Effective computation of maximal sound approximations of Description Logic ontologies
published: Dec. 19, 2014, recorded: October 2014, views: 9
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We study the problem of approximating Description Logic (DL) ontologies speciﬁed in a source language LS in terms of a less expressive target languageLT. This problem is getting very relevant in practice: e.g., approximation is often needed in ontology-based data access systems, which are able to deal with ontology languages of a limited expressiveness. We ﬁrst provide a general, parametric, and semantically well-founded deﬁnition of maximal sound approximation of a DLontology. Then, we present an algorithm that is able to effectively compute two different notions of maximal sound approximation according to the above parametric semantics when the source ontology language is OWL 2 and the target ontology language is OWL 2 QL. Finally, we experiment the above algorithm by computing the two OWL 2 QL approximations of a large set of existing OWL 2 ontologies. The experimental results allow us both to evaluate the effectiveness of the proposed notions of approximation and to compare the two different notions of approximation in real cases.
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