Data quality is crucial for operational efficiency and sound decision making. This paper focuses on believability, a major aspect of data quality. Our approach is based on the provenance (lineage) of data. We present the main concepts of our model for representing and storing data provenance, and an ontology of the sub-dimensions of data believability. We then use aggregation operators to compute believability across the sub-dimensions of data believability and the provenance of data. Link to the article
PRAT, N. and MADNICK, S. (2007). Evaluating and Aggregating Data Believability across Quality Sub-dimensions and Data Lineage. In: Proceedings of the 17th International Workshop on Information Technologies and Systems (WITS 2007). Montreal: Financial Management Association (FMA), pp. 170-176.