Tracking Dynamics of Geospatial Phenomena in Distributed and Heterogeneous Environments Using Scientific Workflow and Web Services Technologies

We propose to use W3C Web services and recently emerging scientific workflow technologies for geospatial data processing in distributed and heterogeneous computation environments. The Web service technology provides platform independence and greater interoperability; the scientific workflow technology provides software reuse and visual programming. We demonstrate the feasibility of the proposed approach using storm dynamics tracking from weather radar data as an example. Technical details of algorithm development, Web services publishing, workflow composition and execution for the demonstrative example are discussed

[1]  Jan M. H. Hendrickx,et al.  GIS-based NEXRAD Stage III precipitation database: automated approaches for data processing and visualization , 2005, Comput. Geosci..

[2]  Matthew R. Pocock,et al.  Taverna: a tool for the composition and enactment of bioinformatics workflows , 2004, Bioinform..

[3]  Max J. Egenhofer,et al.  Spatial and temporal reasoning in geographic information systems , 1998 .

[4]  Martien Molenaar,et al.  Diachronic Analysis of Fuzzy Objects , 1999, GeoInformatica.

[5]  Ian J. Taylor,et al.  Distributed computing with Triana on the Grid , 2005, Concurr. Pract. Exp..

[6]  Jianting Zhang,et al.  Using Web Services and Scientific Workflow for Species Distribution Prediction Modeling , 2005, WAIM.

[7]  Tom Rink,et al.  Java distributed components for numerical visualization in VisAD , 2002, CACM.

[8]  Geoffrey C. Fox,et al.  Proceedings of the 4th international conference on Grid and Cooperative Computing , 2005 .

[9]  Sara J. Graves,et al.  Towards Dynamically Adaptive Weather Analysis and Forecasting in LEAD , 2005, International Conference on Computational Science.

[10]  M. Yuan.  Representing Complex Geographic Phenomena in GIS , 2001 .

[11]  Edward A. Lee,et al.  Scientific workflow management and the Kepler system , 2006, Concurr. Comput. Pract. Exp..

[12]  Kaizhong Zhang,et al.  Approximate tree pattern matching , 1997 .

[13]  Yogesh L. Simmhan,et al.  Building Grid Portal Applications From a Web Service Component Architecture , 2005, Proceedings of the IEEE.

[14]  Geoffrey M. Davis,et al.  NetCDF User''s Guide for C , 1997 .

[15]  Bertram Ludäscher,et al.  A Scientific Workflow Approach to Distributed Geospatial Data Processing using Web Services , 2005, SSDBM.

[16]  Max J. Egenhofer,et al.  Identity-based change: a foundation for spatio-temporal knowledge representation , 2000, Int. J. Geogr. Inf. Sci..

[17]  C. Cartalis,et al.  Application of an automated cloud‐tracking algorithm on satellite imagery for tracking and monitoring small mesoscale convective cloud systems , 2005 .

[18]  David S. Burggraf,et al.  Geography Mark-Up Language: Foundation for the Geo-Web , 2004 .