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Semantic Web Services-based process planning for earth science applications

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Abstract:

In a Web service-based distributed environment, individual services must be chained together dynamically to solve a complex real world problem. The Semantic Web Service has shown promise for automatic chaining of Web services. This paper addresses semi-automatic geospatial service chaining through Semantic Web Services-based process planning. Process planning includes three phases: process modeling, process model instantiation and workflow execution. Ontologies and Artificial Intelligence (AI) planning methods are employed in process planning to help a user dynamically create an executable workflow for earth science applications. In particular, the approach was implemented in a common data and service environment enabled by interoperable standards from OGC and W3C. A case study of the chaining process for wildfire prediction illustrates the applicability of this approach.

Keywords: AI planning; Geospatial web service; Ontology; Semantics; Service chain; Service composition

Document Type: Research Article

DOI: https://doi.org/10.1080/13658810802032680

Affiliations: 1: Center for Spatial Information Science and Systems (CSISS), George Mason University, Greenbelt, MD 20770, USA,State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China 2: Center for Spatial Information Science and Systems (CSISS), George Mason University, Greenbelt, MD 20770, USA 3: State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China

Publication date: 2009-09-01

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