A manifesto for reproducible science

Improving the reliability and efficiency of scientific research will increase the credibility of the published scientific literature and accelerate discovery. Here we argue for the adoption of measures to optimize key elements of the scientific process: methods, reporting and dissemination, reproduc...

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Bibliographic Details
Published in:Nature human behaviour 2017-01, Vol.1 (1), p.0021, Article 0021
Main Authors: Munafò, Marcus R., Nosek, Brian A., Bishop, Dorothy V. M., Button, Katherine S., Chambers, Christopher D., Percie du Sert, Nathalie, Simonsohn, Uri, Wagenmakers, Eric-Jan, Ware, Jennifer J., Ioannidis, John P. A.
Format: Article
Language:English
Subjects:
706/689
Behavioral Sciences
Bias
Biomedical and Life Sciences
Data analysis
Dissemination
Education
Efficiency
Experimental Psychology
Hypotheses
Laboratory animals
Life Sciences
Microeconomics
Neurosciences
Personality and Social Psychology
perspective
Reliability
Reproducibility
Science
Scientists
Transparency
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Summary:Improving the reliability and efficiency of scientific research will increase the credibility of the published scientific literature and accelerate discovery. Here we argue for the adoption of measures to optimize key elements of the scientific process: methods, reporting and dissemination, reproducibility, evaluation and incentives. There is some evidence from both simulations and empirical studies supporting the likely effectiveness of these measures, but their broad adoption by researchers, institutions, funders and journals will require iterative evaluation and improvement. We discuss the goals of these measures, and how they can be implemented, in the hope that this will facilitate action toward improving the transparency, reproducibility and efficiency of scientific research. Leading voices in the reproducibility landscape call for the adoption of measures to optimize key elements of the scientific process.
ISSN:2397-3374
2397-3374
DOI:10.1038/s41562-016-0021