Codefair: Your Personal Assistant for Developing FAIR Software (Presentation)

The abstract associated with this presentation is provided below. More information is availabe at https://github.com/fairdataihub/codefair-USRSE-2024

Abstract

Most research projects today involve the development of some research software. Therefore, it has become more important than ever to make research software reusable to enhance transparency, prevent duplicate efforts, and ultimately increase the pace of discoveries. The Findable, Accessible, Interoperable, and Reusable (FAIR) Principles for Research Software (or FAIR4RS Principles) provide a general framework for achieving that.1 Just like the original FAIR Principles2, the FAIR4RS Principles are as designed to be aspirational and do not provide actionable instructions. To make their implementation easy, we established the FAIR Biomedical Research Software (FAIR-BioRS) guidelines, which are minimal, actionable, and step-by-step guidelines that biomedical researchers can follow to make their research software compliant with the FAIR4RS Principles.3,4 While they are designed to be easy to follow, we learned that the FAIR-BioRS guidelines can still be time-consuming to implement, especially for researchers without formal software development training. They are also prone to user errors as they require several actions with each new version release of a software. 

To address this challenge, we are developing codefair, a free and open-source GitHub app that acts as a personal assistant for making research software FAIR in line with the FAIR-BioRS guidelines.5,6 The objective of codefair is to minimize developers’ time and effort in making their software FAIR so they can focus on the primary goals of their software. To use codefair, developers only need to install it from the GitHub marketplace. By leveraging tools such as Probot and GitHub API, codefair monitors activities on the software repository and communicates with the developers via a GitHub issue “dashboard” that lists issues related to FAIR-compliance (updated with each new commit). For each issue, there is a link that takes the developer to the codefair user interface (built with Nuxt, Naive UI and Tailwind) where they can better understand the issue, address it through an intuitive interface, and submit a pull request automatically with necessary changes to address the related issue. Currently, codefair is in the early stages of development and helps with including essential metadata elements such as a license file, a CITATION.cff metadata file, and a codemeta.json metadata file. Additional features are being added to provide support for complying with language-specific standards and best coding practices, archiving on Zenodo and Software Heritage, registering on bio.tools, and much more to cover all the requirements for making software FAIR. 

In this talk, we will highlight the current features of codefair, discuss upcoming features, explain how the community can benefit from it, and also contribute to it. We believe codefair is an essential and impactful tool for enabling software curation at scale and turning FAIR software into reality. The application of codefair is not limited to just making biomedical research software FAIR as it can be extended to other fields and also provide support for software management aspects outside of the FAIR Principles, such as software quality and security. We believe this work is fully aligned with the US-RSE’24 topic of “Software engineering approaches supporting research”. The conference participants will benefit greatly from this talk as they will learn about a tool that can enhance their software development practices. We will similarly benefit as we are looking for community awareness and contribution in the development of codefair, which is not currently supported through any funding but is the result of the authors aim to reduce the burden of making software FAIR on fellow developers.

References

1. Barker, M. et al. Introducing the FAIR Principles for research software. Sci Data 9, 622 (2022). https://doi.org/10.1038/s41597-022-01710-x 

2. Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016). https://doi.org/10.1038/sdata.2016.18 

3. Patel, B., Soundarajan, S., Ménager, H. & Hu, Z. Making Biomedical Research Software FAIR: Actionable Step-by-step Guidelines with a User-support Tool. Sci Data 10, 557 (2023). https://doi.org/10.1038/s41597-023-02463-x 

4. FAIR biomedical research software (FAIR-BioRS) guidelines. https://fair-biors.org.

5.  codefair. https://codefair.io. 

6.  codefair-app. GitHub. https://github.com/fairdataihub/codefair-app.