rOpenSci | Our package reviews in review: Introducing a 3-post series about software onboarding data

Our package reviews in review: Introducing a 3-post series about software onboarding data

On March the 17th I had the honor to give a keynote talk about rOpenSci’s package onboarding system at the satRday conference in Cape Town, entitled “Our package reviews in review: introducing and analyzing rOpenSci onboarding system”. You can watch its recording, skim through the corresponding slides or… read this series!

🔗 What is rOpenSci onboarding?

rOpenSci’s suite of packages is partly contributed by staff members and partly contributed by community members, which means the suite stems from a great diversity of skills and experience of developers. How to ensure quality for the whole set? That’s where onboarding 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, four 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. This blog post written by rOpenSci onboarding editors is a good introduction to rOpenSci onboarding.

Technically, we make the most of GitHub infrastructure: each package onboarding process is an issue in the ropensci/onboarding GitHub repository. For instance, click here to read the onboarding review thread of my 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 such as labelling which we use to track progress of submissions (from editor checks to approval).

🔗 What is this series?

In my talk in Cape Town, I presented the motivation for and process of the rOpenSci onboarding system (with the aid of screenshots made in R using the webshot and magick packages!). I also presented a data collection and analysis of onboarding, which I shall report in three posts. The first post in the series will explain how I rectangled onboarding. The second post will give some clues as to how to quantify the work represented by rOpenSci onboarding. The third and last post will use tidy text analysis of onboarding threads to characterize the social weather of onboarding.