The Nature of eScience

by Ian Foster on December 8th, 2006

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.

[From http://ianfoster.typepad.com/blog/2006/12/the_nature_of_e.html] _uacct = “UA-686198-1″; urchinTracker();

Open Source Problem Solving in Science

by Ian Foster on December 3rd, 2006

Linus’ Law according to Eric S. Raymond: “given enough eyeballs, all bugs are shallow.” In other words, if a large enough community of users and developers has access to (and is using) your source code, even subtle problems will be identified and resolved quickly.The use of the Internet to create a “massively parallel human problem-solving system” is a powerful concept, as evidenced by such phenomena as the blogger as a source of news, wikipedia as a source of information, and advertising campaigns that solicit user-generated spots. (For more examples, see Jeff Howe’s writings on crowdsourcing.)

Now Karim Lakhani of Harvard Business School is looking into whether such techniques can be applied to scientific problems. From a recent article (and interview):

In a perfect world, scientists share problems and work together on solutions for the good of society. In the real world, however, that’s usually not the case. The main obstacles: competition for publication and intellectual property protection.

…

What [Karim Lakhani] and his coauthors discovered: “broadcasting” or introducing problems to outsiders yields effective solutions. Indeed, it was outsiders—those with expertise at the periphery of a problem’s field—who were most likely to find answers and do so quickly.

He cites a few intriguing examples, including both more traditional “competitions” (with prizes) that have yielded novel solutions, and also more novel approaches such as MathWorks’ collaborative programming contest. I am also reminded of NASA’s involvement of the general public in analyzing image data from its comet return mission (StarDust@home), and of the nice work at CMU on enlisting people (under the guise of a game) to tag photos. I suspect that there is much much more to be done here.

(From http://ianfoster.typepad.com/blog/2006/12/open_source_pro.html.)