The Nature of eScience

A talk by Tiejien Luo at CANS reminded me of Jim Gray's nice formulation of the evolution of science methodologies:

Thousand years ago: science was empirical, describing natural phenomena

Last few hundred years: theoretical branch, using models, generalizations

Last few decades: a computational branch, simulating complex phenomena

Today: data exploration (eScience)--unify theory, experiment, and simulation. (Data captured by instruments, or generated by simulator; processed by software; information/knowledge stored in computer; scientist analyzes database/files, using data management and statistics.)

Jim's equating of "eScience" with "data exploration" seems a little too narrow. (John Taylor, who coined the term, had a somewhat broader definition: "e-Science will refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet.") However, the growing importance of data can hardly be overstated, and Jim's perspectives are worthy of careful consideration, especially by those who think of "computation and science" as being entirely about simulation

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