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BTW to the original poster: a better place to
ask this question would be one where the ontology
experts hang out. One such list is the
Conceptual Graphs list. cg@cs.uah.edu
Code lists are a productive place to start.
This seems easy, but it isn't although it is the
easiest of the problems once one gets past the
syntax and terms of the semantic web app itself.
Industry lists have been around for years. Getting
those into formats that are readily processable is
a step in the right direction. Then 'to do what?'
Local doesn't always mean 'in our shop'. An industry
is a locale of sorts. The mushiness is domain overlap.
For instance, we sell systems with jail commissaries.
Some of the terminology is local to the 'jail business'
but the items sold are items obtainable in most
commercial stores. Then there are some items which one
would only see in a detention or corrections facility
but are nonetheless, items one obtains at the jail.
This sorting of the domains if done well can provide
good code lists, but then one implements say a dropdown
that has members from multiple codelists. Domain
overlap (a domain subsuming multiple domains with
some common members and slightly different definitions)
and domain leakage (a member that is adopted from one
domain into another with not so small differences in
definition but the assumption of equivalence) are a
part of the semantic drift problem.
If the semantic web has one very large hurdle, it is
the very dynamic nature of meaning with regards to
changing intent. Do the best you can but no one
can make time or meaning stand still. YMMV.
len
From: Jeff Rafter [mailto:lists@jeffrafter.com]
> 3) Your thoughts on the Complexity of the current ontology expression
> languages like OWL, DAML+OIL etc.
Actually, in the MISMO (Mortgage Industry Standards Maintenance
Organization, which is the agreed upon standards body in the United
States for Mortgage Technology) working groups this has been coming up
quite a bit. In its standards process MISMO maintains a data dictionary
of terms that work across the industry, as well as a variety of
structures (grouped in process areas and transactions) where these terms
are used.
It seems like a perfect candidate for a top down approach of semantic
description, possibly via OWL. To be honest on a macro level the problem
seems tenable-- much like the examples floating around the web of the
Wineries and wines, it seems like it would be pretty simple to develop a
strategy for describing the data-points, and ultimately the way in which
they can/should be used (even on a process/transaction basis). Maybe
that is because I mentally skipped some things that were important to
understand...
But as Michael said, there is a lot of resistance to terminology--
ontology, description logics, KR, etc.-- and we don't have enough
experts from that domain (i.e., I am not an expert in that domain).
There is also an ingrained need for ROI. Unfortunately, predicting ROI
in this space is difficult because of a lack of visible successes. It
would help if the media stopped focusing on what-if and started focusing
on what-happened.
But ultimately it strikes me that the solution is somewhere in between
the top-down and bottom-up approach. It would be really great if
industry organizations such as MISMO created ontologies for their space
and people could interact with them using their own local definitions
and mapping them together using equivalence classes. Especially in the
mortgage industry, if interfacing with a business partner was simply a
matter of identifying like terms, and structure was invisible, then I
think we will have made incredible progress. If you can eliminate the
need for a programmer who understands the esoteric terms of the industry
and enable the business experts to identify terms you will greatly
reduce the time and money spent interfacing.
Perhaps this is a limited or wrong view of the Semantic Web. But it is a
small step.
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