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Abstract
Introduction
Brief Introduction to RDF and RDFS
Data Model
Construction of XML Results
Storage of RDF Data
RDF Storage in Berkeley Databases
RDF Storage in Object Databases
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Computer Science
Database Systems

RDF Querying: Language Constructs and Evaluation Methods Compared

Profile image of François BryFrançois Bry

2006, Lecture Notes in Computer Science

https://doi.org/10.1007/11837787_1
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54 pages

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Abstract

This article is firstly an introduction into query languages for the Semantic Web, secondly an in-depth comparison of the languages introduced. Only RDF query languages are considered because, as of the writing of this paper, query languages for other Semantic Web data modeling formalisms, especially OWL, are still an open research issue, and only a very small number of, furthermore incomplete, proposals for querying Semantic Web data modeled after other formalisms than RDF exist. The limitation to a few RDF query languages is motivated both by the objective of an in-depth comparison of the languages addressed and by space limitations. During the three years before the writing of this article, more than three dozen proposals for RDF query languages have been published! Not only such a large number, but also the often immature nature of the proposals makes the focus on few, but representative languages a necessary condition for a non-trivial comparison. For this article, the following RDF query languages have been, admittedly subjectively, selected: Firstly, the "relational" or "pattern-based" query languages SPARQL, RQL, TRIPLE, and Xcerpt; secondly the reactive rule query language Algae; thirdly and last the "navigational access" query language Versa. Although subjective, this choice is arguably a good coverage of the diverse language paradigms considered for querying RDF data. It is the authors' hope and expectation, that this comparison will motivate and trigger further similar studies, thus completing the present article and overcoming its limitation. 5 Sections 2 and 3 are shortend versions of corresponding sections of [5]. 7 The same example is used in [5].

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    Jorge Pérez

    ACM Transactions on Database Systems, 2009

    SPARQL is the W3C candidate recommendation query language for RDF. In this paper we address systematically the formal study of SPARQL, concentrating in its graph pattern facility. We consider for this study a fragment without literals and a simple version of filters which encompasses all the main issues yet is simple to formalize. We provide a compositional semantics, prove there are normal forms, prove complexity bounds, among others that the evaluation of SPARQL patterns is PSPACE-complete, compare our semantics to an alternative operational semantics, give simple and natural conditions when both semantics coincide and discuss optimizations procedures.

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    Survey of graph database models
    Renzo Angles

    ACM Computing Surveys, 2008

    Graph database models can be characterized as those where data structures for the schema and instances are modeled as graphs or generalizations of them, and data manipulation is expressed by graph-oriented operations and type constructors. These models flourished in the eighties and early nineties in parallel to object oriented models and their influence gradually faded with the emergence of other database models, particularly the geographical, spatial, semistructured and XML.

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    The Expressive Power of SPARQL
    Renzo Angles

    Lecture Notes in Computer Science, 2008

    This paper studies the expressive power of SPARQL. The main result is that SPARQL and non-recursive safe Datalog with negation have equivalent expressive power, and hence, by classical results, SPARQL is equivalent from an expressive point of view to Relational Algebra. We present explicit generic rules of the transformations in both directions. Among other findings of the paper are the proof that negation can be simulated in SPARQL, that non-safe filters are superfluous, and that current SPARQL W3C semantics can be simplified to a standard compositional one.

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    Rule Interchange on the Web
    Michael Kifer

    Lecture Notes in Computer Science, 2007

    Rules play an increasingly important role in a variety of Semantic Web applications as well as in traditional IT systems. As a universal medium for publishing information, the Web is envisioned to become the place for publishing, distributing, and exchanging rule-based knowledge. Realizing the importance and the promise of this vision, W3C has created the Rule Interchange Format Working Group (RIF WG) and chartered it to develop an interchange format for rules in alignment with the existing standards in the Semantic Web architecture stack.

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    Datalog Relaunched: Simulation Unification and Value Invention
    Clemens Ley

    Lecture Notes in Computer Science, 2011

    For reasoning on the Web, Datalog is lacking data extraction and value invention. This article proposes to overcome these limitations with "simulation unification" and "RDFLog". Simulation unification is a non-standard unification inspired from regular path queries. Like standard unification, it yields bindings for variables in both terms to unify. Unlike standard unification, it does not try to make the two terms identical but instead to embed the query into the data. Simulation unification is decidable. Without variables, it has polynomial complexity. With variables it is, like standard unification, np-complete. We identify a number of interesting special cases of unification, e.g., in presence or absence of term injectivity. In particular, we show that simulation unification without term injectivity on tree data is linear and in presence of injectivity it is still polynomial even on unordered trees in contrast to the np-complete unordered tree inclusion problem. RDFLog is Datalog with arbitrary quantifier alternation: Blank nodes, i.e., existentially quantified variables, in rule heads may be governed by universally quantified variables, universally quantified variables by blank nodes. RDFLog's declarative semantics is defined in terms of RDF entailment; its sound and complete operational semantics, in terms of Skolemization, standard Datalog evaluation, and un-Skolemization. We show that RDFLog limited to ∀ * ∃ * prefixes is (up to unique helper predicates) equivalent to RDFLog with full quantifier alternation. A lightweight implementation points to the efficiency of the approach.

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