|To:||"[ontolog-forum] " <ontolog-forum@xxxxxxxxxxxxxxxx>|
|From:||Andreas Tolk <atolk@xxxxxxx>|
|Date:||Mon, 23 Jul 2007 21:49:10 -0400|
We just had a paper with this topic on the SCSC 2007 and another one accepted for the WSC 2007. The Modeling & Simulation world is just learning that models are purposeful abstractions of reality, which means each model has its own ontology. Federation of models needs to migrate between these ontologies, or you run into variances and inconsistencies. I attach the WSC paper for those interested.
All the best
Andreas Tolk, Ph.D.
-----ontolog-forum-bounces@xxxxxxxxxxxxxxxx wrote: -----
>To: "[ontolog-forum]" <ontolog-forum@xxxxxxxxxxxxxxxx>
>From: "John F. Sowa" <sowa@xxxxxxxxxxx>
>Sent by: ontolog-forum-bounces@xxxxxxxxxxxxxxxx
>Date: 07/23/2007 08:57PM
>Subject: [ontolog-forum] Systems that learn each other's ontologies
>Arun and Paul,
>Attached is a note that I sent to ontolog-forum.
>It presents a solution to the Knowledge Soup problem,
>which is based on some of the technology we have been
>developing. I think this is something we should write
>up as a proposal to be submitted to our usual clients.
> > There is no single way to define classes of food that works for
> > everyone and there need not be. There are many equally valid
> > options depending on the actors and the context.
> > On a practical level, not everything fits into classes.
>Or more generally, anything can be classified in an open-ended
>number of ways for different purposes -- just because different
>people have different backgrounds, habits, and viewpoints.
>An example I like to use is the Amazon.com ontology, which any
>supplier must accommodate if they want to sell anything through
>Amazon.com. For any company that supplies books, electronics,
>etc., that's a prerequisite if they want to stay in business.
>So those companies, which usually have wildly different internal
>ontologies for their databases, are forced to write mappings from
>their internal schemas to the Amazon schema. They do that, but
>it typically takes them about 6 weeks to do so.
>When people with different ontologies meet -- which means any two
>people in the world -- they seldom understand each other very well,
>and they must take some time to get acquainted, to adapt to one
>another's quirks, to negotiate, to compromise, and to *learn*
>how to map their ways of thinking to the other's.
>For interoperability, the goal must be to design our systems
>so that they can *learn* to accommodate other ontologies in
>a minimum amount of time. A system should be able to find a
>mapping from its own ontology to Amazon's, for example, in a
>few minutes -- automatically -- instead of requiring a database
>specialist to spend 6 weeks to write the mappings.
>Summary: It's incorrect to say that people with different
>backgrounds understand one another; it's more accurate to say
>that they can learn to understand one another. We can't expect
>computer systems to be smarter than we are. At best, they should
>be able to learn to do something similar.
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