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Dynamic Querying of Mass-Storage RDF Data with Rule-Based Entailment Regimes

ARAN - Access to Research at NUI Galway

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dc.contributor.author Krennwallner, Thomas en
dc.contributor.author Martello, Alessandra en
dc.contributor.author Polleres, Axel en
dc.date.accessioned 2009-11-30T15:27:27Z en
dc.date.available 2009-11-30T15:27:27Z en
dc.date.issued 2009 en
dc.identifier.citation Giovambattista Ianni, Thomas Krennwallner, Alessandra Martello, Axel Polleres "Dynamic Querying of Mass-Storage RDF Data with Rule-Based Entailment Regimes", Proceedings of the 8th International Semantic Web Conference (ISWC 2009), Springer, 2009. en
dc.identifier.uri http://hdl.handle.net/10379/456 en
dc.description.abstract RDF Schema (RDFS) as a lightweight ontology language is gaining popularity and, consequently, tools for scalable RDFS inference and querying are needed. SPARQL has become recently aW3C standard for querying RDF data, but it mostly provides means for querying simple RDF graphs only, whereas querying with respect to RDFS or other entailment regimes is left outside the current specification. In this paper, we show that SPARQL faces certain unwanted ramifications when querying ontologies in conjunction with RDF datasets that comprise multiple named graphs, and we provide an extension for SPARQL that remedies these effects. Moreover, since RDFS inference has a close relationship with logic rules, we generalize our approach to select a custom rule set for specifying inferences to be taken into account in a SPARQL query. We show that our extensions are technically feasible by providing benchmark results for RDFS querying in our prototype system GiaBATA, which uses Datalog coupled with a persistent Relational Database as a back-end for implementing SPARQL with dynamic rule-based inference. By employing different optimization techniques like magic set rewriting our system remains competitive with state-of-the-art RDFS querying systems. en
dc.format application/pdf en
dc.language.iso en en
dc.publisher Springer en
dc.subject.lcsh Ontology en
dc.subject.lcsh Querying (Computer science) en
dc.title Dynamic Querying of Mass-Storage RDF Data with Rule-Based Entailment Regimes en
dc.type Conference paper en
dc.local.publishedsource http://dx.doi.org/10.1007/978-3-642-04930-9_20 en
dc.local.publisherstatement The original publication is available at www.springerlink.com en
dc.description.peer-reviewed peer-reviewed en
dc.contributor.funder Science Foundation Ireland en

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