| Summary: Pressed by technological developments, the increased importance of geospatial data has rendered it to be used in decision making throughout public, private sectors, and all other interested parties. This was indeed the reason of quest for “Spatial Data Infrastructures (SDI)” among spatial data communities for the past two decades. Being interoperability infrastructures, SDIs enable the integration of data from different sources. “Semantic schema matching” is a recent Semantic Web Technology (SWT) for enabling data integration in SDIs an “automatic” manner. For this reason, during first part of this thesis, the database schemas of different Public agencies have been tried to be matched by semantic matching. As a result, it has been found that full automated schema matching by SWT is not possible today. Accordingly, a number of problems have been identified and some proposals for these problems have been made. In the second part of the thesis, another popular problem like semantic matching, Web Services Composition (WSC) has been tackled. The purpose was to employ SWT for the problems of WSC in the context of SDIs. As the result, an architecture for this aim has been proposed. The architecture has been tested for the case study of the thesis, “site selection for waste disposal”. A WSC is a combination of a number of Web Services to perform a more complex task than the combined services can do alone. Currently WSC is performed semi-automatically meaning that human intervention is needed. Although there is plenty of research towards, Full Automated WSC (FAWSC) has not been achieved yet. In FAWCS both the combination of services into an “abstract” WSC and the execution of the WSC (“concrete” WSC) are performed by the software without human intervention. To achieve FAWCS a number of problems have to addressed. This has formed the inspiration for this thesis; would SWT have some provisions in dealing with these problems? An architecture has been proposed in this thesis. By the architecture, the user states his “goal” by a natural language sentence. By semantically matching this sentence to a Spatial Services Ontology (SSO), the corresponding “abstract” WSC is “located” within SSO. Discovering the “matching” advertised services semantically again, “concrete” WSC is formed afterwards. Although there are still untackled problems due partly to the scope of the thesis, this study makes a valuable contribution to the area.
Key Words: Semantic matching, Semantic Web Services, Web Services Composition, Spatial Services Ontology, Spatial Data Infrastructures, Semantic Web
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