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I guess the question is 'what are you trying to say/send?' My point was
supposed to be that you can say the same thing - say, a position - many
different ways, and all are equally 'good.'
But, if you've got data you've measured then yeah -- send it the way it is
-- just make sure the recipient clearly understands what you're sending.
Have I understood your perspective correctly?
[ My experience here is in exchanging data from physics experiments/
simulations, which is perhaps not a common example ;-). In that case,
problems constantly crop up when the experimenters try to 'clean' the
data for someone else's use .... ]
ian
On Tue, 7 Jan 2003, Joshua Allen wrote:
> I get very nervous about saying "just derive it" about any data. If the
> data is important, it shouldn't be derived. If it's not important,
> there is no point even talking about it or having a schema for it -- let
> each user "derive" how they want.
>
> I know it seems common sense to say "we only store Fahrenheit, since we
> can 'derive' Centigrade", but many an IT manager has been burned badly
> by that sort of common sense. There are very few exceptions to this
> rule. Data isn't math.
>
>
> > -----Original Message-----
> > From: Ian Graham [mailto:igraham@ic-unix.ic.utoronto.ca]
> > Sent: Tuesday, January 07, 2003 4:17 PM
> > To: Roger L. Costello
> > Cc: xml-dev@lists.xml.org
> >
> >
> > On Tue, 7 Jan 2003, Roger L. Costello wrote:
> >
> > > Now let's get back to the hard issues:
> > >
> > > - should there be 2 schemas, one for fundamental data and one
> > > for derived data? I will argue that there should only be
> > > one schema - the fundamental data schema. Derived data is
> > > transient and should not have its own schema. What do you
> > > think?
> > >
> > > - at what point does sharing of fundamental data become a
> > > Service of derived data?
> >
> > I honestly don't think you can always make such a distinction. SUppose
> you
> > have a set of fundamental data x, and derived data y, with the
> monotonic
> > relationship
> >
> > y = f(x),
> >
> > Then a simple transformation can make y fundamental, and x derived
> >
> > x = g(y) (g = the inverse function to f)
> >
> > So it would seem you need something to define the semantics of either
> > data model (so that interpretation is consistent), but can't really
> say
> > which one is 'fundamental'.
> >
> > Consider your example: which is more fundamental, cartesian
> coordinates
> > (x,y,z) spherical (r, theta, phy) or cylindrical (r, theta, z). The
> answer
> > is -- all of them.
> >
> > Ian
> >
> >
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