At rOpenSci we’re continually grateful for the support and engagement of our community who help make our open-source ecosystem stronger, more inclusive, and more collaborative. The software peer review program is one of the best examples of this: bringing together people from diverse expertise and backgrounds to improve the quality, reproducibility, and usability of scientific software across the R ecosystem.

Today we’re excited to welcome Natalia da Silva and Andrew Heiss as new editors for our Statistical Software Peer Review team. Their expertise and dedication will help grow and sustain this important program, ensuring that statistical software reviews maintain high standards and continue to improve in quality and impact.

Meet our new editors!

Natalia da Silva

Natalia is an assistant professor of statistics in the Department of Quantitative Methods at Universidad de la República in Montevideo, Uruguay (UDELAR-IESTA).
She has a Ph.D. in Statistics from Iowa State University. Her research interests include supervised learning methods, prediction, exploratory data analysis, statistical graphics, reproducible research, and meta-analysis. She has developed some R packages like PPforest, PPtreeExt, SpICE and colaborate in others. She has served as an Associate Editor for Reproducibility at the Journal of the American Statistical Association since 2022. She co-founded the Latinamerican Conference About the Use of R in R&D, LatinR, in 2018. She also co-founded the R-Ladies Montevideo chapter and the R User Group in Montevideo, known as GURU. She teaches courses in statistics and economy, data science with R, statistical learning and inference. Most of the courses she teaches involve coding in R at various levels.

Natalia on GitHub, Website.

I have known about rOpenSci for a long time now, but at useR! 2017 I met Maëlle. She presented a talk, “rOpenSci Onboarding System for Packages”, through which I became more interested in what rOpenSci was doing and how close they were to the software philosophy that Di Cook and Heike Hofmann were teaching us at Iowa State University at that time. At this point, I asked Maëlle if I could submit the package I was working on to be reviewed, but she told me they were not doing statistical software reviews. I’m happy that everything is moving forward, and I’m excited to help as a statistical software editor in this great community.

Andrew Heiss

Andrew is an assistant professor of public policy at the Andrew Young School of Policy Studies at Georgia State University. He has a PhD in public policy from Duke University. His research focuses on the role of civil society and international nongovernmental organizations in global politics, and his with published work spans international relations, comparative politics, public administration, and nonprofit management. He also researches applied social science methods and writes (quRan, scriptuRs), maintains (qatarcars, colourlovers), and contributes to (marginaleffects, equatiomatic) many R packages. He has also developed several Quarto extensions (hikmah-academic-quarto, quarto-wordcount, fancy-epigraphs, language-name). He teaches courses in statistics, data science, data visualization, economics, and global politics. He is also an RStudio certified instructor and Posit Academy mentor.

Andrew on website, Bluesky, GitHub

I learned about rOpenSci in 2019 when I reviewed rtweet and I loved the whole review process and how transparent and collaborative everything felt—it was a wild contrast from standard academic peer review! Since then, I’ve held rOpenSci’s package guidelines, documentation standards, and review process as a gold standard for my own work. I love the rOpenSci community and everything they do to contribute to the broader R community and open science movement and I’m thrilled to be able to join in as an editor!

About the Statistical Software Peer Review Program

rOpenSci’s software peer review program brings together volunteers to collaboratively review scientific and statistical software according to transparent, constructive, and open standards. Editors manage submissions, coordinate reviewers, and help guide packages through review to improve code quality, documentation, and usability.

This program is possible thanks to the many community members: authors submitting their packages, reviewers volunteering their time and expertise, and editors like Natalia and Andrew who help shepherd reviews and maintain a supportive process.

Get Involved

Are you considering submitting your package for review? These resources will help:

• About rOpenSci Software Peer Review;
• Browse the online book rOpenSci Packages: Development, Maintenance, and Peer Review;
• Read public software review threads on GitHub

Would you like to review packages? Fill out the rOpenSci Reviewer Sign-Up Form to volunteer to review.

Welcome again Natalia and Andrew! We’re thrilled to have you join the editorial team.