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Proceedings Paper

Ontology-based knowledge representation for resolution of semantic heterogeneity in GIS
Author(s): Ying Liu; Han Xiao; Limin Wang; Jialing Han
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Paper Abstract

Lack of semantic interoperability in geographical information systems has been identified as the main obstacle for data sharing and database integration. The new method should be found to overcome the problems of semantic heterogeneity. Ontologies are considered to be one approach to support geographic information sharing. This paper presents an ontology-driven integration approach to help in detecting and possibly resolving semantic conflicts. Its originality is that each data source participating in the integration process contains an ontology that defines the meaning of its own data. This approach ensures the automation of the integration through regulation of semantic integration algorithm. Finally, land classification in field GIS is described as the example.

Paper Details

Date Published: 21 July 2017
PDF: 7 pages
Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 104204Z (21 July 2017); doi: 10.1117/12.2281985
Show Author Affiliations
Ying Liu, Jilin Univ. of Finance and Economics (China)
Han Xiao, Jilin Univ. (China)
Limin Wang, Jilin Univ. of Finance and Economics (China)
Jialing Han, Jilin Univ. of Finance and Economics (China)


Published in SPIE Proceedings Vol. 10420:
Ninth International Conference on Digital Image Processing (ICDIP 2017)
Charles M. Falco; Xudong Jiang, Editor(s)

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