Data Integrity in Research: What Does It Mean and How Do We Achieve It?
Listicle
Last Updated: April 7, 2022
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Published: May 25, 2021
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Naomi Heffer
Naomi Heffer is a PhD researcher working in the fields of cognitive and clinical psychology at the University of Bath. Her research focuses on sensory integration and emotion perception in anxiety and PTSD.
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Data integrity is a broad term that describes the overall accuracy, consistency and completeness of a dataset. In the context of research, maintaining data integrity also includes making sure that data is accessible to those seeking to validate it. Problems with data integrity exist across all industries, but the consequences for those working in science can be particularly serious given the role that scientific research plays in informing policy, healthcare, education and other fundamental aspects of society.
Download this listicle to learn about:
- The importance of data integrity in research
- Data integrity in the digital age
- Improving data integrity
Meet the Author
Naomi Heffer is a PhD researcher working in the fields of cognitive and clinical psychology at the University of Bath. Her research focuses on sensory integration and emotion perception in anxiety and PTSD.
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