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Re: [ontolog-forum] Visual Complexity

To: "[ontolog-forum] " <ontolog-forum@xxxxxxxxxxxxxxxx>
From: "tom beckman" <tombeckman@xxxxxxxxxxxxx>
Date: Wed, 7 Feb 2007 15:37:54 -0500
Message-id: <0d4801c74af7$d8c90a20$0a00a8c0@bipper>
Dear colleagues,
 
Clearly, man-made constructs such as organizations and machines are designed in an attempt to eliminate ambiguity and reduce approximation in order to better function or to operate at all. 
 
John Sowa was nice enough to share his Knowledge Soup and Analogy papers with me much earlier in this discussion thread.  As a result of reading these fine papers, I am attaching the following typology and ontology(?) for discussion.  I am an advocate for the explication of generic Knowledge Representations that not only describe concepts and their contexts, but also represent knowledge as actionable forms that can be applied to perform varied generic tasks through appropriate inferencing mechanisms.  I was hoping that this forum would at least attempt to:
  • Describe concepts as conceptual primitives or building blocks within ontologies (beyond RDF),
  • Provide alternative knowledge representations in support of defining and describing upper ontologies, and
  • Examine alternative inferencing approaches to apply and manipulate ontologies in addition to logic.
Best regards, Tom Beckman    301-920-0715
 
----- Original Message -----
From: "Pat Hayes" <phayes@xxxxxxx>
To: "Christopher Menzel" <cmenzel@xxxxxxxx>
Cc: "[ontolog-forum] " <ontolog-forum@xxxxxxxxxxxxxxxx>
Sent: Wednesday, February 07, 2007 3:04 PM
Subject: Re: [ontolog-forum] Visual Complexity

>Attachment converted: betelguese2:mthworl2 1.gif (GIFf/«IC») (000E4A31)
>
>
>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.

For the record, I agree, of course. Tarskian
models can be platonic, and can be simplified
"models" (sense 2) of reality. But they can also
be actually made up from real parts of the real
world.

>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.

Quite.

Pat
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Attachment: K Repr Taxonomy and Typing.doc
Description: MS-Word document


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