Working together to push science forward
Happy rOpenSci users can be found at
We mean it. On behalf of rOpenSci, thank you to everyone who has contributed their creativity, curiosity, smarts, and time in the last year. We are fortunate to have paid staff who work to build technical and social infrastructure to lower barriers to working with research data. But it is our community, built on trust, that binds us together and helps us see who we are working for. Many people have submitted their R packages for software peer review (31)1, reviewed those packages (~60), contributed some code or documentation to a package (117 people made their first code contribution to rOpenSci this year), (co-)authored a blog post or tech note about their package or an rOpenSci resource (48 authors), shared a use case to help package authors see how their work is being used and help other users imagine how they can apply it (26 people), attended a Community Call (331 people in 23 countries), cited our software (306 citations of 122 packages), asked or answered questions, explored project ideas, or gave us a generous shoutout in a talk, a post, or on Twitter....
Want to get some hands-on insights into running an open source community? Here’s an opportunity to work with me, rOpenSci’s Community Manager, on some non-code community-related work. I am looking for someone to work 1 day a week for 12 to 14 weeks. Working alongside rOpenSci’s Community Manager, Stefanie Butland, you will use guidelines and checklists to help run some of our established programs like our Blog and Community Calls. Tasks include:...
🔗 rOpenSci HQ rOpenSci Announces a New $896k Award From The Gordon and Betty Moore Foundation to Improve the Scientific Package Ecosystem for R. We’re excited to announce a new member of our team! Introducing Mark Padgham, rOpenSci’s new Software Research Scientist NumFOCUS recognizes Melina Vidoni and Will Landau for their contributions to rOpenSci. Videos, speaker’s slides, resources and collaborative notes from our Community Call on Testing in R are posted....
How we corrected URLs in our website source (broken internal and external URLs, shortlinks, http scheme, etc.) using R tools (crul::ok(), commonmark, etc.) and some manual work.
Testing is a crucial component to any software package. Testing makes sure that your code does what you expect it to do; and importantly, makes it safer to make changes moving forward because a good test suite will tell you if a change has broken existing functionality. Our recent community call on testing is a nice place to get started with testing. One way to make testing even harder is through including HTTP requests....
Happy rOpenSci users can be found at