
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.
Databases and Information Systems, Bioinformatics, OS and Networks, Open Geospatial Consortium, Temporal Selection, Temporal Join, Social and Behavioral Sciences, Spatio-Temporal Filter, Science and Technology Studies, Spatial Selection, Spatial Object, Spatial Join, Physical Sciences and Mathematics, Triple Pattern, Computer Engineering, Spatio-Temporal Semantic Web, Spatio-Temporal Query, SPARQL-ST, Spatial Filter, Computer Sciences, Communication, Life Sciences, Valid Time, 006, Graph Pattern, Electrical and Computer Engineering, 004, Communication Technology and New Media, Temporal Filter
Databases and Information Systems, Bioinformatics, OS and Networks, Open Geospatial Consortium, Temporal Selection, Temporal Join, Social and Behavioral Sciences, Spatio-Temporal Filter, Science and Technology Studies, Spatial Selection, Spatial Object, Spatial Join, Physical Sciences and Mathematics, Triple Pattern, Computer Engineering, Spatio-Temporal Semantic Web, Spatio-Temporal Query, SPARQL-ST, Spatial Filter, Computer Sciences, Communication, Life Sciences, Valid Time, 006, Graph Pattern, Electrical and Computer Engineering, 004, Communication Technology and New Media, Temporal Filter
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