"The best way to promote integrity in data-intensive science is to maintain a firm commitment to epistemological and ethical values..."

Account Res. 2017 May 8. doi: 10.1080/08989621.2017.1327813. [Epub ahead of print]

Data-Intensive Science and Research Integrity.

Resnik DB1, Elliott KC2, Soranno PA3, Smith EM4.

Author information

1

a National Institute for Environmental Health Ethics, National Institutes of Health , 111 Alexander Drive, Research Triangle Park , NC , 27709 , USA.

2

b Lyman Briggs College, Department of Fisheries and Wildlife, and Department of Philosophy , Michigan State University.

3

c Department of Fisheries and Wildlife , Michigan State University.

4

d National Institute for Environmental Health Ethics, National Institutes of Health.

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.