21 July 2017 Ontology-based knowledge representation for resolution of semantic heterogeneity in GIS
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Proceedings Volume 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017); 104204Z (2017) https://doi.org/10.1117/12.2281985
Event: Ninth International Conference on Digital Image Processing (ICDIP 2017), 2017, Hong Kong, China
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.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ying Liu, Ying Liu, Han Xiao, Han Xiao, Limin Wang, Limin Wang, Jialing Han, Jialing Han, } "Ontology-based knowledge representation for resolution of semantic heterogeneity in GIS", Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 104204Z (21 July 2017); doi: 10.1117/12.2281985; https://doi.org/10.1117/12.2281985
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