And finally, we end our series of unconf project summaries (day 1, day 2, day 3, day 4).mwparser Summary: Wikimarkup is the language used on Wikipedia and similar projects, and as such contains a lot of valuable data both for scientists studying collaborative systems and people studying things documented on or in Wikipedia.

Continuing our series of blog posts (day 1, day 2, day 3) this week about unconf 17.cityquant Summary: The goal with the cityquant project was to build a digital dashboard for sustainable cities. They also had a “spin-off” project called selfquant to get data from a quantified self google sheets template to keep track of weekly performance in various categories.

Continuing our series of blog posts (day 1, day 2) this week about unconf 17.available Summary: Ever have trouble naming your software package? Find a great name and realize it’s already taken on CRAN, or further along in development on GitHub? The available package makes it easy to check for valid, available names, and also checks various sources for any unintended meanings.

Following up on Stefanie’s recap of unconf 17, we are following up this entire week with summaries of projects developed at the event. We plan to highlight 4-5 projects each day, with detailed posts from a handful of teams to follow.checkers Summary: checkers is a framework for reviewing analysis projects. It provides automated checks for best practices, using extensions on the goodpractice package.

Following up on Stefanie’s recap of unconf 17, we are following up this entire week with summaries of projects developed at the event. We plan to highlight 4-5 projects each day, with detailed posts from a handful of teams to follow.skimr Summary: skimr, a package inspired by Hadley Wickham’s precis package, aims to provide summary statistics iteratively and interactively as part of a pipeline.

We held our 4th annual unconference in Los Angeles, May 25-26, 2017. Scientists, 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 to give our online community an opportunity to connect in-person. The result?

As all other types of visualization, linguistic mapping has two main goals: data presentation and data analysis.

On 21-22 April, the London School of Economics hosted the Text Analysis Package Developers’ Workshop , a two-day event held in London that brought together developers of R packages for working with text and text-related data.

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

There’s a lot of work that goes in to making software: the code that does the thing itself, unit testing, examples, tutorials, documentation, and support. rOpenSci software is created and maintained both by our staff and by our (awesome) community. In keeping with our aim to build capacity of software users and developers, three interns from our academic home at UC Berkeley are now working with us as well.