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Foundations for Quality Management of Scientific Data Products

Summary: [This abstract is based on the author's abstract.]The consequences of scientific conclusions based on faulty data can be far reaching, remain unchallenged for years in the literature, and skew subsequent research. Additionally, since most scientific research in the U.S. is federally funded, propagation of error is costly to taxpayers. A foundation is proposed for the management of data quality as it applies to scientific data products. Definitions of data products and data quality are suggested in two circumstances: collecting observational data and performing archive-based research. Relevant extensions of the total quality management (TQM) philosophy are examined to determine if they are applicable to scientific data management. Recommendations are given for designing quality into the production process.

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  • Topics: Total Quality Management, Data Quality, Quality Management
  • Keywords: Research,Total Quality Management (TQM),Data analysis,Quality management principles
  • Author: Radziwill, Nichole M.
  • Journal: Quality Management Journal