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Quality assurance and quality control are phrases used to describe activities that prevent errors from entering or staying in a data set. These activities ensure the quality of the data before it is collected, entered, or analyzed, as well as actively monitoring and maintaining the quality of data throughout the study. In this lesson, we define and provide examples of quality assurance, quality control, data contamination and types of errors that may be found in data sets. After completing this lesson, participants will be able to describe best practices in quality assurance and quality control and relate them to different phases of data collection and entry.


Cite this lesson:
DataONE Community Engagement & Outreach Working Group (2017) "Data Quality Control and Assurance". Accessed through the Data Management Skillbuilding Hub at https://dataoneorg.github.io/Education/lessons/05_qaqc/index on Oct 09, 2018



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Version date: Apr 06, 2017