Ontology-based access to large data-sets has recently gained a lot of attention. To access data e_ciently, one approach is to rewrite the ontology into Datalog, and then use powerful Datalog engines to compute implicit entailments. Existing rewriting techniques support Description Logics (DLs) from ELH to Horn-SHIQ. We go one step further and present one such data-independent rewriting technique for Horn-SRIQ⊓, the extension of Horn-SHIQ that supports role chain axioms, an expressive feature prominently used in many real-world ontologies. We evaluated our rewriting technique on a large known corpus of ontologies. Our experiments show that the resulting rewritings are of moderate size, and that our approach is more efficient than state-of-the-art DL reasoners when reasoning with data-intensive ontologies. / This is an extended version of the article to appear in the proceedings of AAAI 2019.
Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:79612 |
Date | 20 June 2022 |
Creators | Carral, David, González, Larry, Koopmann, Patrick |
Publisher | Technische Universität Dresden |
Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
Language | English |
Detected Language | English |
Type | info:eu-repo/semantics/acceptedVersion, doc-type:report, info:eu-repo/semantics/report, doc-type:Text |
Rights | info:eu-repo/semantics/openAccess |
Relation | urn:nbn:de:bsz:14-qucosa2-785040, qucosa:78504 |
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