Geo-Store: a spatially-augmented SPARQL query evaluation system

Authors:
Chih-Jye Wang;Wei-Shinn Ku;Haiquan Chen
Affiliations:
Auburn University, Auburn, AL;Auburn University, Auburn, AL;Valdosta State University, Valdosta, GA
Venue:
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
Year:
2012

Citing 3
Cited 0

Hexastore: sextuple indexing for semantic web data management

Proceedings of the VLDB Endowment
The RDF-3X engine for scalable management of RDF data

The VLDB Journal — The International Journal on Very Large Data Bases
Deep integration of spatial query processing into native RDF triple stores

Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

The techniques of utilizing spatial data on the Semantic Web have attracted more and more interest from researchers due to the rapidly increasing applications based on geographic information. However, there are currently limited solutions providing efficient spatial query evaluation based on Semantic Web data. In this demonstration, we present Geo-Store, a novel spatially-augmented SPARQL evaluation system. By extending the standard SPARQL query language with spatial query filters, Geo-Store is able to process complex spatial queries with common spatial constraints. These spatial filters are designed based on our Spatially Aware Mapping (SAM) scheme. With SAM, spatial data are pre-processed and encoded with their Hilbert values by employing the Hilbert curve, resulting in more efficient spatial query processing than the existing approaches. The Geo-Store demonstration includes both a server and a web browser-based client.