Containment and Minimization of RDF/S Query Patterns

Serfiotis, Giorgos; Koffina, Ioanna; Christophides, Vassilis; Tannen, Val

doi:10.1007/11574620_44

Cited by 37 publications

(46 citation statements)

References 14 publications

(16 reference statements)

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“…In [2] semantic query optimization for objectoriented databases is considered. In [19,22] the authors, as in our work, consider query optimization for typed RDF graphs. These works are mainly oriented towards schema violations.…”

Section: Related Workmentioning

confidence: 99%

Selectivity Estimation for SPARQL Triple Patterns with Shape Expressions

Abbas

Genevès

Roisin

et al. 2018

Lecture Notes in Computer Science

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ShEx (Shape Expressions) is a language for expressing constraints on RDF graphs. In this work we optimize the evaluation of conjunctive SPARQL queries, on RDF graphs, by taking advantage of ShEx constraints. Our optimization is based on computing and assigning ranks to query triple patterns, dictating their order of execution. We first define a set of well formed ShEx schemas, that possess interesting characteristics for SPARQL query optimization. We then define our optimization method by exploiting information extracted from a ShEx schema. We finally report on evaluation results performed showing the advantages of applying our optimization on the top of an existing state-of-the-art query evaluation system.

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Section: Related Workmentioning

confidence: 99%

Selectivity Estimation for SPARQL Triple Patterns with Shape Expressions

Abbas

Genevès

Roisin

et al. 2018

Lecture Notes in Computer Science

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“…Anyanwu et al [12] propose an extended SPARQL query language called SPARQ2L, which supports subgraph extraction queries. Serfiotis et al [93] study the containment and minimization problems of RDF query fragments using a logic framework that allows to reduce these problems into their relational equivalents. Hartig and Heese [59] propose a SPARQL query graph model and pursue query rewriting based on this model.…”

Section: Storing and Querying Rdf Data Using Relational Rdf Storesmentioning

confidence: 99%

RDFProv: A relational RDF store for querying and managing scientific workflow provenance

Chebotko¹,

Lu²,

Fei³

et al. 2010

Data & Knowledge Engineering

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Provenance metadata has become increasingly important to support scientific discovery reproducibility, result interpretation, and problem diagnosis in scientific workflow environments. The provenance management problem concerns the efficiency and effectiveness of the modeling, recording, representation, integration, storage, and querying of provenance metadata. Our approach to provenance management seamlessly integrates the interoperability, extensibility, and inference advantages of Semantic Web technologies with the storage and querying power of an RDBMS to meet the emerging requirements of scientific workflow provenance management. In this paper, we elaborate on the design of a relational RDF store, called RDFPROV, which is optimized for scientific workflow provenance querying and management. Specifically, we propose: i) two schema mapping algorithms to map an OWL provenance ontology to a relational database schema that is optimized for common provenance queries; ii) three efficient data mapping algorithms to map provenance RDF metadata to relational data according to the generated relational database schema, and iii) a schema-independent SPARQL-to-SQL translation algorithm that is optimized on-the-fly by using the type information of an instance available from the input provenance ontology and the statistics of the sizes of the tables in the database. Experimental results are presented to show that our algorithms are efficient and scalable. The comparison with two popular relational RDF stores, Jena and Sesame, and two commercial native RDF stores, AllegroGraph and BigOWLIM, showed that our optimizations result in improved performance and scalability for provenance metadata management. Finally, our case study for provenance management in a real-life biological simulation workflow showed the production quality and capability of the RDFPROV system. Although presented in the context of scientific workflow provenance management, many of our proposed techniques apply to general RDF data management as well.

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“…Several works [3], [4], [5], [6], [7], [8], [9] have acknowledged the need for introducing integrity constraints in KBs (and RDF/S KBs in particular). This is motivated by the ongoing discussion about the rule level of the Semantic Web [6], as well as by the need to support various applications, such as semantic interoperability [5], the integration of ontologies with relational databases [4], [8], query optimization [3] and efficient query answering [7], [9].…”

Section: Introductionmentioning

confidence: 99%

“…In particular, we consider DED constraints [16] (disjunctive embedded dependencies), which can capture several inter-esting types of constraints, including constraints mainly used in the relational context, such as primary key and foreign key constraints (used, e.g., in [5]), and constraints used in the RDF/S and ontological context, such as acyclicity and transitivity constraints (as in [3]) and cardinality constraints (used in [4]). In addition, DEDs can be used to detect and resolve invalidities efficiently, using only syntactical manipulations which avoid the need to perform standard (and inefficient) reasoning.…”

Section: Introductionmentioning

confidence: 99%

Formal foundations for RDF/S KB evolution

et al. 2012

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Abstract-There are ongoing efforts to provide declarative formalisms of integrity constraints over RDF/S data. In this context, addressing the evolution of RDF/S knowledge bases while respecting associated constraints is a challenging issue, yet to receive a formal treatment. We provide a theoretical framework for dealing with both schema and data change requests. We define the notion of a rational change operator as one that satisfies the belief revision principles of Success, Validity and Minimal Change. The semantics of such an operator are designed to be subject to customization, by tuning the properties that a rational change should adhere to. We prove some interesting theoretical results and propose a general-purpose algorithm for implementing rational change operators in knowledge bases with integrity constraints, which allows us to handle uniformly any possible change request in a provably rational and consistent manner. Then, we apply our framework to a well-studied RDF/S variant, for which we suggest a specific notion of minimality. For efficiency purposes, we also describe specialized versions of the general evolution algorithm for the RDF/S case, which provably have the same semantics as the general-purpose one for a limited set of (useful in practice) types of change requests.

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Containment and Minimization of RDF/S Query Patterns

Cited by 37 publications

References 14 publications

Selectivity Estimation for SPARQL Triple Patterns with Shape Expressions

Selectivity Estimation for SPARQL Triple Patterns with Shape Expressions

RDFProv: A relational RDF store for querying and managing scientific workflow provenance

Formal foundations for RDF/S KB evolution

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