Tractable query answering and rewriting under description logic constraints

Abstract

Answering queries over an incomplete database w.r.t. a set of constraints is an important computational task with applications in fields as diverse as information integration and metadata management in the semantic Web. Description Logics (DLs) are constraint languages that have been extensively studied with the goal of providing useful modeling constructs while keeping the query answering problem decidable. For many DLs, query answering under constraints can be solved via query rewriting: given a conjunctive query Q and a set of DL constraints T , the query Q can be transformed into a datalog query Q T that takes into account the semantic consequences of T ; then, to obtain answers to Q w.r.t. T and some (arbitrary) database instance A, one can simply evaluate Q T over A using existing (deductive) database technology, without taking T into account. In this paper, we present a novel query rewriting algorithm that handles constraints modeled in the DL ELHIO ¬ and use it to show that answering conjunctive queries in this setting is PTime-complete w.r.t. data complexity. Our algorithm deals with various description logics of the EL and DL-Lite families and is worst-case optimal w.r.t. data complexity for all of them.

Repairing Ontologies for Incomplete Reasoners

“…Our implementation uses the system REQUIEM [13] for the computation of TBox rewritings. We evaluated our approach using the following two well-known ontologies.…”

“…Depending on the language that T is expressed in, systems such as REQUIEM [13] and KAON2 [5] can compute a (possibly disjunctive) datalog rewriting; now whenever the rewriting is a datalog program, each datalog rule in the rewriting can always be 'rolled-up' into an OWL 2 RL axiom. Therefore, in order to simplify the presentation, we consider such rewritings to be OWL 2 RL TBoxes rather than datalog programs.…”

Ontology-Guided Image Interpretation for GEOBIA of High Spatial Resolution Remote Sense Imagery: A Coastal Area Case Study

“…OWL-QL is a lightweight language that sacrifices some expressiveness in comparison with OWL 2. Here, query-answering is based on REQUIEM (REsolution-based QUery rewrIting for Expressive Models) [26], a prototypical implementation of a query rewriting algorithm [27]. …”

Hydrowl: A Hybrid Query Answering System for OWL 2 DL Ontologies

“…Hydrowl accomplishes this by combining ans with a second system ans which can explicate such type of information. One such family of systems are query rewriting systems which take as input a (possibly non-SPARQL) query Q and a TBox T and compute a so-called query rewriting Rew [13][14][15]. Roughly speaking, a rewriting Rew for Q, T consists of two parts, a set of datalog rules Rew D which captures ground entailments of T and a union of conjunctive queries Rew Q which captures all inferences related to non-ground entailments.…”