At rOpenSci, we are continually grateful for the support and involvement of our community who help us 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 with different expertise and backgrounds to improve the quality, reproducibility and usability of scientific software across the R ecosystem.
Today we are happy to welcome Natalia da Silva And Andreas Heis 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 assessments 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 the 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 graphing, reproducible research, and meta-analysis. She has developed a number of R packages such as
PPbos,
PPtreeExt,
Herb and collaborate with others. Since 2022, she has been Associate Editor for Reproducibility at the Journal of the American Statistical Association. She co-founded the Latinamerican Conference About the Use of R in R&D, LatinRin 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 economics, data science with R, statistical learning, and inference. Most of the courses she teaches involve coding in R at various levels.
Natalia does GitHub, Website.
I have known rOpenSci for a long time, but with useR! I met Maëlle in 2017. She gave a lecture, “rOpenSci Package Onboarding System”which made me more interested in what rOpenSci was doing and how close they were to the software philosophy that Di Cook and Heike Hofmann taught us at Iowa State University back in the day. At that point I asked Maëlle if I could submit the package I was working on for review, but she told me they didn’t do statistical software reviews. I’m glad things are moving forward, and I look forward to helping out in this great community as a statistical software editor.
Andreas Heis
Andrew is an assistant professor of public policy at Georgia State University’s Andrew Young School of Policy Studies. He has a doctorate in public policy from Duke University. His research focuses on the role of civil society and international non-governmental organizations in global politics, and his published work includes international relations, comparative politics, public administration, and nonprofit management. He also conducts research into applied social scientific methods and writes (Quran, writingRs), maintains (qatarcars, color lovers), and contributes to (marginal effects, equatiomatic) many R packages. He has also developed several Quarto extensions (wisdom-academic-quarto, quarto word count, fancy inscriptions, 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.
Andreas on website, Blue sky, GitHub
I heard 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 stark contrast to standard academic peer review! Since then, I have considered 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 the open science movement, and I’m glad I can participate as an editor!
About the Peer Review Program for Statistical Software
rOpenSci’s software peer review program brings together volunteers to jointly review scientific and statistical software according to transparent, constructive and open standards. Editors manage submissions, coordinate reviewers, and guide packages through review to improve code quality, documentation, and usability.
This program is possible thanks to the many members of the community: authors who submit their packages, reviewers who volunteer their time and expertise, and editors like Natalia and Andrew who help manage reviews and maintain a support process.
Join us
Are you considering submitting your package for review? These tools help:
Would you like to rate packages? Fill the rOpenSci reviewer registration form to be assessed voluntarily.
Welcome again Natalia and Andreas! We are happy that you will join our editorial team.
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