The commonly accepted definition of research software is "Any software created during the research process or for a research purpose". It can come in many format and could be developed for different applications such as artificial intelligence (AI)/machine learning (ML) models with Python, data visualization tools with Jupyter notebook, or data analysis code with R.

The FAIR (Findable, Accessible, Interoperable, Reusable) Principles for Research Software (FAIR4RS Principles) are a set of high-level instructions established by the research software community to make software reusable. Making research software FAIR means complying with each of the 17 FAIR principles.

We developed the FAIR-Biomedical Research Software (FAIR-BioRS) guidelines so it is easier for researchers to make their software compliant with the FAIR4RS Principles. However, it still requires time and effort to do so, especially when software is frequently updated and has multiple contributors

Just install codefair from the GitHub marketplace on your software’s GitHub repository. By communicating with you through GitHub issues and submitting pull requests, codefair will then make sure that your software follows best coding practices, provides metadata in standard format, includes a license file, and much more to align with the FAIR4RS principles.