Data == knowledge! Much of the data we use, whether it be fromgovernment repositories, social media, GitHub, or e-commerce sites comesfrom public-facing APIs. The quantity of data available is trulystaggering, but munging JSON output into a format that is easilyanalyzable in R is an equally staggering undertaking.

You can find members of the rOpenSci team at various meetings and workshops around the world. Come say ‘hi’, learn about how our software packages can enable your research, or about our process for open peer software review and onboarding, how you can get connected with the community or tell us how we can help you do open and reproducible research.Where’s rOpenSci?

Introduction I never thought that I’d be programming software in my career. I startedusing R a little over 2 years now and it’s been one of the most importantdecisions in my career. Secluded in a small academic office with no oneto discuss/interact about my new hobby, I started searching the web fortutorials and packages. After getting to know how amazing and nurturingthe R community is, it made me want to become a data scientist.

For the fourth and last day of project recaps from this year’s unconf, here is an overview of the next five projects. (Full set of project recaps: recap 1, recap 2, recap 3, recap 4.) In the spirit of exploration and experimentation at rOpenSci unconferences, these projects are not necessarily finished products or in scope for rOpenSci packages.

KO: What is your name, job title, and how long have you been using R? JS: My name is Julia Silge and I’m a data scientist at Stack Overflow. I have been working in R for less than three years. KO: Wow! What were you all about before that?

For day 3 of project recaps from this year’s unconf, here is an overview of the next five projects. Stay tuned for the last recap tomorrow. (Full set of project recaps: recap 1, recap 2, recap 3, recap 4.) In the spirit of exploration and experimentation at rOpenSci unconferences, these projects are not necessarily finished products or in scope for rOpenSci packages.

As part of our series summarizing all projects from this year’s unconf I’m excited to dive into all the security related offerings from this year.

After Stefanie’s recap of unconf18, this week the blog will feature brief summaries of projects developed at the event: each day 4 to 5 projects will be highlighted. (Full set of project recaps: recap 1, recap 2, recap 3, recap 4) In the following weeks, a handful of groups will share more thorough posts about their work.

We held our 5th annual unconference in Seattle, May 21-22, 2018 at Microsoft’s Reactor space. Researchers, students, postdocs and faculty, R software users and developers, and open data enthusiasts from academia, industry, government, and non-profits came together for two days to hack on projects they dreamed up and for an opportunity to meet and work together in person.

Our onboarding processensures that packages contributed by the community undergo atransparent, constructive, non adversarial and open review process.Before even submitting my first R package to rOpenSci onboarding systemin December 2015, I spent a fair amount of time reading through previousissue threads in order to assess whether onboarding was a friendly placefor me: a newbie, very motivated to learn more but a newbie nonetheless.I soon got