Framework for Spatial Query Resolution for Decision Support Using Geospatial Service Chaining and Fuzzy Reasoning

  • Jayeeta Mukherjee
  • Indira Mukherjee
  • Soumya Kanti Ghosh
Part of the Communications in Computer and Information Science book series (CCIS, volume 141)


Geospatial data play a vital role in various decision making systems. Technological advancements have enabled users to access geospatial functionalities as services over web. In many decision support systems, it is required that more than one service is to be involved to help decision makers, calling for a service chaining. Chaining distributed geospatial services requires dealing with several heterogeneity issues such as semantic, syntactic issues. In addition, properties of geospatial data are fuzzy by nature. The fuzziness may exist in thematic definition and in spatial properties. This may lead to inflexible, less accurate decision making. Thus, to avail more accurate decision making, the uncertainty associated with the spatial information should be captured. In this paper, an approach for service chaining in decision support systems has been taken, along with fuzzy logic to resolve user queries and process imprecise information. Service chaining has been used for integrating distributed geospatial services, and fuzzy logic has been incorporated with services to capture fuzziness and uncertainty that are intrinsic to the data.


Decision Support System Description Logic Service Discovery Service Description Geospatial Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Aditya, T., Lemmens, R.: Chaining distributed gis services. In: Prosiding Pertemuan Ilmiah Tahunan XII (2003)Google Scholar
  2. 2.
    Mark, D.: Toward a Theoretical Framework for Geographic Entity Types. In: Spatial Information Theory. Springer, Heidelberg (1993)Google Scholar
  3. 3.
    Alameh, N.: Service chaining of interoperable geographic information web services (2010), (accessed on June 2)
  4. 4.
    Alameh, N.: Chaining geographic information web services. In: Internet Computing. IEEE, Los Alamitos (2003)Google Scholar
  5. 5.
    Lemmens, R., Wytzisk, A., de By, R., Granell, C., Gould, M., van Oosterom, P.: Integrating semantic and syntactic descriptions to chain geographic services. In: Internet Computing, vol. 10, pp. 42–52. IEEE, Los Alamitos (2006)Google Scholar
  6. 6.
    Lemmens, R., de By, R., Gould, M., Wytzisk, A., Granell, C., van Oosterom, P.: Enhancing geo-service chaining through deep service descriptions. Transactions in GIS 11(6), 849–871 (2007)CrossRefGoogle Scholar
  7. 7.
    Visser, U., Stuckenschmidt, H.: Interoperability in gis – enabling technologies. In: Ruiz, M., Gould M., Ramon, J. (eds.) 5th AGILE Conference on Geographic Information Science, pp. 291–297 (2002)Google Scholar
  8. 8.
    Lutz, M., Sprado, J., Klien, E., Schubert, C., Christ, I.: Overcoming semantic heterogeneity in spatial data infrastructures. Computers & Geosciences 35(4), 732–752 (2009)CrossRefGoogle Scholar
  9. 9.
    Di, L., Yue, P., Yang, W., Yu, G., Zhao, P., Wei, Y.: Ontology-supported automatic service chaining for geospatial knowledge discovery. In: American Society of Photogrammetry and Remote Sensing (2007)Google Scholar
  10. 10.
    Sozer, A., Yazici, A., Oguztuzun, H., Tas, O.: Modeling and querying fuzzy spatiotemporal databases. Information Sciences 178(19), 3665–3682 (2008)CrossRefGoogle Scholar
  11. 11.
    Worboys, M.: Imprecision in finite resolution spatial data. GeoInformatica 2(3), 257–279 (1998)CrossRefGoogle Scholar
  12. 12.
    Sicilia, M., Mastorakis, N.: Extending uml 1.5 for fuzzy conceptual modeling: A strictly additive approach. WSEAS Transaction on Systems 3, 2234–2239 (2004)Google Scholar
  13. 13.
    Ma, Z.M., Yan, L.: Fuzzy xml data modeling with the uml and relational data models. Journal of Data & Knowledge Engineering 63, 972–996 (2007)CrossRefGoogle Scholar
  14. 14.
    Zadeh, L.: Fuzzy sets. Information and Control 8, 338–353 (1963)MathSciNetCrossRefzbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Jayeeta Mukherjee
    • 1
  • Indira Mukherjee
    • 1
  • Soumya Kanti Ghosh
    • 1
  1. 1.School of Information TechnologyIndian Institute of TechnologyKharagpurIndia

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