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Re: [ontolog-forum] The concepts can change?

To: ontolog-forum@xxxxxxxxxxxxxxxx
From: John F Sowa <sowa@xxxxxxxxxxx>
Date: Tue, 17 Jul 2012 10:21:49 -0400
Message-id: <500574FD.6020606@xxxxxxxxxxx>
Ed and Ronald,    (01)

I strongly agree with both of you:    (02)

> We don't want to excuse "term migration" as "concept evolution", but we
> do have to recognize the existence of true concept evolution in science
> and engineering.  (And my concerns have nothing to do with 'social
> domains'.)    (03)

> Ed, You are right about the evolution of concepts in engineering and science.
> Our own methods were developed through the analysis of organizational systems,
> especially those specified by legal norms. That context led us to base our
> analysis on affordances and perceptual norms, which are easier (not always
> easy) to handle empirically than are concepts, which are hidden in individual
> minds.    (04)

I'd also emphasize that concept evolution occurs in every field,
including the supposedly "hard" sciences of mathematics and physics.
But you don't have to peer inside minds to see the evolution.  The
effects are visible in the way people write, talk, and act.    (05)

In a recent note (with the subject line "Large Heterogeneous Data"),
I cited the announcement of the LHD-12 workshop, which addresses
some related issues:    (06)

    http://dream.inf.ed.ac.uk/events/lhd-12/cfp.html    (07)

> The resulting formalism can be handled computationally, but from a logical
> point of view, its messiness poses problems we have not solved.    (08)

Yes.  That is the focus of the LHD workshop.  Following is an excerpt
from their CFP:    (09)

> In order to interact successfully in an open and heterogeneous environment,
> being able to dynamically and adaptively integrate large and heterogeneous
> data from the Web “on the go” is necessary. This may not be a precise process
> but a matter of finding a good enough integration to allow interaction to
> proceed successfully, even if a complete solution is impossible.
> Considerable success has already been achieved in the field of ontology
> matching and merging, but the application of these techniques - often
> developed for static environments - to the dynamic integration of
> large-scale data has not been well studied.    (010)

The complete proceedings for last year's LDH-11 is available online:    (011)

    http://ijcai-11.iiia.csic.es/files/proceedings/W23-proceedings.pdf    (012)

There are many good papers on in that collection.  I'd like to cite one
by Pat Hayes, coauthored with Harry Halpin and Henry Thompson (p. 25)    (013)

    "When owl:sameAs isn’t the Same Redux: A preliminary theory
    of identity and inference on the Semantic Web."    (014)

 From the opening paragraph:    (015)

> With the beginning of the deployment of the Semantic Web, the
> problem of identity in knowledge representation – sometimes
> assumed  trivially solved – has returned with a vengeance.    (016)

This is just one of many reasons why I keep warning people that
URIs don't automagically solve a huge host of thorny issues.    (017)

A copy below of the comment I included in my earlier note about
the LDH workshop.    (018)

______________________________________________________________________    (019)

Alan Bundy is one the people on the program committee.  He is a
pioneers in using logic and theorem proving in AI.  He hasn't given
up on logic, but he has abandoned the idea that a single, uniform,
static ontology of everything is possible.    (020)

Bundy and his students showed that even in a field as rigorous and
mathematical as physics, it's not possible to have a homogeneous
ontology.  Even for Newtonian mechanics, for which the fundamental
laws have been stable for centuries, every problem to be solved
requires a different engineering model that makes different
assumptions and approximations about the subject.    (021)

Bundy's article in LHD-11 (p. 14) summarizes their approach.
The names of their software systems indicates what they do:
GALILEO (Guided Analysis of Logical Inconsistencies Leads to
Evolved Ontologies) and ORS (Ontology Repair System).    (022)

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