Geospatial Knowledge Discovery Using Semantic Web Services

  • Peisheng ZhaoEmail author
  • Liping Di
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)


Modern-day satellites and other data acquisition systems have collected an overwhelming volume of Earth and space science data. The data are processed and managed by a variety of geographically distributed data providers. NASA’s Earth Observing System (EOS), for instance, has been generating on the average almost 100 gigabytes of imagery per hour for the past decade. It releases over 900 Earth science data products at more than a dozen data centers. It is extremely valuable for innovative scientific researches and decision-making processes to extract useful information and knowledge from these distributed massive volumes of data. A geospatial model in which prior domain expertise is encoded formally as computable algorithms can facilitate knowledge discovery by detecting and interpreting patterns and regularities, discovering classification rules, and inferring causation. With complex spatial and/or temporal dynamics, geospatial knowledge discovery commonly requires a capability beyond that of an individual geospatial model. Specifically, it involves a complex workflow that requires the integration of various geospatial models and distributed multi-disciplinary, multi-source, and multi-scale science data. For example, to predict fire behavior and estimate possible damage, decision makers and firefighters must effectively combine satellite observations, weather data, geographic data, census data, and simulation models from various sources. The best model and the most appropriate data must be selected in order to predict the fire spread in near-real time or real time. Therefore, the interoperability of geospatial models and data is becoming a critical issue for geospatial knowledge discovery.


Geospatial Data Simple Object Access Protocol Business Process Execution Language Open Geospatial Consortium Geography Markup Language 
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.


  1. Beaujardiere, J.: OpenGIS Web Map Server Implementation Specification OGC 06-042. Technical report, Open Geospatial Consortium Inc. (2006)Google Scholar
  2. Cannataro, M. and Comito, C.: A Data Mining Ontology for Grid Programming. In: 1st International Workshop on Semantics in Peer-to-Peer and Grid Computing, pp. 113–134 (2003)Google Scholar
  3. Chandrasekaran, B., Johnson, T. and Benjamins, V.: Ontologies: what are they? why do we need them? IEEE Intelligent Systems and Their Applications 14, 20–26 (1999)CrossRefGoogle Scholar
  4. Durbha, S. and King, R.: Knowledge mining in earth observation data archives: a domain ontology perspective. In: 2004 IEEE International Geoscience and Remote Sensing Symposium (2004)Google Scholar
  5. Egenhofer, M.: Toward the semantic geospatial web. In: 10th ACM International Symposium on Advances in Geographic Information Systems, pp. 1–4 (2002)Google Scholar
  6. Hwang, S.: Using formal ontology for integrated spatial data mining. In: International Conference on Computational Science and Its Applications, pp. 1026–1035, Springer-Verlag, New York (2004)Google Scholar
  7. ISO/TC211: ISO 19119:2005 Geographic Information – Services. Technical report (2005)Google Scholar
  8. Lieberman, J., Pehle, T. and Dean, M.: Semantic evolution of geospatial web services. In: W3C Workshop on Frameworks for Semantic in Web Services. The World Wide Web Consortium (W3C) (2005)Google Scholar
  9. McIlraith, S., Son, T. and Zeng, H.: Semantic Web services. IEEE Intelligent Systems 16, 46–53 (2001)Google Scholar
  10. Na, A. and Priest, M.: Sensor Observation Service OGC 06-009r6. Technical report, Open Geospatial Consortium Inc. (2007)Google Scholar
  11. Nebert, D., Whiteside, A. and Vretanos, P.: OpenGIS Catalogue Services Specification OGC 07-006r1. Technical report (2007)Google Scholar
  12. Raskin, R.: Enableing Semantic Interoperability for Earth Science Data. Technical report, NASA JPL (2004)Google Scholar
  13. Schut, P.: OpenGIS Web Processing Service OGC 05-007r7. Technical report, Open Geospatial Consortium Inc. (2007)Google Scholar
  14. Simonis, I.: OpenGIS Sensor Planning Service Implementation Specification OGC 07-014r3. Technical report, Open Geospatial Consortium Inc. (2005)Google Scholar
  15. Vowles, G.: Geospatial Digital Rights Management Reference Model OGC 06-004r3. Technical report (2006)Google Scholar
  16. Vretanos, P.: Web Feature Service Implementation Specification OGC 04-094. Technical report, Open Geospatial Consortium Inc. (2005)Google Scholar
  17. Web Service Architecture,
  18. Whiteside, A. and Evans, J.: Web Coverage Service (WCS) Implementation Standard OGC 07-067r5. Technical report, Open Geospatial Consortium Inc. (2008)Google Scholar
  19. Zhao, P., Di, L., Yang, W., Yu, G. and Yue, P.: Geospatial semantic web: critical issues. In: H. Karimi (eds.) Encyclopedia of Geoinformatics. Idea Group Publishing, Hershey (2007)Google Scholar
  20. Zhao, P., Di, L., Yue, P., Yu, G. and Yang, W.: Semantic web based geospatial knowledge transformation. Computer & Geosciences 35, 798–208 (2009)Google Scholar
  21. Zhao, P., Yu, G. and Di, L.: Geospatial web services. In: B. Hilton (eds.) Emerging Spatial Information Systems and Applications, pp. 1–35. Idea Group Publishing, Hershey (2006)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  1. 1.Center for Spatial Information Science and Systems (CSISS), George Mason UniversityGreenbeltUSA

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