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: FAIR principles, Replicability, Reproducibility
References:
- on Reproducibility, C., & in Science et al., R. (2019). Reproducibility and Replicability in Science (p. 25303). National Academies Press. https://doi.org/10.17226/25303
- Kitzes, J., Turek, D., & Deniz, F. (2017). The practice of reproducible research: Case studies and lessons from the data-intensive sciences. University of California Press.
- LeBel, E. P., McCarthy, R. J., Earp, B. D., Elson, M., & Vanpaemel, W. (2018). A unified framework to quantify the credibility of scientific findings. Advances in Methods and Practices in Psychological Science, 1(3), 389–402. https://doi.org/10.1177/2515245918787489
- Nosek, B. A., & Errington, T. M. (2020). What is replication? PLOS Biology, 18(3), e3000691. https://doi.org/10.1371/journal.pbio.3000691
- Obels, P., Lakens, D., Coles, N. A., Gottfried, J., & Green, S. A. (2020). Analysis of open data and computational reproducibility in registered reports in psychology. Advances in Methods and Practices in Psychological Science, 3(2), 229–237. https://doi.org/10.1177/2515245920917961
Originally drafted by: Tina Lonsdorf
Reviewed by: Sarah Ashcroft-Jones, Helena Hartmann, Annalise A. LaPlume, Adam Parker, Charlotte R. Pennington, Eike Mark Rinke