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gst-store: Querying Large Spatiotemporal RDF Graphs.

Authors :
Dong Wang
Lei Zou
Dongyan Zhao
Source :
Data & Information Management. Dec2017, Vol. 1 Issue 2, p84-103. 20p.
Publication Year :
2017

Abstract

The Simple Protocol and RDF Query Language (SPARQL) query language allows users to issue a structural query over a resource description framework (RDF) graph. However, the lack of a spatiotemporal query language limits the usage of RDF data in spatiotemporal-oriented applications. As the spatiotemporal information continuously increases in RDF data, it is necessary to design an effective and efficient spatiotemporal RDF data management system. In this paper, we formally define the spatiotemporal information-integrated RDF data, introduce a spatiotemporal query language that extends the SPARQL language with spatiotemporal assertions to query spatiotemporal information-integrated RDF data, and design a novel index and the corresponding query algorithm. The experimental results on a large, real RDF graph integrating spatial and temporal information (> 180 million triples) confirm the superiority of our approach. In contrast to its competitors, gst-store outperforms by more than 20%-30% in most cases. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
25439251
Volume :
1
Issue :
2
Database :
Academic Search Index
Journal :
Data & Information Management
Publication Type :
Academic Journal
Accession number :
129346506
Full Text :
https://doi.org/10.1515/dim-2017-0008