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Re: [ontolog-forum] Data Models v. Ontologies (again)

To: "[ontolog-forum]" <ontolog-forum@xxxxxxxxxxxxxxxx>
From: "John F. Sowa" <sowa@xxxxxxxxxxx>
Date: Wed, 28 May 2008 18:49:03 -0400
Message-id: <483DE15F.4040705@xxxxxxxxxxx>
Sean, Len, and Ed,    (01)

SB> If I might remind you of the traditional definition of
 > an engineer "Someone who can do for sixpence what any fool
 > can do for a shilling".    (02)

That is a variant of my preferred definition of engineering:
the art of using science to solve problems within the limits
of budgets and deadlines.    (03)

SB> Also, the yardstick of whether something is a scientific
 > theory is whether it makes testable predictions, not whether
 > it has, say, a mathematical basis.    (04)

I strongly agree with that definition.  It includes a much
broader range of work that has traditionally been called
science.  And that criterion includes the knowledge required
to build medieval cathedrals or samurai swords.  (I once knew
somebody who thought his stress calculations for a ski-lift
design were more accurate than the traditional constructions.
Fortunately, his ski lift collapsed before anyone got on it.)    (05)

LY> Engineering results in consistent scalable production, which
 > so called 'knowledge engineering' does not. And it will not until
 > it applies theories... in the above context theory does not mean
 > formal set of axioms, not does it mean some good way to predict
 > the outcome. Here it means !!!unifying!!! paradigm, like theory
 > of evolution. This is why I used plural.    (06)

I mostly agree.  But I also believe that there are suitable ways
of analyzing a large body of knowledge in a productive manner.
To avoid arguments about philosophy, I'll mention lexicography.
The editors of large, unabridged dictionaries have developed
systematic methodologies.  They organize and manage a team of
lexicographers and editors who analyze millions of citations
in order to produce a dictionary with tens or even hundreds
of thousands of definitions.    (07)

Traditional dictionaries are written in natural languages. But
with suitable tools, it would be possible to organize similar
efforts that use controlled NLs for writing the definitions
and logic-based methods for testing and relating them.    (08)

And by the way, C. S. Peirce was not only a logician, philosopher,
mathematician, physicist, astronomer, and chemist, he was also
a lexicographer.  In the 1890s, he worked as an associate editor
of the _Century Dictionary_, which was intended as a competitor
to the OED.  It was an excellent dictionary, but it wasn't as large
as the OED, and the company eventually went out of business.  As
a result, the _Century Dictionary_ went out of copyright, and its
definitions were freely copied by most of the dictionaries
published during the 20th century.    (09)

For that dictionary, Peirce wrote, revised, or edited over 16,000
definitions -- more than any other editor of that dictionary.
That experience gave Peirce's later writings deep insight into
the nature of language, logic, and their interrelationships.
Unlike many philosophers who talk about the criteria for a good
definition, Peirce had 16,000 instances of direct experience.    (010)

EB> There is also the old joke about distinguishing mathematicians,
 > scientists and engineers...    (011)

I don't like that story because it implies that the scientist and
the engineer are less competent than the mathematician (even though
I grew up as a mathematician).  I prefer the story about the three
who were asked to determine the volume of a red rubber ball:    (012)

The mathematician assumed it was a perfect sphere, measured its
diameter, and applied the formula.  The physicist filled a beaker
with water, submerged the ball, and measured the overflow.  The
engineer checked the manufacturer and model number and looked up
the specifications in a table of red rubber balls.    (013)

In this story, all three of them are competent, but they have
different ways of thinking about a problem and getting results.    (014)

John Sowa    (015)

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