Members
Overall Objectives
Research Program
Highlights of the Year
New Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
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Section: New Results

Logics and Graph-Based Languages for Ontology-Mediated Query Answering

Participants : Jean-François Baget, Meghyn Bienvenu, Efstathios Delivorias, Michel Leclère, Marie-Laure Mugnier, Swan Rocher, Federico Ulliana.

Ontolology-mediated query answering (and more generally Ontology-Based Data Access, OBDA) is a recent paradigm in data management, which takes into account inferences enabled by an ontology when querying data. In other words, the notion of a database is replaced by that of a knowledge base, composed of data (also called facts) and of an ontology. Two families of formalisms for representing and reasoning with the ontological component are considered in this context: description logics and the more recent existential rule framework. Until last year, the team has mainly investigated existential rules. This expressive formalism generalizes most lightweight description logics used in OBDA (such as ℰℒ and DL-Lite, on which OWL 2 tractable profiles are based) on the one hand, and Datalog, the language of deductive databases, on the other hand. With the arrival of Meghyn Bienvenu, description logics have joined the core formalisms studied by the team. Compared to existential rules, the description logics considered for OBDA lead to lower complexity classes and specific algorithmic techniques. Studying both formalisms is scientifically highly relevant, specially in the context of OBDA.

We have also broadened this research line by starting investigating ontological languages for non-relational data, an issue that has barely been considered yet.

Before presenting this year' results, we recall the two classical ways of processing rules, namely forward chaining and backward chaining. In forward chaining (also known as the chase in databases), the rules are applied to enrich the initial facts and query answering can then be solved by evaluating the query against the “saturated” factbase (as in a classical database system i.e., with forgetting the rules). The backward chaining process can be divided into two steps: first, the initial query is rewritten using the rules into a first-order query (typically a union of conjunctive queries, UCQ); then the rewritten query is evaluated against the initial factbase (again, as in a classical database system). Note that forward and backward processes do not halt for all kinds of existential rules nor all lightweight description logics.

New Results in the Description Logics Framework

When using Description Logics (DL) ontologies to access relational data, mappings are used to link the relational schema to the vocabulary of the ontology (which uses only unary and binary predicates). In order to debug and optimize DL-based OBDA systems, it is important to be able to analyze and compare ontology-mapping pairs, called OBDA specifications. Prior work in this direction compared specifications using classical notions of equivalence and entailment.

New Results in the Existential Rule Framework

Several new theoretical results have been obtained on ontology-mediated query answering with existential rules:

Querying NoSQL databases (Key-value stores)

Over the last decade, research efforts to develop algorithms for OBDA have built on the assumption that data conforms to relational structures (including RDF) and that the paradigm can be deployed on top of relational databases with conjunctive queries at the core (e.g., in SQL or SPARQL). However, this is not the prominent way on which data is today stored and exchanged, especially in the Web. Whether OBDA can be developed for non-relational structures, like those shared by increasingly popular NOSQL languages sustaining Big-Data analytics, is still an open question. In collaboration with Marie-Christine Rousset (University of Grenoble, LIG), we proposed the first framework for studying the problem of answering ontology-mediated queries on top of NOSQL key-value stores. More precisely, we formalized the core data model and basic queries of these systems and introduced a rule language (NO-RL) to express lightweight ontologies on top of data. We defined a sound and complete query rewriting technique and studied the decidability and data complexity of answering ontology-mediated queries depending on considered the rule fragment.