Computational reproducibility

Definition: Ability to recreate the same results as the original study (including tables, figures, and quantitative findings), using the same input data, computational methods, and conditions of analysis. The availability of code and data facilitates computational reproducibility, as does preparation of these materials (annotating data, delineating software versions used, sharing computational environments, etc). Ideally, computational reproducibility should be achievable by another second researcher (or the original researcher, at a future time), using only a set of files and written instructions. Also referred to as analytic reproducibility (LeBel et al., 2018).

Related terms: <a href='/glossary/fair-principles/'>FAIR principles</a>, <a href='/glossary/replicability/'>Replicability</a>, <a href='/glossary/reproducibility/'>Reproducibility</a>

References: Committee on Reproducibility and Replicability in Science et al. (2019), Kitzes et al (2017, p. xxii), LeBel et al. (2018), Nosek and Errington (2020), & Obels et al. (2020)

Drafted and Reviewed by: Tina Lonsdorf, Sarah Ashcroft-Jones, Helena Hartmann, Annalise A. LaPlume, Adam Parker, Charlotte R. Pennington, Eike Mark Rinke

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