Biomedical Open Source Software: Crucial Packages and Hidden Heroes

April 10, 2024 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Eva Maxfield Brown, Stephan Druskat, Laurent HΓ©bert-Dufresne, James Howison, Daniel Mietchen, Andrew Nesbitt, JoΓ£o Felipe Pimentel, Boris Veytsman arXiv ID 2404.06672 Category cs.SE: Software Engineering Cross-listed cs.CY Citations 3 Venue arXiv.org Last Checked 4 months ago
Abstract
Despite the importance of scientific software for research, it is often not formally recognized and rewarded. This is especially true for foundational libraries, which are hidden below packages visible to the users (and thus doubly hidden, since even the packages directly used in research are frequently not visible in the paper). Research stakeholders like funders, infrastructure providers, and other organizations need to understand the complex network of computer programs that contemporary research relies upon. In this work, we use the CZ Software Mentions Dataset to map the upstream dependencies of software used in biomedical papers and find the packages critical to scientific software ecosystems. We propose centrality metrics for the network of software dependencies, analyze three ecosystems (PyPi, CRAN, Bioconductor), and determine the packages with the highest centrality.
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