Overcoming Geoinformatic Knowledge Fence: An Exploratory of Intelligent Geospatial Data Preparation within Spatial Analysis

  • Authors:
  • Jian Wang;Chun-Jiang Zhao;Fang-Qu Niu;Zhi-Qiang Wang

  • Affiliations:
  • National Engineering Research Center for Information Technology in Agriculture (NERCITA), Beijing, China 100097;National Engineering Research Center for Information Technology in Agriculture (NERCITA), Beijing, China 100097;Institute of Geography Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China 100060;Institute of Geography Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China 100060

  • Venue:
  • ICCS 2009 Proceedings of the 9th International Conference on Computational Science
  • Year:
  • 2009

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Abstract

The booming of earth observation provides decision-makers with more available geospatial data as well as more puzzles about how to understand, evaluate, search, process, and utilize those overwhelming resources. The paper distinguishes a concept termed geoinformatic knowledge fence (GeoKF) to discuss the knowledge-aspect of such puzzles and the approach to overcoming them. Basing on analysis of the gap between common geography sense and geoinformatic professional knowledge, the approach composes analysis space modeling and spatial reasoning to match decision models to the online geospatial data sources they need. Such approach enables automatically and intelligently searching of suitable geospatial data resources and calculating their suitability to given spatial decision and analysis. An experiment with geo-services, geo-ontology and rule-based reasoning (Jess) is developed to illustrate the feasibility of the approach in scenario of data preparation within decisions of bird flu control.