A Decision Procedure for the Alternation-Free Two-Way Modal μ-Calculus

Tanabe, Yoshinori; Takahashi, Koichi; Yamamoto, Masahiro; Tozawa, Akihiko; Hagiya, Masami

doi:10.1007/11554554_21

Cited by 20 publications

(45 citation statements)

References 14 publications

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“…We present a compact formalization of RDF [12]. Let U, B, and L be three disjoint infinite sets denoting the set of URIs (identifying a resource), blank nodes (denoting an unidentified resource) and literals (a character string or some other type of data) respectively.…”

Section: Rdf(s)mentioning

confidence: 99%

“…Each triple can be thought of as an edge between the subject and the object labelled by the predicate, hence a set of RDF triples is often referred to as an RDF graph. RDF has a model theoretic semantics [12].…”

Section: Rdf(s)mentioning

confidence: 99%

“…G ={(john, childOf, mary), (childOf, sp, ancestor), ( :b, hasF ather, john), (ancestor, dom, P erson), (ancestor, range, P erson)} RDF Schema (RDFS) may be considered as a simple ontology language expressing subsumption relations between classes or properties [12]. Technically, this is an RDF vocabulary used for expressing axioms constraining the interpretation of graphs.…”

Section: Rdf(s)mentioning

confidence: 99%

“…The language is being extended with different entailment regimes and regular path expressions 3 . The semantics of SPARQL relies on the definition of basic graph pattern matching that is built on top of RDF simple entailment [12]. However, it may be desirable to use SPARQL to query triples entailed from subclass, subproperty, range, domain, and other relations which can be represented using RDF schema.…”

Section: Introductionmentioning

confidence: 99%

“…SPARQL is interpreted over graphs, hence we encode it in a graph logic, specifically the alternation-free fragment of the µ-calculus [13] with converse and nominals [?] interpreted over labeled transition systems.…”

Section: Introductionmentioning

confidence: 99%

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SPARQL Query Containment under RDFS Entailment Regime

Chekol

Euzenat

Genevès

et al. 2012

Automated Reasoning

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Abstract. The problem of SPARQL query containment is defined as determining if the result of one query is included in the result of another for any RDF graph. 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 µ-calculus: where RDF graphs become transition systems, queries and schema axioms become formulas. Thus, the containment problem is reduced to formula satisfiability test. Beyond the logic's expressive power, satisfiability solvers are available for it. Hence, this study allows to exploit these advantages.

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Section: Rdf(s)mentioning

confidence: 99%

Section: Rdf(s)mentioning

confidence: 99%

Section: Rdf(s)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

SPARQL Query Containment under RDFS Entailment Regime

Chekol

Euzenat

Genevès

et al. 2012

Automated Reasoning

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Abstraction of Graph Transformation Systems by Temporal Logic and Its Verification

Yamamoto

Tanabe

Takahashi

et al. 2008

Verified Software: Theories, Tools, Experiments

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Evaluating and Benchmarking SPARQL Query Containment Solvers

Chekol

Euzenat

Genevès

et al. 2013

Advanced Information Systems Engineering

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Query containment is the problem of deciding if the answers to a query are included in those of another query for any queried database. This problem is very important for query optimization purposes. In the SPARQL context, it can be equally useful. This problem has recently been investigated theoretically and some query containment solvers are available. Yet, there were no benchmarks to compare theses systems and foster their improvement. In order to experimentally assess implementation strengths and limitations, we provide a first SPARQL containment test benchmark. It has been designed with respect to both the capabilities of existing solvers and the study of typical queries. Some solvers support optional constructs and cycles, while other solvers support projection, union of conjunctive queries and RDF Schemas. No solver currently supports all these features or OWL entailment regimes. The study of query demographics on DBPedia logs shows that the vast majority of queries are acyclic and a significant part of them uses UNION or projection. We thus test available solvers on their domain of applicability on three different benchmark suites. 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.

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A Decision Procedure for the Alternation-Free Two-Way Modal μ-Calculus

Cited by 20 publications

References 14 publications

SPARQL Query Containment under RDFS Entailment Regime

SPARQL Query Containment under RDFS Entailment Regime

Abstraction of Graph Transformation Systems by Temporal Logic and Its Verification

Evaluating and Benchmarking SPARQL Query Containment Solvers

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