S. Schenk. KI 2007: Advances in Artificial Intelligence, volume 4667 of Lecture Notes in Computer Science, page 160--174. Springer Berlin / Heidelberg, (2007)
DOI: 10.1007/978-3-540-74565-5_14
Abstract
SPARQL is the upcoming W3C standard query language for RDF data in the semantic web. In this paper we propose a formal semantics for SPARQL based on datalog. A mapping of SPARQL to datalog allows to easily reuse existing results from logics for analysis and extensions of SPARQL. Using this semantics we analyse the complexity of query answering in SPAQRL and propose two useful extensions to SPARQL, namely binding of variables to results of filter expressions and views on RDF graphs as datasets for queries. We show that these extensions to not add to the overall complexity of SPARQL.
%0 Conference Paper
%1 Schenk2007
%A Schenk, Simon
%B KI 2007: Advances in Artificial Intelligence
%D 2007
%I Springer Berlin / Heidelberg
%K InformationIntegration datalog semantics sparql
%P 160--174
%R 10.1007/978-3-540-74565-5_14
%T A SPARQL Semantics Based on Datalog
%U http://www.springerlink.com/content/9608038906030121/
%V 4667
%X SPARQL is the upcoming W3C standard query language for RDF data in the semantic web. In this paper we propose a formal semantics for SPARQL based on datalog. A mapping of SPARQL to datalog allows to easily reuse existing results from logics for analysis and extensions of SPARQL. Using this semantics we analyse the complexity of query answering in SPAQRL and propose two useful extensions to SPARQL, namely binding of variables to results of filter expressions and views on RDF graphs as datasets for queries. We show that these extensions to not add to the overall complexity of SPARQL.
%@ 978-3-540-74564-8
@inproceedings{Schenk2007,
abstract = {SPARQL is the upcoming W3C standard query language for RDF data in the semantic web. In this paper we propose a formal semantics for SPARQL based on datalog. A mapping of SPARQL to datalog allows to easily reuse existing results from logics for analysis and extensions of SPARQL. Using this semantics we analyse the complexity of query answering in SPAQRL and propose two useful extensions to SPARQL, namely binding of variables to results of filter expressions and views on RDF graphs as datasets for queries. We show that these extensions to not add to the overall complexity of SPARQL.},
added-at = {2010-01-29T19:11:27.000+0100},
author = {Schenk, Simon},
biburl = {https://www.bibsonomy.org/bibtex/29ec92725dee90f00af034decff99f6a6/alexjdl},
booktitle = {{KI} 2007: Advances in Artificial Intelligence},
doi = {10.1007/978-3-540-74565-5_14},
interhash = {cbaa2f71dd4ff2f803f53ced84f9db6c},
intrahash = {9ec92725dee90f00af034decff99f6a6},
isbn = {978-3-540-74564-8},
issn = {0302-9743 (Print) 1611-3349 (Online)},
keywords = {InformationIntegration datalog semantics sparql},
pages = {160--174},
publisher = {Springer Berlin / Heidelberg},
series = {Lecture Notes in Computer Science},
subject_collection = {Computer Science},
timestamp = {2010-01-29T19:11:27.000+0100},
title = {A {SPARQL} Semantics Based on Datalog},
url = {http://www.springerlink.com/content/9608038906030121/},
volume = 4667,
year = 2007
}