Earlier this year I outlined three ways PLOS is working to eliminate author fees through new business models. The models we introduced…
PLOS Computational Biology has adopted an enhanced code sharing policy for all papers submitted from 30 March 2021. The change, announced in this editorial, comes in response to community needs and support for initiatives which drive Open Science practices.
Code sharing is not new to many of our authors. Research shows that 41% of papers in PLOS Computational Biology already share code voluntarily (Boudreau et al. 2021), demonstrating the community’s willingness to make their work both rapidly available and methodologically transparent. This creates a strong foundation for implementing a stronger policy and also works towards establishing code sharing as a normal research behaviour.
PLOS Computational Biology defines “open” as more than the availability of a research article. Our authors, editors, and readers see data and code sharing as tools to boost reproducibility and transparency. Sharing code alongside data will allow others to check and reproduce work and ultimately drive new discoveries. Requiring authors to share their code (unless there are good reasons not to) works towards making the research published in PLOS Computational Biology as robust as possible for the benefit of the whole research community.
In developing the policy we sought views from researchers in the computational community on the barriers they face when sharing code (Harney et al. 2021). We then tested our policy text with researchers to help inform its design and content. This has allowed us to respond to researcher needs, for example by allowing exemptions to the policy for those with legitimate legal or ethical constraints on sharing. In this way, PLOS Computational Biology continues to be shaped by policies the community has helped define, and Open Science values that reflect the way they want to communicate research.
Open Science at PLOS
Open Science is one of our founding principles at PLOS. Enhancing the code sharing policy at one of our journals in response to community needs is just one step we are making to increase the adoption of Open Science practices. We aim to empower researchers to share their good practices because we believe communities are best placed to define their own needs. The computational biology community is shaping the future of research communication by leading the way in practices that make science more open and equitable for all. However, we do offer guidance and help to those who need it, for example, by detailing best practice for code sharing alongside our policy text. No matter how researchers choose to make their work Open, PLOS Computational Biology provides options to support researcher needs and the platform to influence broader change.
Collaboration with the community and responding to their needs is part of our approach to Open Science, regardless of how that community is defined. We will be closely monitoring the reaction to the code sharing policy at PLOS Computational Biology and exploring what an enhanced policy could mean for other communities that we serve.
Written by Lauren Cadwallader, Open Research Manager
Boudreau M, Poline J-B, Bellec P, Stikov N (2021) On the open-source landscape of PLOS Computational Biology. PLOS Comput Biol 17(2): e1008725. https://doi.org/10.1371/journal.pcbi.1008725
Harney J, Hrynaszkiewicz I, Cadwallader L, (2021) Code Sharing Survey 2020 – PLOS Computational Biology. figshare. Dataset. https://doi.org/10.6084/m9.figshare.13366025