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Enabling Query Technologies for the Semantic Sensor Web

Author

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  • Jean-Paul Calbimonte

    (Universidad Politécnica de Madrid, Spain)

  • Hoyoung Jeung

    (SAP Research, Australia)

  • Oscar Corcho

    (Universidad Politécnica de Madrid, Spain)

  • Karl Aberer

    (Ecole Polytechnique Fédérale de Lausanne, Switzerland)

Abstract

Sensor networks are increasingly being deployed in the environment for many different purposes. The observations that they produce are made available with heterogeneous schemas, vocabularies and data formats, making it difficult to share and reuse this data, for other purposes than those for which they were originally set up. The authors propose an ontology-based approach for providing data access and query capabilities to streaming data sources, allowing users to express their needs at a conceptual level, independent of implementation and language-specific details. In this article, the authors describe the theoretical foundations and technologies that enable exposing semantically enriched sensor metadata, and querying sensor observations through SPARQL extensions, using query rewriting and data translation techniques according to mapping languages, and managing both pull and push delivery modes.

Suggested Citation

  • Jean-Paul Calbimonte & Hoyoung Jeung & Oscar Corcho & Karl Aberer, 2012. "Enabling Query Technologies for the Semantic Sensor Web," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global, vol. 8(1), pages 43-63, January.
    • Handle: RePEc:igg:jswis0:v:8:y:2012:i:1:p:43-63
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    Cited by:

    1. Huayou Si & Yajie Qi & Meilian Zheng & Yongjian Ren & Lifeng Yu, 2018. "Structured peer-to-peer-based publication and sharing of ontologies to automatically process SPARQL query on a semantic sensor network," International Journal of Distributed Sensor Networks, , vol. 14(10), pages 15501477187, October.

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