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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.

Bioscience
|March 31, 2018
PubMed
Summary

An iterative scientific method framework helps understand and evaluate data-intensive science, drawing from historical and modern research. This approach offers insights for reforming scientific practices in funding, publishing, and education.

Keywords:
data-intensive sciencehypothesis testingiterationscience educationscience funding

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