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Conceptions of Good Science in Our Data-Rich World
Kevin C Elliott1, Kendra S Cheruvelil1, Georgina M Montgomery1
1Kevin C. Elliott (kce@msu.edu) is an associate professor in Lyman Briggs College, the Department of Fisheries and Wildlife, and the Department of Philosophy; Kendra S. Cheruvelil is an associate professor in Lyman Briggs College and the Department of Fisheries and Wildlife; Georgina M. Montgomery is an associate professor in Lyman Briggs College and the Department of History; and Patricia A. Soranno is a professor in the Department of Fisheries and Wildlife at Michigan State University, in East Lansing. All authors contributed equally to the conceptualization of the paper and the supporting research. KCE organized the collaboration and initiated the writing process. All authors contributed text, reviewed manuscript drafts, and approved the final version.
Abstract:
Scientists have been debating for centuries the nature of proper scientific methods. Currently, criticisms being thrown at data-intensive science are reinvigorating these debates. However, many of these criticisms represent long-standing conflicts over the role of hypothesis testing in science and not just a dispute about the amount of data used. Here, we show that an iterative account of scientific methods developed by historians and philosophers of science can help make sense of data-intensive scientific practices and suggest more effective ways to evaluate this research. We use case studies of Darwin's research on evolution by natural selection and modern-day research on macrosystems ecology to illustrate this account of scientific methods and the innovative approaches to scientific evaluation that it encourages. We point out recent changes in the spheres of science funding, publishing, and education that reflect this richer account of scientific practice, and we propose additional reforms.
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