Subsurface-data reasoning framework for natural disasters

Abstract

Many heterogeneous data are being distributed via the Web. The heterogeneous data that different suppliers produce make it difficult for users to find and share the data they need. Especially in the GIS, reuse and sharing are very difficult. In this study, the ontological methodology was used to overcome the semantic heterogeneity in the subsurface database system, which is one of Korea's national geospatial information systems and essential for the prevention of diverse natural disasters. The subsurface ontology model, which consists of a generic concept, a measurement unit, a spatial model, and subsurface information, was developed using OWL-DL. Also, subsurface-data reasoning framework, which needs to query, interpret by Jena reasoning engine, and integrate thematic information in the interoperable repositories, open-source geospatial services (e.g. WMS, WFS), and external open-map services was implemented to raise a natural language-style sample query for the retrieval of boring hole or subsurface area in high liquefaction potential. In the future, this study will be expanded to establish domain ontology related to other natural hazards and semantic reasoning system for preventing these disasters by which semantic sharing could be made available in the national geospatial information system.