New data- and code-sharing paper in Proceedings B
Ivimey-Cook, E.R.*, Sánchez-Tójar, A.*, Berberi, I., Culina, A., Roche, D.G., Almeida, R.A., Amin, B., Bairos-Novak, K.R., Balti, H., Bertram, M.G., Bliard, L., Byrne, I., Chan, Y.-C., Cioffi, W.R., Corbel, Q., Elsy, A.D., Florko, K.R.N., Gould, E., Grainger, M.J., Harshbarger, A.E., Hovstad, K.A., Martin, J.M., Martinig, A.R., Masoero, G., Moodie, I.R., Moreau, D., O'Dea, R.E., Paquet, M., Pick, J.L., Rizvi, T., Silva, I., Szabo, B., Takola, E., Thoré, E.S.J., Verberk, W.C.E.P., Windecker, S.M., Winter, G., Zajková, Z., Zeiss, R., Moran, N.P.* 2025. From policy to practice: progress towards data- and code-sharing in ecology and evolution. Proc. R. Soc. Lond., B, Biol. Sci. 292: 20251394. https://doi.org/10.1098/rspb.2025.1394 | PDF * Authors contributed equally.
ABSTRACT
Data and code are essential for ensuring the credibility of scientific results and facilitating reproducibility, areas in which journal sharing policies play a crucial role. However, in ecology and evolution, we still do not know how widespread data- and code-sharing policies are, how accessible they are, and whether journals support data and code peer review. Here, we first assessed the clarity, strictness and timing of data- and code-sharing policies across 275 journals in ecology and evolution. Second, we assessed initial compliance to journal policies using submissions from two journals: Proceedings of the Royal Society B (Mar 2023–Feb 2024: n = 2340) and Ecology Letters (Jun 2021–Nov 2023: n = 571). Our results indicate the need for improvement: across 275 journals, 22.5% encouraged and 38.2% mandated data-sharing, while 26.6% encouraged and 26.9% mandated code-sharing. Journals that mandated data- or code-sharing typically required it for peer review (59.0% and 77.0%, respectively), which decreased when journals only encouraged sharing (40.3% and 24.7%, respectively). Our evaluation of policy compliance confirmed the important role of journals in increasing data- and code-sharing but also indicated the need for meaningful changes to enhance reproducibility. We provide seven recommendations to help improve data- and code-sharing, and policy compliance.
