Published: June 19, 2025
Not all R packages are clearly “good” or “risky”, most fall somewhere in between. This post introduces a scoring framework to help users assess package quality, based on documentation, code, maintenance, and popularity. We also share key principles to ensure the scores are useful, fair, and adaptable to different contexts.
Published: April 7, 2025
The Litmusverse is a suite of R tools that automates the risk assessment, scoring, and reporting of R packages—supporting compliance in regulated environments. Built for use across CRAN, Bioconductor, and internal repos, it helps teams streamline package approval and maintain a production-ready R ecosystem.
Published: March 31, 2025
Wondering if your R package collection is any good? It all boils down to your risk appetite. Happy to wing it? Go for it! Need rock-solid reliability? You'll want proper validation.
Published: December 1, 2022
Data science and data engineering are incredibly cognitively demanding professions. As data professionals, we are required to leverage both our analytical/engineering skills and our interpersonal skills to be effective contributors within our organisations. In this blog, we discuss why this combination could reasonably count as an occupational hazard.
