Sharing geoscience algorithms in a Web service-oriented environment (GRASS GIS example)

  • Authors:

  • Xiaoyan Li;Liping Di;Weiguo Han;Peisheng Zhao;Upendra Dadi

  • Affiliations:

  • Center for Spatial Information Science and Systems (CSISS), George Mason University, 10517 Braddock Rd, Fairfax, VA 22032, USA;Center for Spatial Information Science and Systems (CSISS), George Mason University, 10517 Braddock Rd, Fairfax, VA 22032, USA;Center for Spatial Information Science and Systems (CSISS), George Mason University, 10517 Braddock Rd, Fairfax, VA 22032, USA;Center for Spatial Information Science and Systems (CSISS), George Mason University, 10517 Braddock Rd, Fairfax, VA 22032, USA;Center for Spatial Information Science and Systems (CSISS), George Mason University, 10517 Braddock Rd, Fairfax, VA 22032, USA

  • Venue:
  • Computers & Geosciences
  • Year:
  • 2010

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Abstract

Effective use of the large amounts of geospatial data available for geospatial research and applications is needed. In this paper, the emerging SOAP-based Web service technologies have been used to develop a large number of standard compliant, chainable geospatial Web services, using existing geospatial modules in software systems or specific geoscientific algorithms. A prototype for wrapping legacy software modules or geoscientific algorithms into loosely coupled Web services is proposed from an implementation viewpoint. Module development for Web services adheres to the Open GIS Consortium (OGC) geospatial implementation and the World Wide Web consortium (W3C) standards. The Web service interfaces are designed using Web Services Description Language (WSDL) documents. This paper presents how the granularity of an individual existing geospatial service module used by other geoscientific workflows is decided. A treatment of concurrence processes and clustered deployment of Web services is used to overcome multi-user access and network speed limit problems. This endeavor should allow extensive use of geoscientific algorithms and geospatial data.