He went on to describe a recent article in the R journal that analyzed 18 months’ worth of text from the R mailing lists and identified relationships between prominent members of the R community based on the topics they discussed. Plummer cites it as an example of R’s ability to keep up with the ever-changing notion of “data.”
“10 years ago, I would have never called such an amalgamation of text a ‘data set,’” he says. “Today, though, we find ourselves in a situation where we can elicit structure from large and complex data sets and glean meaning from it.”
Buried in this great profile of Martyn Plummer, a prolific contributor to the R platform, is a hint at one of the most profound changes in tech. It’s also a sea change that is in its early innings.
Data is transforming into information at an alarming rate. What used to be considered signal-burying noise in the data stream is now considered part of the signal itself. So, information science is very real and becoming more important. Because of this transformation occurring in conjunction with the growth of data, it is also growing exponentially faster than the pure data growth trajectory.
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