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Biomedical open source software: Crucial packages and hidden heroes.

Eva Maxfield Brown1, Stephan Druskat2, Laurent Hébert-Dufresne3

  • 1Information School, University of Washington, Seattle, Washington, United States of America.

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Summary
This summary is machine-generated.

Scientific software is crucial but often unrewarded. This study identifies critical foundational libraries in biomedical research ecosystems using dependency network analysis, highlighting essential software components.

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Area of Science:

  • Computer Science
  • Bioinformatics
  • Software Engineering

Background:

  • Scientific software is vital for research reproducibility and advancement.
  • Foundational software libraries are often unrecognized and unrewarded, despite their critical role.
  • Understanding research software dependencies is essential for stakeholders like funders and infrastructure providers.

Purpose of the Study:

  • To map the upstream dependencies of software used in biomedical research papers.
  • To identify critical packages within scientific software ecosystems.
  • To propose and apply centrality metrics for analyzing software dependency networks.

Main Methods:

  • Utilized the CZ Software Mentions Dataset to analyze software dependencies.
  • Developed and applied network centrality metrics to quantify package importance.
  • Examined three major software ecosystems: PyPi, CRAN, and Bioconductor.

Main Results:

  • Identified key foundational software packages critical to biomedical research.
  • Quantified the centrality of software packages within different ecosystems.
  • Revealed the hidden network of software dependencies underpinning scientific publications.

Conclusions:

  • Formal recognition and reward systems for scientific software are needed.
  • Centrality metrics can effectively highlight essential software components in research.
  • This work provides a framework for understanding and valuing critical research software infrastructure.