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R for Open Science

FastCompany magazine recently published an in-depth feature on Open Science, with a focus on the R language and the ROpenSci project. If you're not familiar with ROpenSci, the article gives a nice introduction from Ted Hart, a member of the ROpenSci development team: A big sea change was the need to meet digital formatting requirements of scientific data. Hart and the rest of the team have created a set of packages that enables researchers to more easily share and store their research in standardized formats. The idea is the more shareable research is, the more science will progress. This is the foundation of the open science movement. Large scientific publishers, like Nature and its forthcoming Scientific Data publication, are requiring researchers to submit their research data in specific metadata formats. Other scientific organizations also advocate pushing scientific data into various established repositories on the web in standardized formats. Some of rOpenSci’s R packages can help these scientists streamline their data formats to fit the scientific community’s data standards. Hart also described his earliest experiences with R as a PhD student in 2005: “Most people I knew back then used SAS. It was just a giant, old, programming language, kind of like Fortran. It’s analyzed line by line and whatnot,” he says. But when Hart started his post-doc in 2011, the lab where he did research only used R. “It was taught by this evolutionary biologist, Dolph Schluter. Every grad student I knew used it, as opposed to when I was a grad student. And I think I was the only one [who didn’t use R] in my department. So I’ve seen that growth take off,” says Hart. Read more about the growth of R here, and read the complete FastCompany feature at the link below. Fast Co.Labs: How The Rise Of The "R" Computer Language Is Bringing Open Source To Science

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More Stories By David Smith

David Smith is Vice President of Marketing and Community at Revolution Analytics. He has a long history with the R and statistics communities. After graduating with a degree in Statistics from the University of Adelaide, South Australia, he spent four years researching statistical methodology at Lancaster University in the United Kingdom, where he also developed a number of packages for the S-PLUS statistical modeling environment. He continued his association with S-PLUS at Insightful (now TIBCO Spotfire) overseeing the product management of S-PLUS and other statistical and data mining products.<

David smith is the co-author (with Bill Venables) of the popular tutorial manual, An Introduction to R, and one of the originating developers of the ESS: Emacs Speaks Statistics project. Today, he leads marketing for REvolution R, supports R communities worldwide, and is responsible for the Revolutions blog. Prior to joining Revolution Analytics, he served as vice president of product management at Zynchros, Inc. Follow him on twitter at @RevoDavid

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