rseng-fair-softwarelisted

# FAIR research software Use this skill when someone wants their software to be Findable, Accessible, Interoperable, and Reusable, or when reviewing how well a project meets those principles. FAIR is a set of principles for increasing the visibility and usefulness of research to others; the data principles from 2016 now extend to software, workflows, and machine-learning projects. Treat FAIR as one subset of overall software quality: it ensures software can be discovered, understood, and rerun by others (or by the author months later), but it says nothing about whether the software is correct - pair it with testing and the other quality dimensions. Work through the four principles below. Each maps to concrete actions; recommend the ones a project is missing, and explain why each matters as you go. Many actions serve more than one principle, so a single change (good metadata, a DOI, a license) often lifts several at once. ## Make software Findable Software and its metadata must be easy to discover by humans and machines. Recommend: - Write a machine-readable description (metadata) of the software so search engines and tools can index it. Use a standard such as CodeMeta rather than an ad-hoc format, following the Research Software Metadata Guidelines. - Put the code in a public repository (for example GitHub or GitLab) and, ideally, register it in a general-purpose or domain-specific registry (for example bio.tools for the biosciences). The Awesome Research Sof