InfoCard and CT imagery

When I was dealing with the first years of my CS degree, I complained all the time that most of the exams were pure math: everybody kept saying that it would have been a good basis for the advanced topics, yadda yadda but I was’t so inclined to see that strategic value after days and days of calculus exercises :-). Well, years later I attended the Image Elaboration class: after few deconvolutions for correcting the infamous reversed mirror of Hubble, we met the Radon transform. THAT is a piece of beauty, which allows to transform (hence the name) a bunch of density values in a beautiful CT scan wich is now commonplace. Would I need to have passed Calculus I, Calculus II an Cybernetic to invent it or even just understand it? Definitely yes. Would a doctor need to know all that math to understand from a CT scan that my right ankle is messed up (by improper use)? That’s a resounding no, for him the CT machinery can be a magical black box as long as it works.

At the same way, knowing WS-* is useful if you want to figure out HOW InfoCard perform its magic; and without WS-* as enabler happening right now, the reach of the whole idea may be way narrower. But does the user need to know anything of it? NOPE. It’s just a perfectly natural metaphor of what is already happening IRL.
It’s like it should be: as the complexity sinks down in the platform layers, the upper levels are empowered to make more things, better, more easily.

’nuff said, in the next posts I’ll drop the philosophy routine and I’ll go in some more detail. Because some of us aren’t happy with just using things, we *want* to know how it works. Isn’t it? 😉