Also, don't forget that the question is really "can we define a scale within
which one can place true ontologies, thesauri, folksonomies, etc.?". To answer
that, we MAY have to answer "what is an ontology". (01)
> -----Original Message-----
> From: ontology-summit-bounces@xxxxxxxxxxxxxxxx
> [mailto:ontology-summit-bounces@xxxxxxxxxxxxxxxx] On Behalf
> Of Chris Welty
> Sent: Monday, March 05, 2007 8:05 PM
> To: Ontology Summit 2007 Forum
> Subject: Re: [ontology-summit] PLEASE, PLEASE!!
>
>
> Agreed. I hear enough of this crap elsewhere, let's focus on
> ontology.
>
> -Chris
>
> Nicola Guarino wrote:
> > Folks,
> >
> > these discussions are very nice, but I don't think they are
> directly
> > related to the main focus of this list, i.e. the Ontology
> Summit 2007,
> > which is supposed to concentrate on the question "what is
> an ontology".
> >
> > I am already having a VERY hard time following the ontology summit
> > discussion, and these recent messages don't really help to keep the
> > discussion focused.
> >
> > I am afraid I have just to give up any kind of active
> presence if the
> > discussion on this list goes out of its main focus.
> >
> > Best,
> >
> > Nicola
> >
> > On 5 Mar 2007, at 22:31, John F. Sowa wrote:
> >
> >> Leo,
> >>
> >> To continue my point that efficiency *always* depends on
> what you're
> >> trying to do, I would like to address the problem of finding a
> >> consistent set of constraints:
> >>
> >>> I, as usual, recommend the
> >>> description logic complexity navigator:
> >>> http://www.cs.man.ac.uk/~ezolin/logic/complexity.html
> >>
> >> Given a set of arbitrary first-order constraints, the problem of
> >> proving consistency is NP complete. Yet every SQL
> database permits
> >> arbitrary first-order constraints.
> >>
> >> Q: How is possible to prove that the constraints are consistent?
> >>
> >> A: Trivially.
> >>
> >> The point is that no database designer *ever* begins with an
> >> arbitrary set of constraints. They *always* begin with
> some actual
> >> data -- a sample DB that shows what kind of data they
> expect to work
> >> with.
> >>
> >> That sample DB consists of a set of entities and a set of
> relations
> >> that are assumed to be true of those entities.
> >> In other words, the starting point is a Tarski-style model.
> >>
> >> Although *finding* a model is NP complete, the task of
> >> *checking* constraints is trivial, if a model is given.
> >>
> >> Given a proposed set of first-order constraints that do
> not depend on
> >> any recursive definitions -- i.e., anything expressible in
> SQL WHERE
> >> clauses -- the evaluation time in terms of a sample model
> takes, in
> >> the worst case -- polynomial time.
> >>
> >> If all the constraints turn out to be true of the model, then they
> >> are consistent. If any of them turn out to be false, either throw
> >> them away or revise them to make them true.
> >>
> >> Bottom line: If you're trying to define axioms or
> definitions for an
> >> ontology, a database, or a knowledge base, it's a good
> idea to start
> >> with at least one illustrative example.
> >>
> >> John
> >>
> >>
> >> _________________________________________________________________
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> >>
> >
> >
> >
> >
> >
> ----------------------------------------------------------------------
> > -------
> >
> > Nicola Guarino
> >
> > Editor in Chief, Applied Ontology (IOS Press)
> >
> > Head, Laboratory for Applied Ontology (LOA), ISTC-CNR
> >
> > Institute for Cognitive Sciences and Technologies
> >
> > National Research Council
> >
> >
> > mobile: +39 333 5865383
> >
> > email: guarino@xxxxxxxxxx <mailto:guarino@xxxxxxxxxx>
> >
> > web site: http://www.loa-cnr.it
> >
> >
> >
> >
> >
> ----------------------------------------------------------------------
> > --
> >
> >
> > _________________________________________________________________
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>
> --
> Dr. Christopher A. Welty IBM Watson Research Center
> +1.914.784.7055 19 Skyline Dr.
> cawelty@xxxxxxxxx Hawthorne, NY 10532
> http://www.research.ibm.com/people/w/welty
>
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> (02)
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