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[ontology-summit] PLEASE, PLEASE!!

To: Ontology Summit 2007 Forum <ontology-summit@xxxxxxxxxxxxxxxx>
From: Nicola Guarino <guarino@xxxxxxxxxx>
Date: Mon, 5 Mar 2007 22:48:36 +0100
Message-id: <A5E7ABE6-E691-4D26-BA14-5D7B0ADEEB78@xxxxxxxxxx>
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:

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

web site:  http://www.loa-cnr.it




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