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

Natalie Cooper, Bethany J. Allen, Nour Almaani, Res Altwegg, Julia Balogh, Heikel Balti, Robert A. Barber, Maria E. Barbosa de Sousa, Jose Gabriel Nino Barreat, Cassandra F. Barrett, Ryan Bates, Alexia M.J.M. Beale, Louis Bliard, Nynke Blömer, Dariia Borovyk, Charlotte Bunnenberg, Elizabeth A. Bygate, Lucy Cash, Nilanjan Chatterjee, Ting-Wen Chen, Arianna Chiti, Sheena Suet-Wah Chung, Hector Chuquillanqui, Anna Ciezarek, Archie Clarkson, Edward Codling, Andrea Corradini, Amber Cowans, Sofia Dartnell, Amy J.S. Davis, Luciano Ludovico Maria De Benedictis, Gideon G. Deme, Christian Devenish, Shreya Dimri, Carolin Dittrich, Kalyn R. Dorheim, Harriet B. Drage, Manuel-Angel Dueñas, Angelena Efstathiou, Luke C. Evans, Myrna E. Ferreira Santos, Alicia J. Foxx, Ross J. Gardiner, Joseph Gaudard, William Gearty, Laura Graham, Victoria M. Graves, Holly M. Green, Rosemary V. Greensmith, Sylvain Gérard, Aud H. Halbritter, Tamara R. Hartke, Robert M. Hechler, Bethan J. Hindle, Pen-Yuan Hsing, Sonia Illanas, Graziella Iossa, Eleanor E. Jackson, Lewis A. Jones, Faith A.M. Jones, Joshua A. Jones, Jonathan F. Jupke, Nabilla Nuril Kaunain, Rochelle Kennedy, Matthew R. Kerr, Nicole J. Kester, Moritz Klaassen, Oliwia Konecka, Ruby Krasnow, Rebekka Kukowski, Abhishek Kumar, Rowan Kuminski, K. S. Kuzey, Lucrezia Laccetti, Malgorzata Lagisz, Hooman Latifi, Nicolas Lecomte, Keshav D. Luchmun, Agathe Lévêque, Alexandra Markitantova, Benjamin M. Marshall, Esteban Menares-Barraza, Daan Mertens, Geoffrey Mesbahi, Jennifer Meyer, Joseph Millard, Luis M. Montilla, Bruno Moreira, Albert Morera, Gopal Murali, Marcella P. Murray, Frederik Märker, Kaushalya Nagahawatte, Claire L. Narraway, Holly I. Niven, Alivia G. Nytko, Bettina Ohse, Stuart Patterson, Helen R.P. Phillips, Ryan Pienaar, Pietro Pollo, Angel Ponce, Lucas M.V. Porto, Elizabeth F.R. Preston, Clemence S. Prieul, Alona Prylutska, Oleh Prylutskyi, Klara Radman-Daw, Aina M. Raharison, Rachana Rao, Freya R. Read, Sydne Record, William Rees, Richard Reeve, Harriet Rhodes, Camila Rocabado, Anna Rouviere, Anna Rönnfeldt, Alban Sagouis, Sailee Pradeep Sakhalkar, Gabriel Silva Santos, Mohammad Abdus Shakur, Rebecca Shaw, Dominika Siegieda, Lucia Šmídova, Benno I. Simmons, Hannah G. Sisley, Alfredo Sánchez-Tójar , Fernando G. Taboada, Nigel G. Taylor, Hannah Teague, Karthik Thrikkadeeri, Viktoria Thuroczy, Alexa Varah, K. L. Vinay, Cecylia M. Watrobska, Zach B. Williams, Saras M. Windecker

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 ~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.