Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W5, 293-296, 2015
© Author(s) 2015. This work is distributed
under the Creative Commons Attribution 3.0 License.
11 Dec 2015
S. Hasani1, A. Sadeghi-Niaraki1, and M. Jelokhani-Niaraki2 1Department of GIS, Faculty of Geodesy and Geomatics Engineering, K.N.Toosi University of Technology, Tehran, Iran
2Department of GIS & RS, Faculty of Geography, University of Tehran, Tehran, Iran
Keywords: SDI, Ontology, Ubi GIS, Data integration, Semantic Web Abstract. In today's world, the necessity for spatial data for various organizations is becoming so crucial that many of these organizations have begun to produce spatial data for that purpose. In some circumstances, the need to obtain real time integrated data requires sustainable mechanism to process real-time integration. Case in point, the disater management situations that requires obtaining real time data from various sources of information. One of the problematic challenges in the mentioned situation is the high degree of heterogeneity between different organizations data. To solve this issue, we introduce an ontology-based method to provide sharing and integration capabilities for the existing databases. In addition to resolving semantic heterogeneity, better access to information is also provided by our proposed method. Our approach is consisted of three steps, the first step is identification of the object in a relational database, then the semantic relationships between them are modelled and subsequently, the ontology of each database is created. In a second step, the relative ontology will be inserted into the database and the relationship of each class of ontology will be inserted into the new created column in database tables. Last step is consisted of a platform based on service-oriented architecture, which allows integration of data. This is done by using the concept of ontology mapping. The proposed approach, in addition to being fast and low cost, makes the process of data integration easy and the data remains unchanged and thus takes advantage of the legacy application provided.
Conference paper (PDF, 837 KB)

Citation: Hasani, S., Sadeghi-Niaraki, A., and Jelokhani-Niaraki, M.: SPATIAL DATA INTEGRATION USING ONTOLOGY-BASED APPROACH, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W5, 293-296, doi:10.5194/isprsarchives-XL-1-W5-293-2015, 2015.

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