This paper reports our method on measuring data quality in data integration. Data integration is the problem of combining data residing at different sources, and providing the user with a unified view of these data. Data quality is crucial for operational data integration. We posit that data-integration need to handle the measure of data quality. So, measuring data quality in data integration is one of worthy research topics. This paper focuses on believability, a major aspect of quality. At first, the author analyzes the background and content of this paper, then description of dimensions of believability is given, and we present our approach for computing believability based on metadata, finally the summary and prospect are listed. In this method, we make explicit use of lineage-based measurements and develop a precise approach to measuring data quality.
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