Optimizing FOL reducible query answering: Understanding performance challenges

Semantic Web data management raises the challenge of answering queries under constraints (i.e., in the presence of implicit data). To bridge the gap between this extended setting and that of query evaluation provided by database engines, a reasoning step (w.r.t. the constraints) is necessary before query evaluation. A large and useful set of ontology languages enjoys FOL reducibility of query answering: queries can be answered by evaluating a SQLized first-order logic (FOL) formula (obtained from the query and the ontology) directly against the explicitly stored data (i.e., without considering the ontological constraints). Our demonstration showcases to the attendees, and analyzes, the performance of several reformulation-based query answering techniques, including one we recently described in [5], applied to the lightweight description logic DL-LiteR underpinning the W3C's OWL2 QL profile.