Revolution Analytics Supports the R Community

July 25, 2013
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(This article was first published on Revolutions, and kindly contributed to R-bloggers)

by Joseph Rickert

Early on, Revolution Analytics realized that R is more than just a tool for statistical computing — it is also the culture that has grown up around the use of the tool. The R culture is open and inclusive, competitive but also nourishing. There is a strong sense of community that encourages contribution and growth. We very much value R’s culture and community and we are doing our best to contribute. At UserR 2013 we displayed a poster that highlights some of our contributions.


Revolution Analytics sponsors R themed conferences such as useR! and we provide financial support to local R user groups around the world.  We believe in the “live event” and face-to-face encounters. We think that the personal bonds that are forged at these meetings are a great strength of R. In addition to providing a sense of occasion, they make possible the chance meeting,  the serendipitous exchange of ideas, and occasionally the opportunity for a kind word to encourage an R beginner.

On a daily basis we do our best to keep these relationships alive, by listing R user groups on our website, tracking community events, reporting on new developments and recognizing accomplishments in our blog.

We also look outward from the R community to the world of business, finance, industry and government and promote the use of R for analytics and data analyses of all kinds. We are R evangelists and work hard to explain and promote open source R to the press, to social media and to the general population. We do our best to present R, and the R community in a way that we hope all R developers and contributors will be pleased with.

Finally, we look for ways to make technical contributions to R itself. Revolution developers have authored and continue to maintain a number of open-source parallel computing packages on CRAN.  More recently, we have funded early stage R research, such as the beginning work on bigvis, and the RHadoop project which we hope will help to help establish R as a fundamental component of “Big Data” analytics.

We would very much like to hear your ideas about how you think Revolution Analytics might continue contribute to the R community in the future — let us know your thoughts in the comments.

To leave a comment for the author, please follow the link and comment on his blog: Revolutions.

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