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Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
Published on: November 22, 2019
Data-Intensive Science and Research Integrity
David B Resnik1, Kevin C Elliott2,3,4, Patricia A Soranno3
1a National Institute for Environmental Health Sciences , National Institutes of Health , Research Triangle Park , North Carolina , USA.
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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