Data-Intensive Science and Research Integrity |
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| Authors: | David B Resnik Kevin C Elliott Patricia A Soranno Elise M Smith |
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| Institution: | 1. National Institute for Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina, USA;2. Lyman Briggs College, Michigan State University, East Lansing, Michigan, USA;3. Department of Fisheries and Wildlife, Michigan State University, East Lansing, Michigan, USA;4. Department of Philosophy, Michigan State University, East Lansing, Michigan, USA;5. Department of Fisheries and Wildlife, Michigan State University, East Lansing, Michigan, USA |
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| Abstract: | In this commentary, we consider questions related to research integrity in data-intensive science and argue that there is no need to create a distinct category of misconduct that applies to deception related to processing, analyzing, or interpreting data. The best way to promote integrity in data-intensive science is to maintain a firm commitment to epistemological and ethical values, such as honesty, openness, transparency, and objectivity, which apply to all types of research, and to promote education, policy development, and scholarly debate concerning appropriate uses of statistics. |
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| Keywords: | Data-intensive science deception education ethics misconduct research integrity transparency |
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