Measuring Data Quality for Ongoing Improvement

Appendix B

Data Quality Dimensions

Purpose

Dimensions of data quality are fundamental to understanding how to improve data. This appendix summarizes, in chronological order of publication, three foundational definitions of data quality dimensions: those of Richard Wang and Diane Strong, Thomas Redman, and Larry English. These provide context for the choices in the DQAF. In the DQAF, I have not proposed new dimensions of data quality. On the contrary, I draw a subset and have narrowed their scope to define objective measurements that can be taken from within a dataset.

Richard Wang’s and Diane Strong’s Data Quality Framework, 1996

In the article, “Beyond Accuracy: What Data Quality Means to Data Consumers,” Wang and Strong present results of a survey ...