Essential Guide to Sharing Code in Biomedical Research

Research projects generate valuable assets such as data, analytic code, and computational models, but this value often goes unrealized due to limited sharing and curation (Vuorre & Crump, 2021). Sharing data and code is a growing practice in biomedical research (Loder et al., 2024), yet public data sharing remains low, with actual public data availability hovering around 2% and public code sharing stuck at a rate less than 0.5% between 2016 and 2021 (Hamilton, 2023). This article explores the importance of sharing, addresses common reservations among researchers, and provides practical advice on how to share effectively. At the core of this discussion is the idea that by increasing transparency and releasing code as open source, researchers not only meet the requirements of funding agencies and publications but also stimulate institutional, national, and global research progress.