Data- and code-archiving in the British Ecological Society journals: present status and recommendations for future improvements

Abstract

Data- and code-archiving are important components of open science, as both make research more transparent, reproducible, accountable, and credible, allowing future researchers to identify errors and build on previous work. Despite progress in implementing data- and code-archiving policies in journals publishing ecology and evolution research, issues remain. To be more useful to future researchers, archived data and code must not only be archived, but also meet good practice standards.We collected data from 1,861 papers published between 2017 and 2024 in the seven British Ecological Society (BES) journals, during a hackathon event. We systematically checked associated data and/or code, metadata, help files and annotations to assess archiving practices. We determined if and where data and code files were archived, whether they could be located, downloaded, and opened, and whether they had associated READMEs, digital object identifiers (DOI) and licenses. We also recorded the file extensions used to save data/code files, and which programming languages code was written in. 3. 93% of the 1,861 papers we examined used data and ~90% used code. While 97% of the 1,735 papers that used data also archived it, only 35% of the 1,670 papers that used code also archived code. Over 85% of archived data and code could be located, downloaded, and opened. Reusability, however, was more limited; around a third of papers did not have a README or similar to explain their data/code files, and the quality of READMEs varied substantially.
4. We recommend that researchers archive their code, and that archived code be explicitly mentioned in the Data (or Code) Availability statement. We also encourage researchers to provide more accessible and informative READMEs for data and code. To help achieve these recommendations, we advocate that journals employ Data/Code editors to review data and code quality, research institutions deliver more training in open science practices, and funding bodies set clear expectations on open data and code practices.

Preprint

Citation

BibTeX citation:

@online{2026,
  author = {},
  title = {Data- and Code-Archiving in the {British} {Ecological}
    {Society} Journals: Present Status and Recommendations for Future
    Improvements},
  date = {2026-03-08},
  url = {https://www.luismmontilla.com/papers/cooper2026/},
  doi = {10.32942/X26W9V},
  langid = {en},
  abstract = {1. Data- and code-archiving are important components of
    open science, as both make research more transparent, reproducible,
    accountable, and credible, allowing future researchers to identify
    errors and build on previous work. Despite progress in implementing
    data- and code-archiving policies in journals publishing ecology and
    evolution research, issues remain. To be more useful to future
    researchers, archived data and code must not only be archived, but
    also meet good practice standards. 2. We collected data from 1,861
    papers published between 2017 and 2024 in the seven British
    Ecological Society (BES) journals, during a hackathon event. We
    systematically checked associated data and/or code, metadata, help
    files and annotations to assess archiving practices. We determined
    if and where data and code files were archived, whether they could
    be located, downloaded, and opened, and whether they had associated
    READMEs, digital object identifiers (DOI) and licenses. We also
    recorded the file extensions used to save data/code files, and which
    programming languages code was written in. 3. 93\% of the 1,861
    papers we examined used data and \textasciitilde90\% used code.
    While 97\% of the 1,735 papers that used data also archived it, only
    35\% of the 1,670 papers that used code also archived code. Over
    85\% of archived data and code could be located, downloaded, and
    opened. Reusability, however, was more limited; around a third of
    papers did not have a README or similar to explain their data/code
    files, and the quality of READMEs varied substantially. 4. We
    recommend that researchers archive their code, and that archived
    code be explicitly mentioned in the Data (or Code) Availability
    statement. We also encourage researchers to provide more accessible
    and informative READMEs for data and code. To help achieve these
    recommendations, we advocate that journals employ Data/Code editors
    to review data and code quality, research institutions deliver more
    training in open science practices, and funding bodies set clear
    expectations on open data and code practices.}
}

For attribution, please cite this work as:

bioRxiv. 2026. “Data- and Code-Archiving in the British Ecological Society Journals: Present Status and Recommendations for Future Improvements.” March 8. https://doi.org/10.32942/X26W9V.