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  3. From Policy To Practice: Progress Towards Data- And Code-sharing In Ecology And Evolution.
  1. Home
  3. From Policy To Practice: Progress Towards Data- And Code-sharing In Ecology And Evolution.

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From policy to practice: progress towards data- and code-sharing in ecology and evolution.

Edward R Ivimey-Cook1, Alfredo Sánchez-Tójar2, Ilias Berberi3

  • 1School of Biodiversity, One Health, and Veterinary Medicine, University of Glasgow, Glasgow, UK.

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|September 16, 2025

View abstract on PubMed

Summary
This summary is machine-generated.

Scientific journals in ecology and evolution show a need for better data and code sharing policies. Improving these policies and compliance is crucial for enhancing research reproducibility.

Keywords:
journal policyopen sciencepeer reviewreplicabilityreproducibilitytransparency

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Area of Science:

  • Ecology and Evolution
  • Scientific Publishing
  • Data Science

Background:

  • Data and code sharing are vital for scientific credibility and reproducibility.
  • Journal policies significantly influence data and code sharing practices.
  • The extent and accessibility of these policies in ecology and evolution remain unclear.

Purpose of the Study:

  • To assess the clarity, strictness, and timing of data and code sharing policies in 275 ecology and evolution journals.
  • To evaluate initial compliance with these policies using manuscript submissions from two leading journals.
  • To identify areas for improvement in journal policies and their enforcement to boost reproducibility.

Main Methods:

  • Policy analysis of 275 ecology and evolution journals.
  • Assessment of data and code sharing policy characteristics (clarity, strictness, timing).
  • Compliance evaluation of manuscript submissions (n=2340 for Proceedings of the Royal Society B, n=571 for Ecology Letters).

    • Main Results:

    • Only 22.5% of journals encouraged and 38.2% mandated data sharing; 26.6% encouraged and 26.9% mandated code sharing.
    • Mandatory sharing policies were more frequently linked to peer review requirements (59.0% for data, 77.0% for code).
    • Encouraged sharing had lower links to peer review (40.3% for data, 24.7% for code), indicating room for stronger policy integration.

    Conclusions:

    • Journal policies play a key role in promoting data and code sharing.
    • Significant improvements are needed in policy clarity, strictness, and compliance to enhance research reproducibility.
    • Seven recommendations are proposed to enhance data and code sharing practices and policy adherence in scientific publishing.