In the Spring 2012 issue of Arts & Sciences Magazine, Mike Field tackles the topic of Big Data—that is, how do we manage the staggering amount of information begin collected and generated every day, by deep-ocean sensors measuring water temperature and salinity, by underground devices detecting soil moisture and carbon dioxide levels? And more importantly, what can we learn by studying this immense data reservoir, by slicing and dicing it in new and unexpected ways?
In an era when you can ask your phone to get you to the nearest pizza parlor and tell your car to parallel park itself, whole battalions of remote digital sensors hardly seem like news. Until you take all the millions of data points they are collecting and start finding ways of connecting them. Assembled randomly they are nothing more than the visual equivalent of white noise. But ask the right questions—and use the right kind of computational approaches and equipment that are being pioneered at Johns Hopkins—and that field of static turns into a picture like a Seurat painting. None of the millions of data points carries meaning by itself, but read together, it does. This is the new approach to research that is beginning to permeate science, across every discipline.
Says Thomas Haine, a professor in the Department of Earth and Planetary Sciences: "Just simply having access to large data sets and more information doesn't lead to improved knowledge. It needs to be digested in ways that are not very obvious. We need new creative ways to understand and analyze data sets. It's a very important challenge."
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