Semi-automatic Ontology Alignment for Geospatial Data Integration
In geospatial applications with heterogeneous databases, an ontology-driven approach to data integration relies on the alignment of the concepts of a global ontology that describe the domain, with the concepts of the ontologies that describe the data in the local databases. Once the alignment between the global ontology and each local ontology is established, users can potentially query hundreds of databases using a single query that hides the underlying heterogeneities. Using our approach, querying can be easily extended to a new data source by aligning a local ontology with the global one. For this purpose, we have designed and implemented a tool to align ontologies. The output of this tool is a set of mappings between concepts, which will be used to produce the queries to the local databases once a query is formulated on the global ontology. To facilitate the user’s task, we propose semi-automatic methods for propagating such mappings along the ontologies. In this paper, we present the principles behind our propagation method, the implementation of the tool, and we conclude with a discussion of interesting cases and proposed solutions.
KeywordsMapping Type Residential Building Apartment Building Land Parcel Local Ontology
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- 3.Cruz, I.F., Rajendran, A., Sunna, W., Wiegand, N.: Handling Semantic Heterogeneities using Declarative Agreements. In: International ACM GIS Symposium, pp. 168–174 (2002)Google Scholar
- 4.Hovy, E.: Combining and Standardizing Large-Scale, Practical Ontologies for Machine Translation and Other Uses. In: Rubio, A., Gallardo, N., Castro, R., Tejada, A. (eds.) First International Conference on Languages Resources and Evaluation (LREC), Granada, Spain, pp. 535–542 (1998)Google Scholar
- 5.McGuinness, D.L., Fikes, R., Rice, J., Wilder, S.: An Environment for Merging and Testing Large Ontologies. In: Seventeenth International Conference on Principles of Knowledge Representation and Reasoning (KR 2000), pp. 483–493 (2000)Google Scholar
- 6.Miller, G.A.: WordNet: An Online Lexical Database. Technical report, Princeton University (1990)Google Scholar
- 7.Noy, N.F., Musen, M.A.: PROMPT: Algorithm and Tool for Automated Ontology Merging and Alignment. In: The Sixteenth National Conference on Artificial Intelligence (AAAI), pp. 450–455 (2000)Google Scholar
- 8.J. Park, J. Gennari, and M. Musen. Mappings for Reuse in Knowledge-based Systems. In 11th Workshop on Knowledge Acquisition, Modelling and Management, , 1998. http://ksi.cpsc.ucalgary.ca/KAW/KAW98/park/. Google Scholar
- 9.Sowa, J.: Building, Sharing, and Merging Ontologies (2001), http://www.jfsowa.com/ontology/ontoshar.htm