Temporal Reasoning for Supporting Temporal Queries in OWL 2.0

  • Sotiris Batsakis
  • Kostas Stravoskoufos
  • Euripides G. M. Petrakis
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6881)


We propose an approach for reasoning and querying over temporal information in OWL ontologies. Representing both qualitative temporal (i.e., information whose temporal extents are unknown such as “before”, “after” for temporal relations) in addition to quantitative information (i.e., where temporal information is defined precisely e.g., using dates) is a distinctive feature of the proposed ontology. Qualitative representations are very common in natural language expressions such as in free text or speech and can be proven to be valuable in the Semantic Web. Reasoning rules applying over temporal relations, infer implied relations, detect inconsistencies and retain soundness, completeness and tractability over the supported sets of relations using path consistency. Temporal representations are defined on time instants rather than on intervals (as it is typical in the literature), resulting into simpler yet equivalent representations. A SPARQL-based temporal query language capable of exploiting the characteristics of the underlying representation is also implemented and discussed.


Temporal Relation Description Logic SPARQL Query Temporal Reasoning Concrete Domain 
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.
    Batsakis, S., Petrakis, E.G.M.: SOWL: Spatio-temporal Representation, Reasoning and Querying over the Semantic Web. In: 6th International Conference on Semantic Systems, Graz, Austria (September 1-3, 2010)Google Scholar
  2. 2.
    Klein, M., Fensel, D.: Ontology Versioning for the Semantic Web. In: International Semantic Web Working Symposium (SWWS 2001), California, USA, pp. 75–92 (July-August 2001)Google Scholar
  3. 3.
    Welty, C., Fikes, R.: A Reusable Ontology for Fluents in OWL. Frontiers in Artificial Intelligence and Applications 150, 226–236 (2006)Google Scholar
  4. 4.
    Artale, A., Franconi, E.: A Survey of Temporal Extensions of Description Logics. Annals of Mathematics and Artificial Intelligence 30(1-4) (2001)Google Scholar
  5. 5.
    Gutierrez, C., Hurtado, C., Vaisman, A.: Introducing Time into RDF. IEEE Trans. on Knowledge and Data Engineering 19(2), 207–218 (2007)CrossRefGoogle Scholar
  6. 6.
    Lutz, C.: Description logics with concrete domains - A survey. In: Advances in Modal Logics, King’s College, vol. 4 (2003)Google Scholar
  7. 7.
    Allen, J.F.: Maintaining Knowledge About Temporal Intervals. Communications of the ACM 26, 832–843 (1983)CrossRefzbMATHGoogle Scholar
  8. 8.
    Tappolet, J., Bernstein, A.: Applied Temporal RDF: Efficient Temporal Querying of RDF Data with SPARQL. In: Aroyo, L., Traverso, P., Ciravegna, F., Cimiano, P., Heath, T., Hyvönen, E., Mizoguchi, R., Oren, E., Sabou, M., Simperl, E. (eds.) ESWC 2009. LNCS, vol. 5554, pp. 308–322. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  9. 9.
    Horrocks, I., Kutz, O., Sattler, U.: The Even More Irresistible SROIQ. In: Proc. KR 2006, Lake District, UK (2006)Google Scholar
  10. 10.
    Grau, B.C., Horrocks, I., Motik, B., Parsia, B., Patel-Schneider, P., Sattler, U.: OWL 2: The Next Step for OWL. In: Web Semantics: Science, Services and Agents on the World Wide Web, vol. 6, pp. 309–322 (2008)Google Scholar
  11. 11.
    Milea, V., Frasincar, F., Kaymak, U.: Knowledge Engineering in a Temporal Semantic Web Context. In: The Eighth International Conference on Web Engineering, ICWE 2008 (2008)Google Scholar
  12. 12.
    Nebel, B., Burckert, H.J.: Reasoning about Temporal Relations: A Maximal Tractable Subclass of Allen’s Interval Algebra. Journal of the ACM (JACM) 42(1), 43–66 (1995)MathSciNetCrossRefzbMATHGoogle Scholar
  13. 13.
    van Beek, P., Cohen, R.: Exact and approximate reasoning about temporal relations. Computational Intelligence 6(3), 132–147 (1990)CrossRefGoogle Scholar
  14. 14.
    Tao, C., Wei, W.Q., Solbrig, H.R., Savova, G., Chute, C.G.: CNTRO: A Semantic Web Ontology for Temporal Relation Inferencing in Clinical Narratives. In: AMIA Annual Symp. Proc. 2010, pp. 787–791 (2010)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Sotiris Batsakis
    • 1
  • Kostas Stravoskoufos
    • 1
  • Euripides G. M. Petrakis
    • 1
  1. 1.Department of Electronic and Computer EngineeringTechnical University of Crete (TUC)ChaniaGreece

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