rOpenSci News Digest, February 2026

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Dear rOpenSci friends, it’s time for our monthly news roundup! You can read this post on our blog. Now let’s dive into the activity at and around rOpenSci!

rOpenSci HQ

Strong Engagement in the Champions Program Call

The Champions Program call closed on February 23, and the response was fantastic. We received 81 Champion and 14 Mentor applications from 23 countries, with 74% of applicants proposing to develop a new package. We’re now kicking off the selection process, starting with mentors so they can support the evaluation of Champion proposals. Confirmation emails have already been sent to all applicants. Thank you to everyone who applied!

Policy Updates for use of Generative AI Tools

We published an initial blog post about planned updates to our policies and practices for use of generative AI tools in rOpenSci packages. This follows recent policy updates at both the Journal of Open Source Software and pyOpenSci. We are seeking feedback on the blog post, and on the policy changes proposed there, via this decidated GitHub issue. The blog explains our intention to permit the use of generative AI tools throughout package development, and during the review process. Our policies aim to maintain our culture of openness and transparency, and we have already started informally asking submitting authors about any use of generative AI tools.

Coworking

Read all about coworking!

And remember, you can always cowork independently on work related to R, work on packages that tend to be neglected, or work on what ever you need to get done!

Community Dashboard for your own R-Universe

Last year we published a blog post on an organization-level dashboard for all rOpenSci packages and community contributors. We have now developed the orgmetricsDashboard repository to enable anybody to deploy their own organizational dashboard directly from their R-Universe repository. The only input needed is an R-Universe “packages.json” file, and you can deploy either via GitHub actions, or a local Docker workflow. Try it out!

Software 📦

New packages

The following two packages recently became a part of our software suite:

  • Athlytics, developed by Zhiang He: An open-source computational framework for longitudinal analysis of exercise physiology metrics using local Strava data exports. Designed for personal analysis and sports science applications, this package provides standardized functions to calculate and visualize key physiological indicators including Acute:Chronic Workload Ratio (ACWR), Efficiency Factor (EF), and training load metrics. It has been reviewed by Eunseop Kim and Simon Nolte.

  • orgmetrics, developed by Mark Padgham: Metrics for your GitHub organization. Call one function to generate an interactive dashboard displaying the state of your organization.

Discover more packages, read more about Software Peer Review.

New versions

The following thirteen packages have had an update since the last newsletter: dittodb (v0.1.11), targets (1.12.0), RSelenium (v1.7.10), Athlytics (v1.0.4), pkgstats (v0.2.2), osmapiR (v0.2.5), dbparser (v2.2.1), taxize (v0.10.1), rangr (v1.0.9), wikitaxa (v0.5.0), mantis (v1.0.2), tarchetypes (0.14.0), and tidyhydat (1.0.0).

Post on dfms release: Releasing dfms 1.0: Fast and Feature-Rich Estimation of Dynamic Factor Models in R.

Software Peer Review

There are seventeen recently closed and active submissions and 4 submissions on hold. Issues are at different stages:

Find out more about Software Peer Review and how to get involved.

On the blog

Software Review

Calls for contributions

Calls for maintainers

If you’re interested in maintaining any of the R packages below, you might enjoy reading our blog post What Does It Mean to Maintain a Package?.

Calls for contributions

Refer to our help wanted page – before opening a PR, we recommend asking in the issue whether help is still needed.

Package development corner

Some useful tips for R package developers. 👀

The R Foundation on OSS

The R Foundation answered a Call for Evidence from the EU about open-source, after asking for examples of the added value of R in the public or private sectors. You can read the full response of the R Foundation, including a discussion of useful ideas for the future of R and open-source in general.

On sitrep (situation report) functions

Athanasia Monika Mowinckel wrote a post on sitrep functions: functions that help the user check their setup and provide them with useful diagnostics. The blog post includes two examples.

New version of the jarl CLI

The jarl CLI by Etienne Bacher “finds inefficient, hard-to-read, and suspicious patterns of R code across dozens of files and thousands of lines of code in milliseconds”. Read about the new features in jarl 0.4.0, like the ability to find “unreachable code”.

futurize R package

Henrik Bengtsson released futurize that allows you to parallelize execution with minimal changes to code, by simply adding a call to futurize(): y <- lapply(x, fcn) |> futurize().

On AI agents and open-source

Scott Shambaugh, an open-source maintainer, wrote about his being targeted by an AI agent after closing a PR for an issue that was intended for human newbies. Initial blog post: “An AI Agent Published a Hit Piece on Me”, Updated.

Last words

Thanks for reading! If you want to get involved with rOpenSci, check out our Contributing Guide that can help direct you to the right place, whether you want to make code contributions, non-code contributions, or contribute in other ways like sharing use cases. You can also support our work through donations.

If you haven’t subscribed to our newsletter yet, you can do so via a form. Until it’s time for our next newsletter, you can keep in touch with us via our website and Mastodon account.

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