The rOpenSci Taxonomy Suite
What is Taxonomy? Taxonomy in its most general sense is the practice and science of classification. It can refer to many things. You may have heard or used the word taxonomy used to indicate any sort of classification of things, whether it be companies or widgets. Here, we’re talking about biological taxonomy, the science of defining and naming groups of biological organisms. In case you aren’t familiar with the terminology, here’s a brief intro.
notary - Signing & Verification of R Packages
Most of us who work in R just want to Get Stuff Done™. We want a minimum amount of friction between ourselves and the data we need to wrangle, analyze, and visualize. We’re focused on solving a problem or gaining insights into a new area of research. We rely on a rich, community-driven ecosystem of packages to help get our work done and likely make an unconscious assumption that there is a safety net out there, protecting us from harm.
The Value of #Welcome
I’m participating in the AAAS Community Engagement Fellows Program (CEFP), funded by the Alfred P. Sloan Foundation. The inaugural cohort of Fellows is made up of 17 community managers working in a wide range of scientific communities. This is cross-posted from the Trellis blog as part of a series of reflections that the CEFP Fellows are sharing. In my training as a AAAS Community Engagement Fellow, I hear repeatedly about the value of extending a personal welcome to your community members.
skimr for useful and tidy summary statistics
Like every R user who uses summary statistics (so, everyone), our team has to rely on some combination of summary functions beyond summary() and str(). But we found them all lacking in some way because they can be generic, they don’t always provide easy-to-operate-on data structures, and they are not pipeable. What we wanted was a frictionless approach for quickly skimming useful and tidy summary statistics as part of a pipeline.
Announcing the rOpenSci Fellowships Program
rOpenSci’s mission is to promote a culture of open, transparent, and reproducible research across various research domains. Everything we do, from developing high-quality open-source software for data science and, software review, to building community through events like our community calls and annual unconference are all geared toward lowering barriers to reproducible, open science. The rOpenSci Fellowship presents a unique opportunity for researchers who are engaged in open source to have a bigger voice in their communities.
