¹School of Management and Engineering, Nanjing University, Nanjing, Jiang Su, China, 210093
²Department of Computer and Information Management, GuangXi University of Finance and Economics, Nanning, GuangXi, China, 530003
³Department of Information Management, Nanjing University, Nanjing, Jiang Su, China, 210093

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Abstract—The ultimate goal of data quality management (DQM) is to improve the data quality (DQ) to facilitate enterprises decision-making, and the data quality assessment (DQA) is an important aspect in the process of DQM. Existing research in DQA focuses on the establishment of evaluation indicators and quantified methods in specific areas of application, but does not take into account the evolution of the data. For the current context of complex heterogeneous data environment, DQA framework based on provenance and SOA is designed, and provenance management process is focused to describe, finally the provenance model is defined and implemented. Overall, an example described in the paper demonstrates the necessity and feasibility of introducing provenance into DQA.

Index Terms—Data quality management, Data quality assessment, Provenance, SOA, SPARQL

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Cite: Hua Zheng, Qinghua Zhu, and Kewen Wu, "Provenance Management for Data Quality Assessment," Journal of Software vol. 7, no. 8, pp. 1905-1910, 2012.