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John, it is your use of "approximation" to characterize ALL models 
without exception here that I object to. Of course, depending on 
what it in the world one is trying to represent, a model *might* 
necessarily be an approximation, especially if one is modeling 
physical phenomena that are inherently vague or (in effect) 
infinitely complex and hence which simply cannot be represented with 
100% accuracy. Consider, e.g., modeling a stochastic process or 
fluid flow by means of probability theory or differential equations. 
However, many physical situations involve, *at a desired level of 
granularity*, NO vagueness and NO intractable complexity at all, as 
in my previous example involving faculty and administrators at Texas 
A&M. Many ontologies involve this kind of sharply delineated, 
unambiguously representable information. Your diagram above belies 
this fact and suggests that models are always in some way false or 
inaccurate. It just ain't so.  (01)
Chris Menzel  (02)

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