2,866 research outputs found
Answering SPARQL queries modulo RDF Schema with paths
SPARQL is the standard query language for RDF graphs. In its strict
instantiation, it only offers querying according to the RDF semantics and would
thus ignore the semantics of data expressed with respect to (RDF) schemas or
(OWL) ontologies. Several extensions to SPARQL have been proposed to query RDF
data modulo RDFS, i.e., interpreting the query with RDFS semantics and/or
considering external ontologies. We introduce a general framework which allows
for expressing query answering modulo a particular semantics in an homogeneous
way. In this paper, we discuss extensions of SPARQL that use regular
expressions to navigate RDF graphs and may be used to answer queries
considering RDFS semantics. We also consider their embedding as extensions of
SPARQL. These SPARQL extensions are interpreted within the proposed framework
and their drawbacks are presented. In particular, we show that the PSPARQL
query language, a strict extension of SPARQL offering transitive closure,
allows for answering SPARQL queries modulo RDFS graphs with the same complexity
as SPARQL through a simple transformation of the queries. We also consider
languages which, in addition to paths, provide constraints. In particular, we
present and compare nSPARQL and our proposal CPSPARQL. We show that CPSPARQL is
expressive enough to answer full SPARQL queries modulo RDFS. Finally, we
compare the expressiveness and complexity of both nSPARQL and the corresponding
fragment of CPSPARQL, that we call cpSPARQL. We show that both languages have
the same complexity through cpSPARQL, being a proper extension of SPARQL graph
patterns, is more expressive than nSPARQL.Comment: RR-8394; alkhateeb2003
Using Description Logics for RDF Constraint Checking and Closed-World Recognition
RDF and Description Logics work in an open-world setting where absence of
information is not information about absence. Nevertheless, Description Logic
axioms can be interpreted in a closed-world setting and in this setting they
can be used for both constraint checking and closed-world recognition against
information sources. When the information sources are expressed in well-behaved
RDF or RDFS (i.e., RDF graphs interpreted in the RDF or RDFS semantics) this
constraint checking and closed-world recognition is simple to describe. Further
this constraint checking can be implemented as SPARQL querying and thus
effectively performed.Comment: Extended version of a paper of the same name that will appear in
AAAI-201
Extended RDF: Computability and Complexity Issues
ERDF stable model semantics is a recently proposed semantics for
ERDF ontologies and a faithful extension of RDFS semantics on RDF graphs.
In this paper, we elaborate on the computability and complexity issues of the
ERDF stable model semantics. Based on the undecidability result of ERDF
stable model semantics, decidability under this semantics cannot be achieved,
unless ERDF ontologies of restricted syntax are considered. Therefore, we
propose a slightly modified semantics for ERDF ontologies, called ERDF #n-
stable model semantics. We show that entailment under this semantics is, in
general, decidable and also extends RDFS entailment. Equivalence statements
between the two semantics are provided. Additionally, we provide algorithms
that compute the ERDF #n-stable models of syntax-restricted and general
ERDF ontologies. Further, we provide complexity results for the ERDF #nstable
model semantics on syntax-restricted and general ERDF ontologies.
Finally, we provide complexity results for the ERDF stable model semantics
on syntax-restricted ERDF ontologies
Model Theory and Entailment Rules for RDF Containers, Collections and Reification
An RDF graph is, at its core, just a set of statements consisting of subjects, predicates and objects. Nevertheless, since its inception
practitioners have asked for richer data structures such as containers (for
open lists, sets and bags), collections (for closed lists) and reification (for
quoting and provenance). Though this desire has been addressed in the
RDF primer and RDF Schema specification, they are explicitely ignored
in its model theory. In this paper we formalize the intuitive semantics
(as suggested by the RDF primer, the RDF Schema and RDF semantics specifications) of these compound data structures by two orthogonal
extensions of the RDFS model theory (RDFCC for RDF containers and
collections, and RDFR for RDF reification). Second, we give a set of
entailment rules that is sound and complete for the RDFCC and RDFR
model theories. We show that complexity of RDFCC and RDFR entailment remains the same as that of simple RDF entailment
On Reasoning with RDF Statements about Statements using Singleton Property Triples
The Singleton Property (SP) approach has been proposed for representing and
querying metadata about RDF triples such as provenance, time, location, and
evidence. In this approach, one singleton property is created to uniquely
represent a relationship in a particular context, and in general, generates a
large property hierarchy in the schema. It has become the subject of important
questions from Semantic Web practitioners. Can an existing reasoner recognize
the singleton property triples? And how? If the singleton property triples
describe a data triple, then how can a reasoner infer this data triple from the
singleton property triples? Or would the large property hierarchy affect the
reasoners in some way? We address these questions in this paper and present our
study about the reasoning aspects of the singleton properties. We propose a
simple mechanism to enable existing reasoners to recognize the singleton
property triples, as well as to infer the data triples described by the
singleton property triples. We evaluate the effect of the singleton property
triples in the reasoning processes by comparing the performance on RDF datasets
with and without singleton properties. Our evaluation uses as benchmark the
LUBM datasets and the LUBM-SP datasets derived from LUBM with temporal
information added through singleton properties
Web and Semantic Web Query Languages
A number of techniques have been developed to facilitate
powerful data retrieval on the Web and Semantic Web. Three categories
of Web query languages can be distinguished, according to the format
of the data they can retrieve: XML, RDF and Topic Maps. This article
introduces the spectrum of languages falling into these categories
and summarises their salient aspects. The languages are introduced using
common sample data and query types. Key aspects of the query
languages considered are stressed in a conclusion
Grid Metadata Lifetime Control in ActOn
In the Semantic Grid, metadata, as first class citizens, should be maintained up to-date in a cost-effective manner. This includes maxi missing the automation of different aspects of the metadata lifecycle, managing the evolution and change of metadata in distributed contexts, and synchronizing adequately the evolution of all these related entities. In this paper, we introduce a semantic model and its operations which is designed for supporting dynamic metadata management in Active Ontology (Act On), a semantic information integration approach for highly dynamic information sources. Finally, we illustrate the Act On-based metadata lifetime control by EGEE examples
A General Framework for Representing, Reasoning and Querying with Annotated Semantic Web Data
We describe a generic framework for representing and reasoning with annotated
Semantic Web data, a task becoming more important with the recent increased
amount of inconsistent and non-reliable meta-data on the web. We formalise the
annotated language, the corresponding deductive system and address the query
answering problem. Previous contributions on specific RDF annotation domains
are encompassed by our unified reasoning formalism as we show by instantiating
it on (i) temporal, (ii) fuzzy, and (iii) provenance annotations. Moreover, we
provide a generic method for combining multiple annotation domains allowing to
represent, e.g. temporally-annotated fuzzy RDF. Furthermore, we address the
development of a query language -- AnQL -- that is inspired by SPARQL,
including several features of SPARQL 1.1 (subqueries, aggregates, assignment,
solution modifiers) along with the formal definitions of their semantics
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