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Proceedings Paper

The geographical ontology, LDAP, and the space information semantic grid
Author(s): Wei Cui; Deren Li
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Paper Abstract

The research purpose is to discuss the development trend and theory of the semantic integration and interoperability of Geography Information Systems on the network ages and to point out that the geography ontology is the foregone conclusion of the development of the semantic-based integration and interoperability of Geography Information Systems. After analyzing the effect by using the various new technologies, the paper proposes new idea for the family of the ontology class based on the GIS knowledge built here. They are the basic ontology, the domain ontology and the application ontology and are very useful for the sharing and transferring of the semantic information between the complicated distributed systems and object abstracting. The main contributions of the paper are as follows: 1) For the first time taking the ontology and LDAP (Lightweight Directory Access Protocol) in creating and optimizing the architecture of Spatial Information Gird and accelerating the fusion of Geography Information System and other domain's information systems. 2) For the first time, introducing a hybrid method to build geography ontology. This hybrid method mixes the excellence of the independent domain expert and data mining. It improves the efficiency of the method of the domain expert and builds ontology semi-automatically. 3) For the first time, implementing the many-to-many relationship of integration ontology system by LDAP's reference and creating ontology-based virtual organization that could provide transparent service to guests.

Paper Details

Date Published: 2 December 2005
PDF: 7 pages
Proc. SPIE 6045, MIPPR 2005: Geospatial Information, Data Mining, and Applications, 60450B (2 December 2005); doi: 10.1117/12.650271
Show Author Affiliations
Wei Cui, Wuhan Univ. of Technology (China)
Deren Li, Wuhan Univ. (China)

Published in SPIE Proceedings Vol. 6045:
MIPPR 2005: Geospatial Information, Data Mining, and Applications
Jianya Gong; Qing Zhu; Yaolin Liu; Shuliang Wang, Editor(s)

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