Rule-Based OWL Reasoning for Specific Embedded Devices

  • Christian Seitz
  • René Schönfelder
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7032)


Ontologies have been used for formal representation of knowledge for many years now. One possible knowledge representation language for ontologies is the OWL 2 Web Ontology Language, informally OWL 2. The OWL specification includes the definition of variants of OWL, with different levels of expressiveness. OWL DL and OWL Lite are based on Description Logics, for which sound and complete reasoners exits. Unfortunately, all these reasoners are too complex for embedded systems. But since evaluation of ontologies on these resource constrained devices becomes more and more necessary (e.g. for diagnostics) we developed an OWL reasoner for embedded devices. We use the OWL 2 sub language OWL 2 RL, which can be implemented using rule-based reasoning engines. In this paper we present our used embedded hardware, the implemented reasoning component, and results regarding performance and memory consumption.


Embed System Description Logic Memory Usage Conjunctive Query Embed Device 
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.


  1. 1.
    Ali, S., Kiefer, S.: μOR – A Micro OWL DL Reasoner for Ambient Intelligent Devices. In: Abdennadher, N., Petcu, D. (eds.) GPC 2009. LNCS, vol. 5529, pp. 305–316. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  2. 2.
    Baader, F., Lutz, C., Suntisrivaraporn, B.: CEL — A polynomial-time reasoner for life science ontologies. In: Furbach, U., Shankar, N. (eds.) IJCAR 2006. LNCS (LNAI), vol. 4130, pp. 287–291. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  3. 3.
    Bechhofer, S.: The DIG description logic interface: DIG/1.1. Tech. rep., University of Manchester (2003)Google Scholar
  4. 4.
    Forgy, C.L.: Rete: A fast algorithm for the many pattern/many object pattern match problem. Department of Computer Science, Carnegie-Mellon University, Pittsburgh (2003)Google Scholar
  5. 5.
    Grosof, B., Dean, M., Ganjugunte, S., Tabet, S., Neogy, C.: Sweetrules homepage (2005),
  6. 6.
    Gumstix: Gumstix website (2010),
  7. 7.
    Hähnle, R.: Tableaux and Related Methods. Handbook of Automated Reasoning (2001)Google Scholar
  8. 8.
    Horridge, M.: OWL2 API (2010),
  9. 9.
    Kleemann, T., Sinner, A.: KRHyper - in your pocket. In: Nieuwenhuis, R. (ed.) CADE 2005. LNCS (LNAI), vol. 3632, pp. 452–457. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  10. 10.
    Krötzsch, M.: Efficient inferencing for OWL EL. In: Janhunen, T., Niemelä, I. (eds.) JELIA 2010. LNCS, vol. 6341, pp. 234–246. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  11. 11.
    Krötzsch, M.: Efficient inferencing for the description logic underlying OWL EL. Institut AIFB, KIT, Karlsruhe (2010)Google Scholar
  12. 12.
    Krötzsch, M., ul Mehdi, A., Rudolph, S.: Orel: Database-driven reasoning for OWL 2 profiles. In: Int. Workshop on Description Logics (2010)Google Scholar
  13. 13.
    Meditskos, G., Bassilades, N.: A rule-based object-oriented OWL reasoner. In: IEEE Transactions on Knowledge and Data Engineering (2008)Google Scholar
  14. 14.
    Meditskos, G., Bassiliades, N.: DLEJena: A practical forward-chaining OWL 2 RL reasoner combining Jena and Pellet. Web Semantics 8(1), 89–94 (2010)CrossRefGoogle Scholar
  15. 15.
    Jang, M., Sohn, J.-C.: Bossam: An Extended Rule Engine for OWL Inferencing. In: Antoniou, G., Boley, H. (eds.) RuleML 2004. LNCS, vol. 3323, pp. 128–138. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  16. 16.
    Parsia, B., Sirin, E.: Pellet: An OWL DL Reasoner. In: Third International Semantic Web Conference-Poster (2004)Google Scholar
  17. 17.
    Parsia, B., Sirin, E., Grau, B.C., Ruckhaus, E., Hewlett, D.: Cautiously approaching SWRL. Tech. rep., University of Maryland (2005)Google Scholar
  18. 18.
    Raptor: Raptor website (2010),
  19. 19.
    Riley, G.: CLIPS (2010),
  20. 20.
    Tsarkov, D., Horrocks, I.: FaCT++ Description Logic Reasoner: System Description. In: Furbach, U., Shankar, N. (eds.) IJCAR 2006. LNCS (LNAI), vol. 4130, pp. 292–297. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  21. 21.
    University, L.: LUBM website (2010),
  22. 22.
    Volz, R.: FactConverter (2010),
  23. 23.
    World Wide Web Consortium (W3C): OWL-Lite (2010),
  24. 24.
    World Wide Web Consortium (W3C): OWL profiles (2010),
  25. 25.
    World Wide Web Consortium (W3C): SPARQL (2010),
  26. 26.
    World Wide Web Consortium (W3C) OWL Working Group: nTriples Format (2010),

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Christian Seitz
    • 1
  • René Schönfelder
    • 1
  1. 1.Siemens AG, Corporate TechnologyIntelligent Systems and ControlMunichGermany

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