Thanks to dwindling research budgets and the rising cost of science software, \"open science\" advocates may be succeeding at getting science to go open source. And it's thanks in part to a little-known language called R. <\/p>\n
R is free, open source statistical analysis software. Privately owned tools like MATLAB, the mathematical computing software, and SAS, the statistical tool, have historically been necessary tools in labs, much the way Microsoft Office was in offices. But the ballooning cost of the software and dwindling research budgets have prompted scientists to turn to R instead. <\/p>\n
Now a growing number of researchers have joined the R development community to create new libraries that branch away from statistical analysis and into parsing the growing quantity of scientific articles and data that find their way online. And it could change the way we do science in a major way. <\/p>\n
Today, researchers use open source software to analyze data. And the R language is the de facto enabler for this trend, thanks to its early mainstay as a statistical analysis tool within scientific circles. <\/p>\n
I first started using R back in 2005 when I was doing my PhD, and it was a very obscure language that very few people knew and that we used for statistics, says Dr. Ted Hart, a member of the core development team of the rOpenSci project, which develops R packages for scientists. <\/p>\n
Most people I knew back then used SAS. It was just a giant, old, programming language, kind of like Fortran. Its analyzed line by line and whatnot, he says. <\/p>\n
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 didnt use R] in my department. So Ive seen that growth take off, says Hart. <\/p>\n
Martin Fenner, the technical lead of the article-level metrics project at the scientific publisher PLoS, agrees. Theres just a lot of R, and everybody is just learning this as a student and is doing some sort of statistics, Fenner says. <\/p>\n
Another benefit of R is that it costs no money and requires less administrative hurdles than would be needed to obtain licenses for large software packages, like SAS or MATLAB. <\/p>\n
I work at a government agency, and I dont think I can get access to MATLAB. I would have to write a long text justifying the expense for MATLAB. And somebody says, Well you can just use this tool for free. Why are you arguing for MATLAB? says Hart. <\/p>\n
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