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Monday, September 03, 2007
"Doing Much More Than We Have So Far Attempted" - Donald J. Waters, EDUCAUSE Review
The broadening deployment of computer-based data-conversion and data-capture instruments and sensors has greatly expanded the scale of humanistic, social, and scientific data for scholars to digest. The Sloan Digital Sky Survey is one example of this expansion; the Google library project is another. Although the systematic exploration of large quantities of information is not a new scholarly practice, what does seem new is the formalization of the very traditional interpretive activities of data-mining, pattern-matching, and simulation in powerful algorithms that represent large and complex sets of data in terms of multiple features and variables that can be analyzed, tested, replicated, and changed at the scale and speed afforded by advanced computation.
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