Matching imperfect spatial data

Ana-Maria Olteanu, Sébastien Mustière and Anne Ruas
COGIT Laboratory, Institut Géographique National
2 av. Pasteur, 94160 Saint-Mandé, France
Tel.: + 33; Fax: + 001 555 832 1156;;

Currently, many independent geographical databases exist in the same area and users need to fusion various information coming from these databases. In order to integrate databases, redundancy and inconsistency between data should be identified. Many steps are required to finalise the databases integration and one of them is automatic data matching. In this paper we study which knowledge is required to guide the matching process and more particularly, how to manage uncertain knowledge. Firstly, we analyse how interactive matching is performed and we identify basic knowledge used in this process: objects with similar location, shapes and attributes are matched. Knowledge used is imperfect and manipulated data hold a certain degree of errors and  vagueness. We classify the various kinds of imperfection information used and we distinguish imprecision uncertainty and incompleteness. For each class of imperfection, we choose the appropriate theory to model it. Finally, we illustrate imperfection in spatial data through the results of experiments of data matching through the comparison of toponyms in the context of ethnographical data.

Keywords: integration, data matching, uncertainty and imprecise knowledge

In: Caetano, M. and Painho, M. (eds). Proceedings of the 7th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, 5 – 7 July 2006, Lisboa, Instituto Geográfico Português

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