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Re: [ontolog-forum] Cmaps (was: (no subject))

To: "[ontolog-forum]" <ontolog-forum@xxxxxxxxxxxxxxxx>
From: york earwaker <yorkearwaker@xxxxxxxxx>
Date: Thu, 17 Apr 2008 05:31:10 -0700 (PDT)
Message-id: <613049.29104.qm@xxxxxxxxxxxxxxxxxxxxxxxxxxx>
Hi John,    (01)

Excellent article just what I was looking for. Thanks.    (02)

All the best,
York.
_________________________________________________    (03)



York Earwaker (for himself) | Rule Financial | London UK
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_________________________________________________    (04)


----- Original Message ----
> From: John F. Sowa <sowa@xxxxxxxxxxx>
> To: [ontolog-forum] <ontolog-forum@xxxxxxxxxxxxxxxx>
> Sent: Tuesday, 15 April, 2008 3:39:31 PM
> Subject: Re: [ontolog-forum] Cmaps (was: (no subject))
> 
> York,
> 
> Try Google.
> 
> > There seems to me a great deal of overlap between Context, Topic
> > and Mind maps. Is this just a na´ve conclusion? Is anyone aware
> > of any comparative studies between the three types of mapping
> > techniques and representational elements?
> 
> Type the following three phrases in quotes:
> 
> "mind maps" "topic maps" "concept maps"
> 
> That will give you 1,030 hits that mention all three.
> 
> There is also a major question about the degree of formalism.
> In my slides, I discussed the issues of systematically mapping
> informal diagrams to a formal logic:
> 
> http://www.jfsowa.com/talks/cmapping.pdf
> 
> The intro to the slides (see below) summarizes the issues.
> 
> John Sowa
> __________________________________________________________________
> 
> Concept Mapping
> 
> John F. Sowa
> 
> Abstract. The task of knowledge representation has two parts:
> the first is to analyze some body of knowledge and identify the
> relevant concepts, relations, and assumptions; the second is to
> translate the result of the analysis into some notation that can
> be processed by computer. Neither part is easy, but the first is far
> more difficult. Natural languages are capable of expressing anything
> that can be stated in any artificial language with the same level of
> detail and precision, but they can tolerate any degree of vagueness
> during the process of analysis. Artificial languages, such as the
> many variants of symbolic logic, are valuable because they do not
> tolerate vagueness, but what they say so precisely may have no
> relationship to what the author intended. The various notations
> for logic are designed to represent the final precise stage, but
> they provide no intermediate forms that can bridge the gap between
> an initial vague idea and its ultimate formalization. Natural languages
> can represent every stage from the most vague to the most precise, but
> no version of fuzzy logic or related variants can come close to the
> flexibility of natural languages.
> 
> The vagueness is not caused by natural language, but by the fact that
> people seldom have a clear idea of what they want to say before the
> analysis has been completed. Engineers have a pithy characterization
> of the phenomenon: "Customers never know what they want until they see
> what they get." Plato's dialogs illustrate the kind of analysis that
> is required. Similar dialogs are necessary when programmers or engineers
> analyze a vague wish list (also called a requirements document) in order
> to generate a formal specification. Those dialogs always take place in
> natural languages, often supplemented with hastily scribbled diagrams,
> but not in any version of logic, fuzzy or precise.
> 
> This talk discusses a range of representations from informal to formal
> and compares four notations that are being used in various stages of
> knowledge acquisition, analysis, and representation: the informal
> Concept Maps, the semiformalized Topic Maps, the formal Conceptual
> Graphs, and the formal, but highly readable Common Logic Controlled
> English (CLCE). These and other similar notations have found useful
> niches in the process of analysis and representation, but it is
> important to recognize their different characteristics and areas of
> applicability.
> 
> The following slides were presented in the track on Technology,
> Instruction, Cognition and Learning (TICL) at the AERA Conference,
> San Francisco, 10 April 2006.
> 
> 
> _________________________________________________________________
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