RuQAR: Querying OWL 2 RL Ontologies with Rule Engines and Relational Databases

  • Jarosław Bąk
  • Michał Blinkiewicz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10448)


We present RuQAR, a tool that supports the ABox reasoning as well as query answering with OWL 2 RL ontologies. RuQAR provides a non-naive method of transforming such ontologies into rules which can be executed by a forward chaining rule engine. Thus, query answering can be performed using functions available in a rule engine. Moreover, RuQAR supports a relational database access which extends reasoning scalability. We evaluate our tool using the LUBM benchmark ontology and data stored in relational databases. We describe our approach, RuQAR’s implementation details as well as future research and development.


Query answering OWL 2 RL Rule engine Database access 



The work presented in this paper was supported by UMO-2011/03/N/ST6/01602 grant and by Polish Ministry of Science and Higher Education under grant 04/45/DSPB/0163.


  1. 1.
    Bak, J.: Ruqar: reasoning with OWL 2 RL using forward chaining engines. In: Informal Proceedings of the 4th International Workshop on OWL Reasoner Evaluation (ORE-2015) Co-located with the 28th International Workshop on Description Logics (DL 2015), Athens, Greece, 6 June 2015, pp. 31–37 (2015)Google Scholar
  2. 2.
    Bak, J., Jedrzejek, C.: Rule-based reasoning system for OWL 2 RL ontologies. In: Hwang, D., Jung, J.J., Nguyen, N.-T. (eds.) ICCCI 2014. LNCS (LNAI), vol. 8733, pp. 404–413. Springer, Cham (2014). doi: 10.1007/978-3-319-11289-3_41CrossRefGoogle Scholar
  3. 3.
    Falkowski, M., Jedrzejek, C.: An efficient sql-based querying method to rdf schemata. Control Cybern. 38(1), 193–213 (2009)MathSciNetzbMATHGoogle Scholar
  4. 4.
    Faruqui, R.U., MacCaull, W.: Owlontdb: a scalable reasoning system for OWL 2 RL ontologies with large aboxes. In: Weber, J., Perseil, I. (eds.) FHIES 2012. LNCS, vol. 7789, pp. 105–123. Springer, Heidelberg (2013). doi: 10.1007/978-3-642-39088-3_7CrossRefGoogle Scholar
  5. 5.
    The W3C SPARQL Working Group. Sparql 1.1 overview (2013).
  6. 6.
    Guo, Y., Pan, Z., Heflin, J.: Lubm: a benchmark for owl knowledge base systems. Web Semant. 3(2–3), 158–182 (2005)CrossRefGoogle Scholar
  7. 7.
    Hogan, A., Decker, S.: On the ostensibly silent ‘W’ in OWL 2 RL. In: Polleres, A., Swift, T. (eds.) RR 2009. LNCS, vol. 5837, pp. 118–134. Springer, Heidelberg (2009). doi: 10.1007/978-3-642-05082-4_9CrossRefGoogle Scholar
  8. 8.
    Horridge, M., Bechhofer, S.: The owl api: a java api for working with owl 2 ontologies. In: OWLED (2009)Google Scholar
  9. 9.
    Kolovski, V., Wu, Z., Eadon, G.: Optimizing enterprise-scale OWL 2 RL reasoning in a relational database system (2010)Google Scholar
  10. 10.
    Meditskos, G., Bassiliades, N.: Dlejena: a practical forward-chaining owl 2 rl reasoner combining jena and pellet. J. Web Sem. 8(1), 89–94 (2010)CrossRefGoogle Scholar
  11. 11.
    Motik, B., Grau, B.C., Horrocks, I., Wu, Z., Fokoue, A., Lutz, C.: OWL 2 Web Ontology Language Profiles, 2nd edn. W3C Recommention, Cambridge (2012)Google Scholar
  12. 12.
    O’Connor, M.J., Das, A.: A pair of owl 2 rl reasoners. In: Klinov, P., Horridge, M. (eds.) CEUR Workshop Proceedings of OWLED, vol. 849. (2012)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Institute of Control and Information EngineeringPoznan University of TechnologyPoznanPoland

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