Spatial and temporal data is plentiful on the Web, and Semantic Web technologies have the potential to make this data more accessible and more useful. Semantic Web researchers have consequently made progress towards better handling of spatial and temporal data.SPARQL, the W3C-recommended query language for RDF, does not adequately support complex spatial and temporal queries. In this work, we present the SPARQL-ST query language. SPARQL-ST is an extension of SPARQL for complex spatiotemporal queries. We present a formal syntax and semantics for SPARQL-ST. In addition, we describe a prototype implementation of SPARQL-ST and demonstrate the scalability of this implementation with a performance study using large real-world and synthetic RDF datasets.
%0 Book Section
%1 PerryJainSheth11p61
%A Perry, Matthew
%A Jain, Prateek
%A Sheth, Amit P.
%B Geospatial Semantics and the Semantic Web
%C New York
%D 2011
%E Ashish, Naveen
%E Sheth, Amit P.
%I Springer
%K 01614 springer paper ai semantic web spatial temporal knowledge processing location rdf zzz.sw
%N 12
%P 61--86
%R 10.1007/978-1-4419-9446-2_3
%T SPARQL-ST: Extending SPARQL to Support Spatiotemporal Queries
%X Spatial and temporal data is plentiful on the Web, and Semantic Web technologies have the potential to make this data more accessible and more useful. Semantic Web researchers have consequently made progress towards better handling of spatial and temporal data.SPARQL, the W3C-recommended query language for RDF, does not adequately support complex spatial and temporal queries. In this work, we present the SPARQL-ST query language. SPARQL-ST is an extension of SPARQL for complex spatiotemporal queries. We present a formal syntax and semantics for SPARQL-ST. In addition, we describe a prototype implementation of SPARQL-ST and demonstrate the scalability of this implementation with a performance study using large real-world and synthetic RDF datasets.
%& 3
@incollection{PerryJainSheth11p61,
abstract = {Spatial and temporal data is plentiful on the Web, and Semantic Web technologies have the potential to make this data more accessible and more useful. Semantic Web researchers have consequently made progress towards better handling of spatial and temporal {data.SPARQL}, the {W3C-recommended} query language for {RDF}, does not adequately support complex spatial and temporal queries. In this work, we present the {SPARQL-ST} query language. {SPARQL-ST} is an extension of {SPARQL} for complex spatiotemporal queries. We present a formal syntax and semantics for {SPARQL-ST.} In addition, we describe a prototype implementation of {SPARQL-ST} and demonstrate the scalability of this implementation with a performance study using large real-world and synthetic {RDF} datasets.},
added-at = {2016-05-26T20:26:04.000+0200},
address = {New York},
author = {Perry, Matthew and Jain, Prateek and Sheth, Amit P.},
biburl = {https://www.bibsonomy.org/bibtex/24456e89232060f0df358a6df92f2627f/flint63},
booktitle = {Geospatial Semantics and the Semantic Web},
chapter = 3,
crossref = {AshishSheth2011},
doi = {10.1007/978-1-4419-9446-2_3},
editor = {Ashish, Naveen and Sheth, Amit P.},
file = {Springer4Pro:2011/PerryJainSheth11p61.pdf:PDF},
groups = {public},
interhash = {d975c56842fc18440e525748364b4527},
intrahash = {4456e89232060f0df358a6df92f2627f},
keywords = {01614 springer paper ai semantic web spatial temporal knowledge processing location rdf zzz.sw},
number = 12,
pages = {61--86},
publisher = {Springer},
series = {Semantic Web and Beyond},
timestamp = {2018-04-16T12:02:16.000+0200},
title = {{SPARQL-ST:} Extending {SPARQL} to Support Spatiotemporal Queries},
username = {flint63},
year = 2011
}