Software Peer Review

rOpenSci’s suite of packages is comprised of contributions from staff engineers and the wider R community, bringing considerable diversity of skills, expertise and experience to bear on the suite. How do we ensure that every package is held to a high standard? That’s where our software review system comes into play: packages contributed by the community undergo a transparent, constructive, non adversarial and open review process. For that process relying mostly on volunteer work, associate editors manage the incoming flow and ensure progress of submissions; authors create, submit and improve their package; reviewers, two per submission, examine the software code and user experience. Our system current accepts software from a variety of broadly-defined categories, including our new system for peer review of statistical software.

Technically, we make the most of GitHub infrastructure: each package software peer review process is an issue in the ropensci/software-review GitHub repository. For instance, read the software peer review thread of the ropenaq package: the process is an ongoing conversation until acceptance of the package, with two external reviews as important milestones. Furthermore, we use GitHub features such as the use of issue templates (as submission templates), and labelling which we use to track progress of submissions (from editor checks to approval).