Abstract
Semantic Web reasoning can be a complex task: depending on the amount of data and the ontologies involved, traditional OWL DL reasoners can be too slow to face problems in real time. An alternative is to use a rule-based reasoner together with the OWL RL/RDF rules as stated in the specification of the OWL 2 language profiles. In most cases this approach actually improves reasoning times, but due to the complexity of the rules, not as much as it could. In this paper we present an improved strategy: based on the TBoxes of the ontologies involved in a reasoning task, we create more specific rules which then can be used for further reasoning. We make use of the EYE reasoner and its logic Notation3. In this logic, rules can be employed to derive new rules which makes the rule creation a reasoning step on its own. We evaluate our implementation on a semantic nurse call system. Our results show that adding a pre-reasoning step to produce specialized rules improves reasoning times by around 75 %.
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References
FuXi 1.4: A Python-based, bi-directional logical reasoning system for the semantic web. http://code.google.com/p/fuxi/
Arndt, D., et al.: Ontology reasoning using rules in an eHealth context. In: Bassiliades, N., Gottlob, G., Sadri, F., Paschke, A., Roman, D. (eds.) RuleML 2015. LNCS, vol. 9202, pp. 465–472. Springer, Heidelberg (2015)
Arndt, D., Verborgh, R., De Roo, J., Sun, H., Mannens, E., Van De Walle, R.: Semantics of notation3 logic: a solution for implicit quantification. In: Bassiliades, N., Gottlob, G., Sadri, F., Paschke, A., Roman, D. (eds.) RuleML 2015. LNCS, vol. 9202, pp. 127–143. Springer, Heidelberg (2015)
Berners-Lee, T.: \(cwm\) (2000–2009). http://www.w3.org/2000/10/swap/doc/cwm.html
Berners-Lee, T., Connolly, D.: Notation3 (N3): A readable RDF syntax. In: W3C Team Submission, March 2011. http://www.w3.org/TeamSubmission/n3/
Berners-Lee, T., Connolly, D., Kagal, L., Scharf, Y., Hendler, J.: N3 Logic: a logical framework for the World Wide Web. Theory Pract. Logic Program. 8(3), 249–269 (2008)
Bishop, B., Bojanov, S.: Implementing OWL 2 RL and OWL 2 QL rule-sets for OWLIM. In: OWLED, vol. 796 (2011)
Bishop, B., Kiryakov, A., Ognyanoff, D., Peikov, I., Tashev, Z., Velkov, R.: OWLIM: a family of scalable semantic repositories. Semant. Web 2(1), 33–42 (2011)
Calvanese, D., Carroll, J., Di Giacomo, G., Hendler, J., Herman, I., Parsia, B., Patel-Schneider, P.F., Ruttenberg, A., Sattler, U., Schneider, M.: OWL 2 web ontology language profiles 2nd edn. In: W3C Recommendation, December 2012. www.w3.org/TR/owl2-profiles/
Cyganiak, R., Wood, D., Lanthaler, M.: RDF 1.1: Concepts and Abstract Syntax. In: W3C Recommendation, February 2014. http://www.w3.org/TR/2014/REC-rdf11-concepts-20140225/
De Roo, J.: Euler yet another proof engine (1999–2015). http://eulersharp.sourceforge.net/
De Roo, J.: EYE and OWL 2 (1999–2015). http://eulersharp.sourceforge.net/2003/03swap/eye-owl2.html
Declerck, T., Krieger, H.U.: Translating XBRL into description logic. an approach using protege, sesame & OWL. In: BIS, pp. 455–467 (2006)
Horrocks, I., Patel-Schneider, P.F., Boley, H., Tabet, S., Grosof, B., Dean, M.: SWRL: a semantic web rule language combining OWL and RuleML. In: W3C Member Submission, 21 May 2004. http://www.w3.org/Submission/SWRL/
Ongenae, F., Bleumes, L., Sulmon, N., Verstraete, M., Van Gils, M., Jacobs, A., De Zutter, S., Verhoeve, P., Ackaert, A., De Turck, F.: Participatory design of a continuous care ontology: towards a user-driven ontology engineering methodology. In: Proceedings of the Knowledge Engineering and Ontology, pp. 81–90 (2011)
Parsia, B., Sirin, E.: Pellet: An OWL DL reasoner. In: Proceedings of the Third International Semantic Web Conference (2004)
Patel, C., et al.: Matching patient records to clinical trials using ontologies. In: Aberer, K., et al. (eds.) ASWC 2007 and ISWC 2007. LNCS, vol. 4825, pp. 816–829. Springer, Heidelberg (2007)
Shearer, R., Motik, B., Horrocks, I.: Hermit: a highly-efficient OWL reasoner. In: OWLED, vol. 432, p. 91 (2008)
Verborgh, R., De Roo, J.: Drawing conclusions from linked data on the web. IEEE Softw. 32(5), 23–27 (2015)
Wu, Z., Eadon, G., Das, S., Chong, E.I., Kolovski, V., Annamalai, M., Srinivasan, J.: Implementing an inference engine for RDFS/OWL constructs and user-defined rules in Oracle. In: 2008 IEEE 24th International Conference on Data Engineering, ICDE 2008, pp. 1239–1248. IEEE (2008)
Acknowledgements
The research activities described in this paper were funded by Ghent University, iMinds, the IWT Flanders, the FWO-Flanders, and the European Union, in the context of the project “ORCA”, which is a collaboration of Televic Healthcare, Internet-Based Communication Networks and Services (IBCN), and Data Science Lab (DSLab).
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Arndt, D. et al. (2016). Improving OWL RL Reasoning in N3 by Using Specialized Rules. In: Tamma, V., Dragoni, M., Gonçalves, R., Ławrynowicz, A. (eds) Ontology Engineering. OWLED 2015. Lecture Notes in Computer Science(), vol 9557. Springer, Cham. https://doi.org/10.1007/978-3-319-33245-1_10
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DOI: https://doi.org/10.1007/978-3-319-33245-1_10
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