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Proceedings Paper

Schema integration of heterogeneous geospatial database
Author(s): Kehua Su; Xinyan Zhu; Fanmin Kong
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Paper Abstract

The integration of heterogeneous geospatial data offers possibilities to manually and automatically derive new information, which are not available when using only a single data source. This paper presents a three-level schema integration architecture which consists of local schemas, mapped schemas, and a global schema, for global heterogeneous geospatial systems. we describe a machine-learning based approach for GIS schema matching. Our approach extends existing machine-learning approaches for (traditional) data mapping but departs from them due to the nature of geographic data. Our solution reduces the complex mappings by identifying different values of a determining property.

Paper Details

Date Published: 10 November 2008
PDF: 9 pages
Proc. SPIE 7146, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Advanced Spatial Data Models and Analyses, 71460Q (10 November 2008); doi: 10.1117/12.813117
Show Author Affiliations
Kehua Su, Wuhan Univ. (China)
Xinyan Zhu, Wuhan Univ. (China)
Fanmin Kong, Yang-En Univ. (China)


Published in SPIE Proceedings Vol. 7146:
Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Advanced Spatial Data Models and Analyses
Lin Liu; Xia Li; Kai Liu; Xinchang Zhang, Editor(s)

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