To give you an idea of where I am in my R developer germination, I’d just started reading about testing when I received an email from @rOpenSci inviting me to review the weathercan package. Many of us in the R community feel like imposters when it comes to software development. In fact, as a statistician, it was a surprise to me when I was recently called a developer.

I love working with R and have been sharing the love with my friends and colleagues for almost seven years now.

rOpenSci is holding our annual staff and leadership meeting in Vancouver, so we’re taking the opportunity to share what we do and, if you’re interested, how you can get involved. Join us for a series of 7 short talks and demos followed by informal networking over snacks & refreshments. rOpenSci is a non-profit initiative that promotes open and reproducible research using shared data and reusable software.

[This interview occurred at the 2017 rOpenSci unconference] SK: I’m Sean Kross, I’m the CTO of the Johns Hopkins Data Science Lab. Today I’m interviewing Julia Stewart Lowndes. Julia, what is your current preferred job title? JSL: I’m calling myself a marine data scientist - I’m the Science Program Lead for the Ocean Health Index.

For a fifth year running, we are excited to announce the rOpenSci unconference, our annual event loosely modeled on Foo Camp. rOpenSci unconferences have a rich history. You can get a feel for them by reading collected stories about people and projects from unconf17.

The drake R package is a pipeline toolkit. It manages data science workflows, saves time, and adds more confidence to reproducibility. I hope it will impact the landscapes of reproducible research and high-performance computing, but I originally created it for different reasons. This post is the prequel to drake’s inception. There was struggle, and drake was the answer. Dissertation frustration My dissertation project was intense.

We’re very pleased to be introducing someone who needs no introduction in the R community.

One of the best things about learning R is that no matter your skill level, there is always someone who can benefit from your experience. Topics in R ranging from complicated machine learning approaches to calculating a mean all find their relevant audiences. This is particularly true when writing R packages.

[This interview occurred at the 2017 rOpenSci unconference] KO: What is your name, job title, and how long have you been using R? KR: My name is Karthik Ram I’m a research scientist at the University of California, Berkeley. I’m an ecologist by training but have been working in the ‘data science’ space for 15 years. My real introduction to R was during my PhD when I was a teaching assistant for an engineering class on data analysis.

Join our Community Call on Tuesday, January 30th (January 31 for our Australian friends) Nick Golding, 2017 rOpenSci Fellow, will talk about two R packages he has developed recently. zoon aims to promote open and reproducible research in ecological modeling by helping researchers share their code in a modular way and produce reproducible research artifacts.