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<p><it>Abstract</it>—Organizational databases are pervaded with data of poor quality. However, there has not been an analysis of the data quality literature that provides an overall understanding of the state-of-art research in this area. Using an analogy between product manufacturing and data manufacturing, this paper develops a framework for analyzing data quality research, and uses it as the basis for organizing the data quality literature. This framework consists of seven elements: management responsibilities, operation and assurance costs, research and development, production, distribution, personnel management, and legal function. The analysis reveals that most research efforts focus on operation and assurance costs, research and development, and production of data products. Unexplored research topics and unresolved issues are identified and directions for future research provided.</p>
Data quality, data manufacturing, data product, Total Quality Management (TQM), ISO9000, information quality, data quality analysis, data quality practices.
Veda C. Storey, Christopher P. Firth, Richard Y. Wang, "A Framework for Analysis of Data Quality Research", IEEE Transactions on Knowledge & Data Engineering, vol. 7, no. , pp. 623-640, August 1995, doi:10.1109/69.404034
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