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Reading  this morning stimulated some thoughts ...
"The reductionist approach [involves] dissecting the world into the
smallest and simplest pieces you can. You look for the solution of some
more or less idealized set of problems, somewhat divorced from the real
world, and constrained sufficiently so that you can find a solution."
As I read this it occurred to me that the RDFS and OWL approach is
reductionist. That is, you take the existing world, break it up into
pieces, and then document the relationship of those pieces. This
documentation of relationships constitutes the "semantics" of those
For example, consider the camera domain. An OWL ontology will break up
this domain into pieces such as Camera, SLR, aperture, f-stop, etc. And
then it will relate those piece like this:
- SRL is a type of Camera
- aperture is synonymous with f-stop
But is it reasonable to treat semantics with such a sterilized,
"The real world demands ... a more holistic approach. Everything
affects everything else, and you have to understand the whole web of
I will argue here that semantics must be approached from a holistic
approach (i.e., a complex systems approach).
Consider the Camera example above. Is aperture really synonymous with
f-stop? I have received many emails from physicists telling me that it
is not. (Characterisitic of a true reductionist I ignored their
objections saying that such differences were inconsequential/noise.)
Yet, if I walk into a camera store the salesperson will use the terms
aperture and f-stop interchangeably. The lesson that I learn from this
is that the semantics of aperture and f-stop are quite interconnected
with, and impacted by other domains such as optics, physics,
mathematics, and the economy.
There may be untility to treating semantics with a sterilized,
laboratory approach. Certainly if this was the 17th century, where
computers weren't available, then such a static, taxonomy-like approach
would be acceptable. But in today's dynamic, computer-driven world
surely we can do better ... much better.
I believe that Didier and Mike Champion made mention of Google as tool
which provides semantics in a holistic fashion. I found their
statements extremely enlightening I totally agree with them. Yes, I
think that Google is the best semantics tool today.
While Google provides semantics in a holistic fashion, it is more or
less semantics for eyeballs, i.e., the results it returns is intended
for humans to process. The critical problem is how to create a tool
which provides semantics in a holistic fashion *for computers*. Would
someone care to take a stab at characterizing the nature of such a tool?
 Complexity by M. Mitchell Waldrop, p. 60-61