the way forward: learning from our past

the context for—and computation, the practice of—com-puting in science and engineering. But isn’t this what weare doing? Our charter commits us to build communitiesof practice that cross disciplines within the sciences, en-gineering, mathematics, and computation. Are we per-haps honoring this commitment, more often than not, inits breach?

This issue offers three responses. First, its theme is mul-tiphysics modeling. Having been an experimental physi-cist for most of my career, modeling naturally brings tomind the fitting of curves to measurements and testingstatistical agreement of experiment with theory. Sure, Iread the journals and am aware that detailed modeling ofcomplex physical systems has become a big business withthe advent of relatively cheap and fast computing. Still, atthe recent SIAM meetings last July, I was unprepared forthe impact of learning about this methodology—a neatblend of computation informed by science. I promptlycollared the symposium presenters, revealing my whettedappetite and wish to learn more. The result is this themeissue of CiSE.

Second, the Education department has been “put onhold” for one issue due to a “plague of riches.” There wasone more theme article than anticipated and the Technol-ogy Reviews department contribution turned out muchlarger than could be accommodated in a single issue. In-stead, the Education department’s authors present a shortsegue into the anticipated continuation of their serial tuto-rial review of discrete Fourier transforms in the next issue.DFT’s and FFT’s ... now there’s something I thought I knewa lot about. But as often happens, the sharpness that lieswithin a comprehensive view is dulled by narrow, ritualpractice. Gradually, we learn to follow a best practice,forgetting what underlies it. Judging by the number of

download requests we received for part one of this article (itcurrently tops our list), other readers may seem to feel thesame way—or at least have a considerable interest in thissort of information.

Finally, the Technology Reviews department, after an ear-lier qualitative and introductory article, features the first ina series of heavy-duty reviews of three major scientific/engineering productivity packages—Maple, Mathematica,and Matlab. This one focuses on their use for educationalapplications. The structure and content for these experi-mental reviews comes from a wish that our departmental ar-ticles have utility, but we aren’t leaving the results to chance.We’ve also commissioned a survey to accompany this arti-cle; the intention is a “usability analysis” of if and how read-ers have actually used this article in their work.

We’re seeking the way forward and are counting on yourhelp. Please keep those cards and letters coming!

2 Copublished by the IEEE CS and the AIP 1521-9615/05/$20.00 © 2005 IEEE COMPUTING IN SCIENCE & ENGINEERING

F R O M T H EE D I T O R S

THE WAY FORWARD: LEARNING FROM OUR PAST

By Norman Chonacky

T ESTIMONY FROM PAST READERS DRIVES THIS ISSUE’S CONTENT AND AP-

PROACH. HIGH ON THEIR WISH LIST ARE A GREATER EMPHASIS ON SCIENCE

CONTENT, A MORE TUTORIAL APPROACH TO COMPUTATION, AND A STRONGER,

MORE UTILITARIAN CHARACTER. THESE ARE APPROPRIATE BECAUSE SCIENCE SETS

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