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

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.