From Peer Review to Mentorship: My rOpenSci Story

Getting Involved with rOpenSci

I first came to rOpenSci in 2022, though at the time I barely knew what it was. I was getting a statistical package of mine ready to submit to the Journal of Statistical Software, and that is how I was pointed toward rOpenSci review: the journal directs authors to rOpenSci’s statistical software standards, so going through the review looked like a convenient step along the way. At the time, my focus was on polishing the software for the journal submission, not on rOpenSci itself.

What I did not expect was how much the process itself would change my perspective. Coming from an academic background, the open review on GitHub felt very different from the closed, anonymous process I was used to. It was rigorous without being adversarial. An editor and two reviewers carefully examined the package, and their feedback was constructive and grounded in rOpenSci’s well-defined standards and guidelines. The review improved the package, and it also gave me a greater appreciation for the collaborative approach behind open-source software review.

I was later invited to review a package myself. The experience gave me a different perspective on the review process. As a reviewer, I saw that the goal was not simply to determine whether a package met some standards or merits, but to help authors improve their software through constructive feedback. When applications opened for the Champions Program, mentoring felt like a natural next step. Having experienced rOpenSci as both a software author and a reviewer, it seemed like a meaningful way to contribute to the community.

Mentoring in the Champions Program

I was matched with Sunny Tseng as her mentor. Over the program, Sunny built bbsTaiwan, an R package that makes Taiwan’s Breeding Bird Survey data much easier to access and analyze. It was a real package solving a real problem for people who study Taiwan’s birds, which made it a pleasure to work on together.

Mostly, what I gave was time and attention. We worked through package scope, unit testing, version control, and the other practical aspects of building an R package. Many of our conversations were not about solving a particular technical problem, but about discussing trade-offs, identifying useful resources, and thinking through the next steps. Those conversations ended up being one of my favorite parts of the program.

What I valued most, though, was seeing how Sunny’s work was used after the project. It is easy to think of a package as code made available for others to use, but in this case it became a tool that supported people working with the same data. While visiting Taiwan, she also ran a session introducing it to members of that community. This reinforced my view that open-source software is not just code shared in public, but a way of bringing people together around shared work.

Looking Back

More than anything, my time with rOpenSci has left me with an appreciation for how thoughtfully it is run. Its initiatives, from peer review to mentorship, are organized with real care, and they are built to do more than improve software. They are designed to connect people, bring contributors together, and keep community at the center of open science.

Fifteen years in, what strikes me about rOpenSci is that it has always been more about people than about packages. What began as a convenient step on the way to a journal turned into one of the more rewarding parts of my work, and I have found value in each perspective I have seen as an author, a reviewer, and a mentor.