Making Research Software Citable & Discoverable

This presentation addresses a fundamental challenge in modern research: ensuring that research software is findable, accessible, interoperable, and reusable (FAIR). Presented at UC Love Data Week 2026, this educational resource guides researchers through practical steps to overcome the "works on my machine" trap and the bus factor problem—situations where code exists only on one person's laptop and disappears when that person is unavailable. The workshop introduces the FAIR Principles for Research Software (FAIR4RS), which adapt the widely adopted FAIR data principles specifically for software. Participants learn how to: Make software Findable: Create persistent identifiers (DOIs), generate CITATION.cff files, and provide rich metadata that makes software discoverable by others Ensure Accessibility: Share code through public repositories (GitHub) and archival platforms (Zenodo) using standard protocols Enable Interoperability: Document dependencies, use standard formats, and create reproducible computational environments Support Reusability: Apply appropriate open source licenses, write comprehensive documentation (README files), and manage software environments The workshop includes three main instructional sections: software licensing (Karla Padilla/Reid Otsuji, UCSD), environment management (Leigh Phan, UCLA), software citation and preservation (Tim Dennis, UCLA), and documentation (Reid). Real-world examples demonstrate best practices, including the Spack package manager as a model of production research software done right. Target audience includes researchers who write code, research software engineers, graduate students, data librarians, and anyone interested in improving the reproducibility and impact of computational research. No prior experience with software publication is required. Materials include presentation slides, hands-on exercises, and links to additional resources for implementing FAIR4RS principles in research workflows.