Abstract
The Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) initiative enables access of sensor data over the Web. The growing amount of available sensors requires discovering mechanisms to find sensor services relevant for users. These mechanisms must rely on explicit sensor metadata model and address the problem of semantic heterogeneity. We present a new discovering approach that is based on a novel sensor metadata model compliant with SWE standards, where sensors’ descriptions are referenced to a common semantic reference frame to support resolution of semantic heterogeneities. The discovery mechanism comprises two steps: first, a network-analysis-based partitioning algorithm modularizes the set of sensors into meaningful sensor clusters, which semantics is generated with aggregation operators. Secondly, an expanded SQWRL rule-based inference engine processes the queries over the sensor clusters and issues the relevant sensor services. This approach allows users to find the sensor services relevant to their needs.
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Bakillah, M., Liang, S.H.L. (2012). Discovering Sensor Services with Social Network Analysis and Expanded SQWRL Querying. In: Di Martino, S., Peron, A., Tezuka, T. (eds) Web and Wireless Geographical Information Systems. W2GIS 2012. Lecture Notes in Computer Science, vol 7236. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29247-7_16
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DOI: https://doi.org/10.1007/978-3-642-29247-7_16
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