Hi John, (01)
I also tried the following searches, (02)
The concept map graph notation has a high degree of overlap with topic map and
mind map graph notations. (03)
Putting these three quoted terms "concept maps" "mind maps" "topic maps" in
Google, depending on the order of the terms, about 1050 results returned. (04)
My original confusion with Context in leu of Concept brought me to the
following searches with regard to an understanding of clear connection between
context and the knowledge representatin with these three graph notations. (05)
"concept maps" "mind maps" "context" get you 993 results,
"concept maps" "topic maps" "context" get you 1620 results,
"mind maps" "topic maps" "context" get you 425 results,
"mind maps" "topic maps" "concept maps" "context" get only 170 results. (06)
All the best,
York. (07)
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_________________________________________________ (09)
----- Original Message ----
> From: york earwaker <yorkearwaker@xxxxxxxxx>
> To: [ontolog-forum] <ontolog-forum@xxxxxxxxxxxxxxxx>
> Sent: Tuesday, 15 April, 2008 5:29:04 PM
> Subject: Re: [ontolog-forum] Cmaps (was: (no subject))
>
> Hi John,
>
> Thanks for the article I shall start reading it on the train on my way home
> tonight.
>
> Interestingly I get different numbers in with these search orders,
> 1050 "concept maps" "mind maps" "topic maps"
> 996 "mind maps" "concept maps" "topic maps"
> 1040 "topic maps" "concept maps" "mind maps" - and most other conbinations.
>
> All the best,
> York.
>
> ----- Original Message ----
> > From: John F. Sowa
> > To: [ontolog-forum]
> > 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 naïve 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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