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

To: "John F. Sowa" <sowa@xxxxxxxxxxx>
Cc: "[ontolog-forum]" <ontolog-forum@xxxxxxxxxxxxxxxx>
From: Ed Barkmeyer <edbark@xxxxxxxx>
Date: Thu, 22 May 2008 12:33:10 -0400
Message-id: <4835A046.3030501@xxxxxxxx>
John,    (01)

you wrote:    (02)

> AS> I just wanted to share the humble results of an exercise
>  > in "convergence" which took place in the context of the
>  > last two OOPSLA workshops on domain-specific modeling
>  > http://www.dsmforum.org/events/DSM07/
> My only suggestion is to drop the word 'humble', since it is
> probably much more relevant to this forum than most of the
> notes that are posted here.    (03)

Strongly agree.    (04)

> I would agree that the philosophers use a terminology and a
> level of abstraction that is often hard to relate to practical
> applications, but many of their issues are reflected in the
> discussions we frequently have    (05)

I would agree, and add "regrettably", and stop there.    (06)

> ...
> EB> Knowledge engineering is an engineering field.  Thinking of
>  > it as fundamentally either philosophical or scientific in nature
>  > makes it more difficult for the would-be practitioner to do it well.
> I agree with the first sentence.  But the second sentence is
> misleading.  Maxwell wrote the equations for electromagnetism,
> but a great deal of the theory of how to use those equations
> was developed by electrical engineers who were trying to solve
> problems within the constraints of budgets and deadlines.    (07)

I think this would-be counterexample is actually supportive.  What the 
engineers contributed was not the advancement of the physics, but rather 
the advancement of the knowledge of how to use the physics to create 
certain valuable "devices".  But there is clearly a kind of feedback 
loop in a new technology in which engineers discover things that work, 
and things that don't, and that creates a new set of observations upon 
which the scientists can improve the theory.  In such areas, engineers 
provide a continuing flow of new observations.  I don't know that 
knowledge engineering is one of those areas.  (That is, I am willing to 
consider that an open question.)    (08)

The point I was trying to make is that engineers who think they are 
scientists get wrapped around expanding the world's collection of 
knowledge instead of building a valuable device.  And they treat 
failures as providing new knowledge (which it usually isn't), as opposed 
to providing experience.    (09)

The function of knowledge engineers is not to create new knowledge, or 
even to create new insights.  It is rather to capture the knowledge that 
other experts have in a form useful to some "application".    (010)

Most of the biomedical ontology work is motivated by a need to provide 
the thousands of bio-researchers with a means of finding out what other 
bio-researchers have already done!  That is the driving application 
(although there are others).  The function of the bio-ontologists is not 
to understand the field better; it is to give the experts the tools by 
which they may come to understand the field better.    (011)

Yes, there is a need for the ontologist to acquire some expertise in the 
field, in order to do his/her job.  And Yes, there are people who become 
experts at both.  The trick is to recognize which expertise is needed 
when and apply it properly.  But if every knowledge engineer thinks that 
s/he must become, or even worse that s/he already is, an expert in the 
subject matter, s/he will be less effective in his/her job!  Like a data 
modeler, the job is to capture what the experts say, and validate the 
models with them.  In that role, his/her own understanding of the field 
is primarily directed toward
  - recognizing the same knowledge phrased differently, and
  - asking intelligent questions
The value s/he adds is the skill (and insight) in getting the expert 
knowledge into a system with limited expressiveness and other limitations.    (012)

I have seen scientists become knowledge engineers, even to the extent of 
dropping behind the knowledge curve in their own field.  But I have 
never seen a knowledge engineer become a scientist!  (Interestingly, I 
have seen fewer corporate analysts become data modelers, and I have seen 
data modelers become valuable corporate analysts.  And in a stint with 
the U.S. Postal Service, I came to understand that the reason for that 
is that it is no one else's job to talk to every business unit manager, 
and the expertise can be acquired in only that way.)    (013)

-Ed    (014)

"The trick is to glean from an experience exactly the knowledge that is
contained in it.  A cat which sits down on a hot stove will never do it
again, but it will never sit on a cold stove again either."
        -- Mark Twain    (015)

Edward J. Barkmeyer                        Email: edbark@xxxxxxxx
National Institute of Standards & Technology
Manufacturing Systems Integration Division
100 Bureau Drive, Stop 8263                Tel: +1 301-975-3528
Gaithersburg, MD 20899-8263                FAX: +1 301-975-4694    (016)

"The opinions expressed above do not reflect consensus of NIST,
  and have not been reviewed by any Government authority."    (017)

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