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SPARQL-ST: Extending SPARQL to Support Spatiotemporal Queries

  • Matthew PerryEmail author
  • Prateek Jain
  • Amit P. Sheth
Chapter
Part of the Semantic Web and Beyond book series (ADSW, volume 12)

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.

Keywords

Spatial Object Graph Pattern Valid Time Triple Pattern Open Geospatial Consortium 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

We thank Professor T. K. Prasad for his helpful comments on our formalization of SPARQL-ST, and Cory Henson for his comments on a draft of this work. This work is partially funded by NSF-ITRIDM Award #0714441 (SemDIS: Discovering Complex Relationships in the Semantic Web) and by NSF Award #IIS-0842129, titled “III-SGER: Spatio-Temporal-Thematic Queries of Semantic Web Data: a Study of Expressivity and Efficiency (09/01/2008-08/31/2010)”.

References

  1. 1.
    Alia I. Abdelmonty, Philip D. Smart, Christopher B. Jones, Gaihua Fu, and David Finch. A critical evaluation of ontology languages for geographic information retrieval on the internet. Journal of Visual Languages and Computing, 16(4):331–358, 2005.CrossRefGoogle Scholar
  2. 2.
    James F Allen. Maintaining knowledge about temporal intervals. Communications of the ACM, 26(11):832–843, 1983.Google Scholar
  3. 3.
    Kemafor Anyanwu, Angela Maduko, and Amit P. Sheth. SPARQ2L: Towards support for subgraph extraction queries in RDF databases. In 16th International World Wide Web Conference, pages 797–806, Banff, Alberta, Canada, 2007.Google Scholar
  4. 4.
    Dan Brickley and Ramanathan V. Guha. RDF vocabulary description language 1.0: RDF schema. W3C recommendation. http://www.w3.org/tr/rdf-schema/ .
  5. 5.
    Anthony G Cohn, Brandon Bennett, John Gooday, and Nicholas Mark Gotts. Oualitative spatial representation and reasoning with the region connection calculus. GeoInformatica, 1(3): 275–316, 1997.Google Scholar
  6. 6.
    Max J Egenhofer. Toward the semantic geospatial web. In 10th ACM International Symposium on Advances in Geographic Information Systems, pages 1–4, McLean, VA, USA, 2002.Google Scholar
  7. 7.
    Max J Egenhofer and John R Herring. Categorizing binary topological relations between regions, lines, and points in geographic databases. Technical Report 94-1, University of Maine, National Center for Geographic Information and Analysis, 1994.Google Scholar
  8. 8.
    Claudio Gutierrez, Carlos Hurtado, and Alejandro Vaisman. Temporal RDF. In 2nd European Semantic Web Conference, pages 93–107, Heraklion, Crete, Greece, 2005.Google Scholar
  9. 9.
    Claudio Gutierrez, Carlos Hurtado, and Alejandro Vaisman. Introducing time into RDF. IEEE Transactions on Knowledge and Data Engineering, 19(2):207–218, February 2007.CrossRefGoogle Scholar
  10. 10.
    Patrick Hayes. RDF semantics. http://www.w3.org/tr/rdf-mt/ .
  11. 11.
    Hewlett-Packard Development Company. ARQ - a SPARQL processor for jena. http://jena.http://sourceforge.net/arq/ .
  12. 12.
    Jerry Hobbs and Feng Pan. An ontology of time for the semantic web. ACM Transactions on Asian Language Processing (TALIP): Special issue on Temporal Information Processing, 3(1):66–85, 2004.Google Scholar
  13. 13.
    Krys Kochut and Maciej Janik. SPARQLeR: Extended SPARQL for semantic association discovery. In 4th European Semantic Web Conference, pages 145–159, Innsbruck, Austria, 2007.Google Scholar
  14. 14.
    David Kolas, John Hebeler, and Mike Dean. Geospatial semantic web: Architecture of ontologies. In 1st International Conference on GeoSpatial Semantics, pages 183–194, Mexico City, Mexico, 2005.Google Scholar
  15. 15.
    David Kolas and Troy Self. Spatially-augmented knowledgebase. In 6th International Semantic Web Conference, pages 792–801, Busan, South Korea, 2007.Google Scholar
  16. 16.
    Manolis Koubarakis and Kostis Kyzirakos. Modeling and Querying Metadata in the Semantic Sensor Web: the model strdf and the query language stsparql. In Lora Aroyo, Grigoris Antoniou, Eero Hyvönen, Annette ten Teije, Heiner Stuckenschmidt, Liliana Cabral, and Tania Tudorache, editors, Proceedings of the 7th Extended Semantic Web Conference (ESWC2010), Heraklion, Crete, Greece, May 30 - June 3, 2010, Proceedings, Part I, volume 6088 of Lecture Notes in Computer Science. Springer, June 2010.Google Scholar
  17. 17.
    Joshua Lieberman. W3C geospatial incubator group. http://www.w3.org/2005/incubator/geo/ .
  18. 18.
    Open Geospatial Consortium. Open geospatial consortium geospatial semantic web interoperability experiment. http://www.opengeospatial.org/projects/initiatives/gswie .
  19. 19.
    Jorge Perez, Marcelo Arenas, and Claudio Gutierrez. Semantics and complexity of SPARQL. In 5th International Semantic Web Conference, pages 30–43, Athens, GA, USA, 2006.Google Scholar
  20. 20.
    Matthew Perry. Tontogen: A synthetic data set generator for semantic web applications. AIS SIGSEMIS Bulletin, 2(2):46–48, 2005.Google Scholar
  21. 21.
    Matthew Perry, Farshad Hakimpour, and Amit Sheth. Analyzing theme, space and time: An ontology-based approach. In 14th ACM International Symposium on Geographic Information Systems, pages 147–154, Arlington, VA, USA, 2006.Google Scholar
  22. 22.
    Matthew Perry, Amit P. Sheth, Farshad Hakimpour, and Prateek Jain. Supporting complex thematic, spatial and temporal queries over semantic web data. In 2nd International Conference on Geospatial Semantics, pages 228–246, Mexico City, Mexico, 2007.Google Scholar
  23. 23.
    Eric Prud’hommeaux and Andy Seaborne. SPARQL query language for RDF, W3C recommendation. http://www.w3.org/tr/rdf-sparql-query/ .
  24. 24.
    Andrea Pugliese, Octavian Udrea, and V S Subrahmanian. Scaling RDF with time. In 17th International World Wide Web Conference, pages 605–614, Beijing, China, 2008.Google Scholar
  25. 25.
    Wolf Siberski, Jeff Z. Pan, and Uwe Thaden. Querying the semantic web with preferences. In 5th International Semantic Web Conference, pages 612–624, Athens, GA, USA, 2006.Google Scholar
  26. 26.
    Raj Singh, Andrew Turner, Mikel Maron, and Allan Doyle. GeoRSS: Geographically encoded objects for RSS feeds. http://georss.org/gml .
  27. 27.
    Philip D. Smart, Alia I. Abdelmonty, Baher A. El-Geresy, and Christopher B. Jones. A framework for combining rules and geo-ontologies. In 1st International Conference on Web Reasoning and Rule Systems, pages 133–147, Innsbruck, Austria, 2007.Google Scholar
  28. 28.
    Yannis Theoharis, Vassilis Christophides, and Gregory Karvounarakis. Benchmarking database representations of RDF/S stores. In 5th International Semantic Web Conference, pages 685–701, Galway, Ireland, 2005.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.OracleNashuaUSA

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