Automatic construction of a knowledge base for transport networks
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Abstract
Abundant spatial transport data is accessible from governmental institutions or internet sources contributed from all over the world. This kind of data obtained from various sources exists in different structures and prevents interoperability. The aim of the research, in this paper, is to develop an ontology compatible with specifications of transport networks of Infrastructure for Spatial Information in the European Community (INSPIRE) and to obtain a knowledge base of transportation data from non-semantic data sources automatically. In the first stage, ontological classes and relations in the transport network are explained. Then, defining algorithms in three main phases, non-semantic spatial data is transformed into the ontological structure. Some ontological queries are implemented to retrieve information from a knowledge base that is produced because of the transformation algorithms. As a result of the study, the transportation datasets in the relational database have been successfully converted into a semantic data format. The functionality of the obtained knowledge base was validated with queries that allow semantic reasoning.
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References
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