Large-scale Ontological Reasoning via Datalog
This work tackles the problem of scalable ontological reasoning for semantic web applications, but it appears incremental as it builds on existing compilations and algorithms.
The paper addresses the computational expense of reasoning over OWL 2 by reducing it to Datalog query evaluation, specifically implementing a new Magic Sets algorithm in DLV2 for Horn-SHIQ knowledge bases.
Reasoning over OWL 2 is a very expensive task in general, and therefore the W3C identified tractable profiles exhibiting good computational properties. Ontological reasoning for many fragments of OWL 2 can be reduced to the evaluation of Datalog queries. This paper surveys some of these compilations, and in particular the one addressing queries over Horn-$\mathcal{SHIQ}$ knowledge bases and its implementation in DLV2 enanched by a new version of the Magic Sets algorithm.