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Standards-Based Middleware and Tools for Coastal Sensor Web Applications

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5 Author(s)
Surya S. Durbha ; Department of Electrical and Computer Engineering, Center for Advanced Vehicular Systems (CAVS), Mississippi State University, ; Roger L. King ; Santhosh K. Amanchi ; Shruthi Bheemireddy
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Coastal buoys and stations provide frequent, high quality marine observations for oceanographic study, weather service, atmospheric, and public safety. There is a great need for sharing the generated data sets to enable timely decision-making across various agencies/institutions. However, this requires tremendous efforts and coordination among different sensor network agencies to come to a shared understanding for disseminating the information in a uniform and standardized way. To address these needs and achieve interoperability, syntactic standardization provides to a certain extent the data description models. In addition, semantic enrichment of the information sources is also required to understand the context of the data. In this paper we adopt standardized data models based on the Open Geospatial Consoritum (OGC) sensor web enablement framework for coastal sensor networks, which facilitates improved information retrieval on a variety of spatio-temporal scales. The semantic enrichment is achieved in terms of conceptualization of selected sensor types and other terminology involved in the coastal domain in the form of Ontologies. A coastal semantic mapping (COSEM-Map) tool developed as a part of this work facilitates the harmonization of different representations. This ontological model is amenable to querying using SPARQL, which is a standardized RDF query language. Further, sensor web services discovery aspects have been addressed by augmenting the Universal Description, discovery and Integration (UDDI) registry with Web Ontology Language for Services (OWL-S) and using a semantic matching algorithm for services discovery. Both web-based and mobile-enabled clients were developed to process syntactic and semantic queries.

Published in:

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  (Volume:3 ,  Issue: 4 )