Last Thursday we held a Community Call discussing how to set up a Package to Foster a Community. This call included speakers Maëlle Salmon, Hugo Gruson and Steffi LaZerte, and was moderated by Stefanie Butland. Summarizing the community call Scientific software development - and with that R packages - is a community effort.

A week ago we held a Community Call discussing rOpenSci Statistical Software Testing and Peer Review.This call included speakers Noam Ross, Mark Padgham, Anna Krystalli, Alex Hayes, and John Sakaluk.

A new R-package, coder, has been developed, peer-reviewed by rOpenSci, accepted by CRAN, and published in a paper by the Journal of Open Source Software (JOSS). In this blog post, I will explain why this package might be useful for (epidemiological/medical/health care related) research. Clinical mess Once upon a time, in countries not far from ours, there were MDs and nurses making up funny names for any diseases they encountered.

Make ¹ -like pipelines enhance the integrity, transparency, shelf life, efficiency, and scale of large analysis projects.With pipelines, data science feels smoother and more rewarding, and the results are worthy of more trust. targets install.packages("targets") The targets ² package is a new pipeline toolkit for R.It recently cleared software review, and it is now on CRAN.

Many people in our community actively contribute to rOpenSci projects.

In this post I will explain the history behind BaseSet then a brief introduction to sets, followed by showing what you can do with BaseSet.

The rOpenSci community is supported by our Code of Conduct with a clear description of unacceptable behaviors, instructions on how to make a report, and information on how reports are handled. We, the Code of Conduct Committee, are responsible for receiving, investigating, deciding, enforcing and reporting on all reports of potential violations of our Code.

Our community is our best asset. It’s so important to us, it’s in our mission statement. We recognize that communities are not inclusive by default; they require deliberate attention, including an enforceable Code of Conduct. rOpenSci is committed to providing a safe, inclusive, welcoming, and harassment-free experience for everyone.

In a year where it has been hard to pay attention to anything not critical to our day-to-day lives, you have continued to share your time, expertise, enthusiasm, and willingness to try things with us. Our staff of developers, researchers, and community builders work to create technical and social infrastructure to lower barriers to working with research data, and you, our community, continually help us push farther.

Introduction Few months ago, I embarked on a full stack spatial data project at work. The project kicked off amazingly, until I was almost backed to the wall when I discovered that some of the data sources were served via a GraphQL API. Before now, I haven’t worked with GraphQL. But, I have heard a lot about it and how amazing it is for querying data.