Epistemic First-order Queries over Description Logic Knowledge Bases

Querying Description Logic knowledge bases has received great attention in the last years. The need of coping with incomplete information is the distinguishing feature with respect to querying databases. Due to this feature, we have to deal with two conflicting needs: on the one hand, we would like to query the knowledge base with sophisticated mechanisms provided by full first-order logic as in databases; on the other hand, the presence of incomplete information makes query answering a much more difficult task than in databases. In this paper we advocate the use of an epistemic first-order query language, which is able to incorporate closed-world reasoning on demand, as a means for expressing sophisticated queries over Description Logic knowledge bases. We show that through a subset of this language, called EQL-Lite, we are able to formulate full first-order queries over Description Logic knowledge bases, while keeping computational complexity of query answering under control. In particular, we show that EQL-Lite queries over DL-Lite knowledge bases are first-order reducible (i.e., can be compiled into SQL) and hence can be answered in LogSpace through standard database technologies.