Data reconciliation and fusion methods: a survey.

With the progress of new technologies of information and communication, more andmore producers of data exist. On the other hand, the web forms a huge support of all these kinds of data. Unfortunately, existing data is not proper due to the existence of the same information in different sources, aswell as erroneous and incomplete data. The aim of data integration systems is to offer to a user a unique interface to query a number of sources. A key challenge of suchsystems is todealwith conflicting information fromthe samesource or fromdifferent sources. We present, in this paper, the resolution of conflict at the instance level into two stages: references reconciliation and data fusion. The reference reconciliationmethods seek to decide if two data descriptions are references to the same entity in reality. We define the principles of reconciliation method then we distinguish the methods of reference reconciliation, first on howto use the descriptions of references, then theway to acquire knowledge. We finish this sectionby discussing some current data reconciliation issues that are the subject of current research. Data fusion in turn, has the objective to merge duplicates into a single representation while resolving conflicts between the data. We define first the conflicts classification, the strategies for dealing with conflicts and the implementing conflict management strategies. We present then, the relational operators and data fusion techniques. Likewise, we finish this section by discussing some current data fusion issues that are the subject of current research. [ABSTRACT FROM AUTHOR]