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An ontology-based methodology for geospatial data integration

dc.contributor.authorHe, Juan Xia
dc.date.accessioned2013-11-07T19:30:58Z
dc.date.available2013-11-07T19:30:58Z
dc.date.created2010
dc.date.issued2010
dc.degree.levelMasters
dc.degree.nameM.Sc.
dc.description.abstractData semantic and schematic heterogeneity is a major obstacle to the reuse and sharing of geospatial data. This research focuses on developing an ontology-based methodology to logically integrate heterogeneous geographic data in a cross-border context Three main obstacles hindering data integration are semantic, schematic, and syntactic heterogeneity. Approaches to overcome these obstacles in previous research are reviewed. Among the different approaches, an ontology-based approach is selected for horizontal geospatial data integration in the context of cross-border applications. The integration methodology includes the extraction of application schemas and application ontologies, ontology integration, the creation of a reference model (or ontologies), schema matching and integration, and the creation of usable integrated datasets. The methodology is conceptual and integrates geospatial data based on the semantic content and so is not tied to specific data formats, geometric representations, or feature locations. In order to facilitate the integration procedure, four semantic relationships are used: refer-to, semantic equivalence, semantic generalization, and semantic aggregation. A hybrid ontology approach is employed in order to facilitate the addition of new geospatial data sources to the integration process. As such, three levels of ontologies are developed and illustrated within a MS ACCESS database: application, domain, and a reference model. Furthermore, a working integration prototype is designed to facilitate the integration of geospatial data in the North American context given the semantic and schema heterogeneities in international Canadian-US geospatial datasets. The methodology and prototype provide users with the ability to freely query and retrieve data without knowledge of the heterogeneous data ontologies and schemas. This is illustrated via a case study identifying critical infrastructure around the Ambassador Bridge international border crossing. The methodology and prototype are compared and evaluated with other GDI approaches and by criteria introduced by Buccella et al. (2009). Specific challenges unique to GDI were uncovered and include geographic discrepancies, scale compatibility and temporal issues.
dc.format.extent132 p.
dc.identifier.citationSource: Masters Abstracts International, Volume: 49-05, page: 3090.
dc.identifier.urihttp://hdl.handle.net/10393/28710
dc.identifier.urihttp://dx.doi.org/10.20381/ruor-12681
dc.language.isoen
dc.publisherUniversity of Ottawa (Canada)
dc.subject.classificationGeodesy.
dc.subject.classificationRemote Sensing.
dc.titleAn ontology-based methodology for geospatial data integration
dc.typeThesis

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