Abstract
We study the problem of approximating Description Logic (DL) ontologies specified in a source language \(\mathcal{L}_S\) in terms of a less expressive target language \(\mathcal{L}_T\). 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 DL ontology. 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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Console, M., Mora, J., Rosati, R., Santarelli, V., Savo, D.F. (2014). Effective Computation of Maximal Sound Approximations of Description Logic Ontologies. In: Mika, P., et al. The Semantic Web – ISWC 2014. ISWC 2014. Lecture Notes in Computer Science, vol 8797. Springer, Cham. https://doi.org/10.1007/978-3-319-11915-1_11
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DOI: https://doi.org/10.1007/978-3-319-11915-1_11
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