From raw data to publication: Introducing data editing at Ecology Letters

A growing number of scientific journals are wrestling with the issue of managing the quality and accessibility of data, code and statistical analyses in the articles they publish. Ensuring that the original data have been deposited in an appropriate repository, that code works and that the analyses on which an article depends can be replicated is increasingly recognized as an essential, but potentially complex, part of the scientific process (Gomes et al., 2022). Moreover, it is also an important element of how science is perceived, trusted and used by the public and to inform policy. Hence, Ecology Letters provides detailed (and recently updated) guidelines on data and code requirements on our website at https://onlinelibrary.wiley.com/page/journal/14610248/homepage/forauthors.html. We urge all authors to carefully read these guidelines before submitting their articles to us. Unfortunately, a substantial fraction of published articles do not meet the standards that journals should be demanding (e.g., Trisovic et al., 2022). Under our previous Editor-in-Chief, Tim Coulson, Ecology Letters piloted an informal data and code-checking step for articles prior to final acceptance. To undertake this activity, we brought several data editors onto the Editorial Board. Following this trial, we have now formally implemented data- and code-checking by incorporating a new step into our workflow. Articles that are likely to be accepted but need data editing will receive a decision of ‘minor revision’. This will allow one of our data editors to be added as a reviewer and provide authors the opportunity to ensure that the data/code standards of Ecology Letters are met before receiving our final decision to accept the article. The revised workflow will make it more efficient for data editors to be involved in the process and ensure that all articles published in Ecology Letters that use data (whether new or existing) or code have gone through this step. Our updated data/code guidelines make it clear what we expect authors to share (and how) as a precondition for articles to be accepted. Specifically, we require the data and code for reproducing statistical results and generating figures and tables that appear in the main text and supplemental materials. This material (i.e., raw data, metadata, code and derived data products) will need to be supplied at the time of submission in an external repository that subject editors and reviewers can access and include a clear README file that will ensure accessibility and readability. This will allow us to properly assess your work and confirm that the archive is complete and usable. A sharing embargo of no more than 1 year is permitted. Exceptions may be made by the Editor-in-Chief only when ethical standards would require that data be kept confidential. If these guidelines are not met, submitted articles will be either sent back for revision or rejected. While we fully support the view that ensuring the executability of code, and access to the raw data that supports published analyses is needed, we also acknowledge the active discussion regarding the equity of ‘FAIR’ data policies to the people who laboured to collect the data (e.g., de Lima et al., 2022; Ross-Hellauer, 2022). This is particularly the case, given the current lack of mechanisms to ensure that subsequent re-use of archived data appropriately credits and cites the original investigators. Data citations are important for the reproducibility of research, to give appropriate credit to data collectors, and as an incentive to make future data publicly available. To this point, we strongly recommend that authors cite all original data sources (rather than a single data compilation) directly in the main text so that citations are properly indexed. This will ensure that authors of the original data sources receive credit. These citations can go in the main text (e.g. methods) where appropriate. For some article types (e.g., Syntheses), long lists of required data citations need not be cited in the main text, but instead will be put into one (or more) appendices with a title such as: ‘Appendix 1—Data citations’. These appendices should be referred to in the main text and will be printed in reduced font in the main article so that citation indexing services will capture them. In cases where there is both an original published article and a citation for the data set, then both should be cited. Finally, as both authors and editors ourselves, we accept that introduction of this step will involve some extra work. However, our experience is that authors are generally willing to comply with the above requirements because of the broader benefits that reproducibility confers on the field. We are hopeful that this change to our review process will be viewed positively by the community of researchers who publish in Ecology Letters.