An MDA-Based Subsurface Spatial Ontology Modeling for Semantic Sharing

Today, it is difficult to reuse and share spatial data, because of the explosive growth of heterogeneous data and the specific characteristics of spatial data that different local agencies accumulate. A spatial analysis of subsurface spatial information, that which is part of the national spatial data infrastructure, needs related spatial information such as topographical maps, geological maps, and underground facility maps. The existing methods, however, which use a standard format or a spatial datawarehouse, cannot consider semantic heterogeneity. In this study, the layered ontology model, which consists of a generic concept, a measurement unit, a spatial model, and a subsurface spatial information, was developed. Besides, the current ontology building method designed by experts is an expensive and time-consuming process. The MDA-based metamodel (UML Profile) of ontology was developed for easy understanding and flexibility of environmental change. The semantic quality of the developed ontology model was evaluated with the reasoning engine, Pellet. Improved semantic sharing and strengthened capacities to develop a GIS experts system using the knowledge representation ability of ontology are expected.