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- Publisher
- Association for Computing Machinery
- Copyright
- Copyright © 2009 by ACM Inc.
- ISSN
- 0360-0300
- DOI
- 10.1145/1541880.1541883
- Publisher site
- See Article on Publisher Site
Abstract
The literature provides a wide range of techniques to assess and improve the quality of data. Due to the diversity and complexity of these techniques, research has recently focused on defining methodologies that help the selection, customization, and application of data quality assessment and improvement techniques. The goal of this article is to provide a systematic and comparative description of such methodologies. Methodologies are compared along several dimensions, including the methodological phases and steps, the strategies and techniques, the data quality dimensions, the types of data, and, finally, the types of information systems addressed by each methodology. The article concludes with a summary description of each methodology.
Journal
ACM Computing Surveys (CSUR) – Association for Computing Machinery
Published: Jul 1, 2009