SoS: BIO: The Anatomy of Scientific Biomedical Open-Source Software--From Code to Communities

This project addresses critical gaps in understanding biomedical open-source software (OSS) infrastructure that underpins modern health research. The broad objective is to systematically characterize, model, and evaluate the sustainability of biomedical OSS to optimize research productivity and ensure reliable scientific outcomes that advance NIH's mission of improving human health. Open-source software has become essential infrastructure for biomedical research, yet the origins, sustainability, and impact of scientific biomedical OSS remain poorly understood. Unlike generic OSS, scientific software requires domain expertise and operates within unique constraints of academic funding cycles and publication incentives. The research addresses three specific aims: (1) identify and characterize biomedical OSS infrastructure through computational census of software origins, evolution, and usage patterns; (2) model the health and sustainability of biomedical OSS by analyzing maintenance practices, team dynamics, and abandonment risk factors; and (3) quantify the relationship between software maintenance status and scientific outcomes, including research productivity, reproducibility, and resource efficiency. The study employs a mixed-methods approach using three integrated datasets. Popular biomedical OSS packages will be identified from the Chan Zuckerberg Initiative's dataset of 15 million software citations. Repository contribution histories will be analyzed using World of Code, which aggregates metadata from OSS repositories worldwide. Contributors will be linked to academic institutions through OpenAlex data and NSF/NIH funding records.