
  12. 12.
    Guizzardi, G., Wagner, G.: What’s in a Relationship: An Ontological Analysis. In: Li, Q., Spaccapietra, S., Yu, E., Olivé, A. (eds.) ER 2008. LNCS, vol. 5231. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  13. 13.
    Guizzardi, G., Wagner, G., Guarino, N., van Sinderen, M.: An Ontologically Well-Founded Profile for UML Conceptual Models. In: Persson, A., Stirna, J. (eds.) CAiSE 2004. LNCS, vol. 3084, pp. 112–126. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  14. 14.
    Smith, B., et al.: Relations in biomedical ontologies. Genome Biology 6(5) (2005)Google Scholar
  15. 15.
    Artale, A., Keet, M.: Essential and Mandatory Part-Whole Relations in Conceptual Data Models. In: 21st International Workshop on Description Logics, Dresden (2008)Google Scholar
  16. 16.
    Keet, M., Artale, A.: Representing and Reasoning over a Taxonomy of Part-Whole Relations. In: Guizzardi, G., Halpin, T. (eds.) Special Issue on Ontological Foundations for Conceptual Modeling, Applied Ontology, vol. 3(1-2), pp. 91–110 (2008) ISSN 1570-5838Google Scholar
  17. 17.
    Thomasson, A.L.: Fiction and Metaphysics. Cambridge University Press, Cambridge (1999)Google Scholar
  18. 18.
    das Graças, A.: Extending a Model-Based Tool for Ontologically Well-Founded Conceptual Modeling with Rule Visualization Support. In: Computer Engineering Monograph, Ontology and Conceptual Modeling Research Group (NEMO), Federal University of Espirito Santo, Brazil (2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Giancarlo Guizzardi
    • 1
  • Mauro Lopes
    • 2
    • 3
  • Fernanda Baião
    • 2
    • 3
  • Ricardo Falbo
    • 1
  1. 1.Ontology and Conceptual Modeling Research Group (NEMO), Computer Science DepartmentFederal University of Espírito SantoEspírito SantoBrazil
  2. 2.NP2Tec – Research and Practice Group in Information TechnologyFederal University of the State of Rio de Janeiro (UNIRIO)Rio de JaneiroBrazil
  3. 3.Department of Applied InformaticsFederal University of the State of Rio de Janeiro (UNIRIO)Rio de JaneiroBrazil

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