Abstract
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.
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KAON2 webpage: http://kaon2.semanticweb.org/.
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In DB case reasoning is performed during the execution of each query.
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Acknowledgments
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.
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Bąk, J., Blinkiewicz, M. (2017). RuQAR: Querying OWL 2 RL Ontologies with Rule Engines and Relational Databases. In: Nguyen, N., Papadopoulos, G., Jędrzejowicz, P., Trawiński, B., Vossen, G. (eds) Computational Collective Intelligence. ICCCI 2017. Lecture Notes in Computer Science(), vol 10448. Springer, Cham. https://doi.org/10.1007/978-3-319-67074-4_10
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