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While some scientists study insects, molecules, brains, or clouds, other scientists study science itself. Meta-research, or research-on-research, is a burgeoning discipline that investigates efficiency, quality, and bias in the scientific ecosystem, topics that have become especially relevant amid widespread concerns about the credibility of the scientific literature. Meta-research may help calibrate the scientific ecosystem toward higher standards by providing empirical evidence that informs the iterative generation and refinement of reform initiatives. We introduce a translational framework that involves ( a) identifying problems, ( b) investigating problems, ( c) developing solutions, and ( d) evaluating solutions. In each of these areas, we review key meta-research endeavors and discuss several examples of prior and ongoing work. The scientific ecosystem is perpetually evolving; the discipline of meta-research presents an opportunity to use empirical evidence to guide its development and maximize its potential.

Key Points Question What are the rates of declared and actual sharing of clinical trial data after the medical journals’ implementation of the International Committee of Medical Journal Editors data sharing statement requirement? Findings In this cross-sectional study of 487 clinical trials published in JAMA , Lancet , and New England Journal of Medicine , 334 articles (68.6%) declared data sharing. Only 2 (0.6%) individual-participant data sets were actually deidentified and publicly available on a journal website, and among the 89 articles declaring that individual-participant data would be stored in secure repositories, data from only 17 articles were found in the respective repositories as of April 10, 2020. Meaning These findings suggest that there is a wide gap between declared and actual sharing of clinical trial data.