Sparql entailment regimes

Sans implication, la requête donnerait une réponse vide, mais sous implication RDF, le triplet 5 peut servir à déduire que zoo:host est une propriété du type ex:zoo1 et ainsi servir de solution à cette requête SPARQL.

Afin de récupérer ex:cat1 et ex:cat2, on aurait besoin d'un système qui supporte les implications RDFS. Voici le résultat final de la requête "qui est un animal? Le logiciel 4SR que nous utiliserons dans un TP est l'une des versions qui sont en cours d'implémentation.

De plus, les concepts d'ontologies sont très complexes à appréhender et le fait de comprendre la finalité exacte d'une ontologie permet de relativiser son utilisation. Une page de Wikiversité. Début de la boite de navigation du chapitre. Système d'implication. Un système d'implication. Un graphe bien formé. Espaces de noms Page Discussion. Communiquer La salle café Discussion instantanée Soutien pédagogique Requêtes.

Contribuer Aide Bac à sable Communauté Faire un don. These experiments show that i tested solutions are overall functionally correct, ii in spite of its complexity, SPARQL query containment is practicable for acyclic queries, iii state-of-the-art solvers are at an early stage both in terms of capability and implementation.

This chapter provides an introduction to the RDF language as well as surveys the languages that can be used for querying RDF graphs. Then it reviews some of the languages that can be used for querying RDF and provides a comparison between these query languages. Query containment is important in many areas, including information integration, query optimization, and reasoning about Entity-Relationship diagrams. We encode this problem into an expressive logic called the mu-calculus where RDF graphs become transition systems, queries and schema axioms become formulas.

Thus, the containment problem is reduced to formula satisfiability. Beyond the logic's expressive power, satisfiability solvers are available for it. Hence, this study allows to exploit these advantages. SPARQL query containment under schema axioms is the problem of determining whether, for any RDF graph satisfying a given set of schema axioms, the answers to a query are contained in the answers of another query. This problem has major applications for verification and optimization of queries.

In order to solve it, we rely on the mu-calculus. Firstly, we provide a mapping from RDF graphs into transition systems. This allows us to reduce query containment and equivalence to satisfiability in the mu-calculus.

Bibliography on Semantic web queries/Interrogation du web sémantique (2016-12-22)

Finally, we prove a double exponential upper bound for containment under SHI schema axioms. The problem of SPARQL query containment has recently attracted a lot of attention due to its fundamental purpose in query optimization and information integration.

New approaches to this problem, have been put forth, that can be implemented in practice. However, these approaches suffer from various limitations: coverage size and type of queriesresponse time how long it takes to determine containmentand the technique applied to encode the problem. In order to experimentally assess implementation limitations, we designed a benchmark suite offering different experimental settings depending on the type of queries, projection and reasoning RDFS.

We have applied this benchmark to three available systems using different techniques highlighting the strengths and weaknesses of such systems. Query containment is defined as the problem of determining if the result of a query is included in the result of another query for any given dataset. It has major applications in query optimization and knowledge base verification. The main objective of this thesis is to provide sound and complete procedures to determine containment of SPARQL queries under expressive description logic axioms.

SPARQL Protocol and RDF Query Language/Système d'implication

Further, we implement these procedures to support theoretical results by experimentation. To date, testing query containment has been performed using different techniques: containment mapping, canonical databases, automata theory techniques and through a reduction to the validity problem in logic.

In this thesis, we use the later technique to test containment of SPARQL queries using an expressive logic called mu-calculus. In doing so, RDF graphs are encoded as transition systems which preserves its characteristics, and queries and schema axioms are encoded as mu-calculus formulae.

Thereby, query containment can be reduced to the validity test in the logic. Additionally, it provides theoretically and experimentally proven procedures to check containment of those decidable fragments. Finally, this thesis proposes a benchmark for containment solvers. This benchmark is used to test and compare the current state-of-the-art containment solvers.

This language has been studied from different perspectives such as optimization and extension. We study the static analysis of queries written in this language, in particular, containment of queries: determining whether, for any graph, the answers to a query are contained in those of another query.

Our approach consists in encoding RDF graphs as transition systems and queries as mu-calculus formulas and then reducing the containment problem to testing satisfiability in the logic. We establish complexity bounds and report experimental results. RDF is a knowledge representation language dedicated to the annotation of resources within the framework of the semantic web.

Other languages, inspired by the work in databases, use regular expressions for searching paths in RDF graphs. Each approach can express queries that are out of reach of the other one. Hence, we aim at combining these two approaches. PRDF thus offers both graph patterns and path expressions.