Ontology-Mediated Query Answering: Performance Challenges and Advances

International audienceOntology-mediated query answering (OMQA) is a recent data management trend in the Artificial Intelligence, Database and Semantic Web areas, which aims at answering database queries on knowledge bases. Because it is an intricate combination of automated reasoning and database query evaluation, it raises major performance challenges. In this demonstration, we showcase a decade of OMQA optimization to understand "Where do we stand now and how did we get there?" and we highlight a promising new OMQA optimization that brings further significant performance improvement to discuss "What's next?"

Urethane Formation with an Excess of Isocyanate or Alcohol: Experimental and Ab Initio Study

A kinetic and mechanistic investigation of the alcoholysis of phenyl isocyanate using 1-propanol as the alcohol was undertaken. A molecular mechanism of urethane formation in both alcohol and isocyanate excess is explored using a combination of an accurate fourth generation Gaussian thermochemistry (G4MP2) with the Solvent Model Density (SMD) implicit solvent model. These mechanisms were analyzed from an energetic point of view. According to the newly proposed two-step mechanism for isocyanate excess, allophanate is an intermediate towards urethane formation via six-centered transition state (TS) with a reaction barrier of 62.6 kJ/mol in the THF model. In the next step, synchronous 1,3-H shift between the nitrogens of allophanate and the cleavage of the C–N bond resulted in the release of the isocyanate and the formation of a urethane bond via a low-lying TS with 49.0 kJ/mol energy relative to the reactants. Arrhenius activation energies of the stoichiometric, alcohol excess and the isocyanate excess reactions were experimentally determined by means of HPLC technique. The activation energies for both the alcohol (measured in our recent work) and the isocyanate excess reactions were lower compared to that of the stoichiometric ratio, in agreement with the theoretical calculations

OptiRef : optimisation pour la gestion de données dans les bases de connaissances

National audienc

OptiRef: Query Optimization for Knowledge Bases

International audienceOntology-mediated query answering (OMQA) consists in asking database queries on a knowledge base (KB); a KB is a set of facts, the KB's database, described by domain knowledge, the KB's ontology. FOL-rewritability is the main OMQA technique: it reformulates a query w.r.t. the KB's ontology so that the evaluation of the reformulated query on the KB's database computes the correct answers. However, because this technique embeds the domain knowledge relevant to the query into the reformulated query, a reformulated query may be complex and its optimization is the crux of efficiency. We showcase OptiRef that implements a novel, general optimization framework for efficient query answering on datalog+/-, description logic, existential rules, OWL and RDF/S KBs. OptiRef optimizes reformulated queries by rapidly computing, based on a KB's database summary, simpler (contained) queries with the same answers. We demonstrate OptiRef's effectiveness on wellestablished benchmarks: performance is significantly improved in general, up to several orders of magnitude in the best cases

Gestion de données efficace dans les bases de connaissances

National audienc

Query Optimization for Ontology-Mediated Query Answering

International audienceOntology-mediated query answering (OMQA) consists in asking database queries on knowledge bases (KBs); a KB is a set of facts called the KB's database, which is described by domain knowledge called the KB's ontology. A widely-investigated OMQA technique is FO-rewriting: every query asked on a KB is reformulated w.r.t. the KB's ontology, so that its answers are computed by the relational evaluation of the query reformulation on the KB's database. Crucially, because FO-rewriting compiles the domain knowledge relevant to queries into their reformulations, query reformulations may be complex and their optimization is the crux of efficiency. We devise a novel optimization framework for a large set of OMQA settings that enjoy FO-rewriting: conjunctive queries, i.e., the core select-project-join queries, asked on KBs expressed using datalog±, description logics, existential rules, OWL, or RDFS. We optimize the query reformulations produced by state-of-the-art FO-rewriting algorithms by computing rapidly, with the help of a KB's database summary, simpler (contained) queries with the same answers that can be evaluated faster by RDBMSs. We show on a well-established OMQA benchmark that time performance is significantly improved by our optimization framework in general, up to three orders of magnitude

Gestion de données efficace dans les bases de connaissances

National audienc

Gestion de données efficace dans les bases de connaissances

National audienc

OptiRef : optimisation pour la gestion de données dans les bases de connaissances

National audienc