2024/12/09 by Alfredo Sánchez‐Tójar, Aya Bezine, Marija Purgar +1 · 1 voice · 1 citation
Decision Sciences · Computer Science · #Scientific Computing and Data Management #Research Data Management Practices
paper · pdf · doi:10.32942/x21s7h
Software code (e.g., analytical code) is increasingly recognised as an important research output, as it improves transparency, collaboration, and research credibility. Many scientific journals have introduced code-sharing policies; however, surveys show alarmingly low compliance with these policies. In this study, we expand on a recent survey of ecological journals with code-sharing policies by investigating sharing practices in a comparable set of ecological journals without code-sharing policies. Our aims were to estimate code- and data-sharing rates, assess key reproducibility-boosting features like the reporting of software versioning, and compare reproducibility potential between journals with and without a code-sharing policy. We reviewed a random sample of 314 articles published between 2015-2019 across 12 ecological journals without a code-sharing policy. Only 15 articles (4.8%) provided analytical code, with the percentage nearly tripling over time (2015-2016: 2.5%, 2018-2019: 7.0%). Data-sharing was higher than code-sharing (2015-2016: 31.0%, 2018-2019: 43.3%), yet only 8 articles (2.5%) shared both code and data. Compared with a comparative sample of 346 articles from 14 ecological journals with a code-sharing policy, journals without code-sharing policies showed 5.6 times lower code-sharing, 2.1 times lower data-sharing, and 8.1 times lower reproducibility potential. Despite these differences, key reproducibility-boosting features between the two types of journals were similar. About 90% of all articles reported the analytical software used; however, for journals with and without a code-sharing policy, software version was often missing (49.8% and 36.1% of articles, respectively), and only proprietary (i.e., non-free) software was used in 16.7% and 23.5% of articles, respectively. Our study suggests that journals with code-sharing policies have greater reproducibility potential than those without. Code-sharing policies are likely a necessary but insufficient key step toward increasing reproducibility. Journals should prioritize adopting explicit, easy-to-find and strict code-sharing policies to facilitate researcher compliance as well as implement mechanisms such as checklists to ensure compliance.