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Hi Jonathan,
> I think it is clear that either we are not using the same definition for
> the term "ontology" or else you don't understand how ontologies have
> been developed and deployed for real world applications.
>
> For example:
> http://www.research.att.com/sw/tools/classic/tm/ijcai-doc.html
> http://www-ksl.stanford.edu/KSL_Abstracts/KSL-02-08.html
Yes, I am aware that there are people making good use of ontologies.
> I'm not sure how you
> arrive at your conclusion that they only capture *static* semantics.
An ontology is a "snapshot" of the relationships among entities, at a
particular moment of time. My assertion is that in "life" nothing is
constant, everything is constantly changing. So, if we wish to reflect
"life" then that snapshot ontology is out of date the moment it is created.
How do we deal with dynamically changing relationships? That's what I am
trying to address.
> >Semantics as graphs Semantics as high-complexity
> > science
> >
> >
> Err... ontologies are being used for high-complexity science, for
> example molecular biology/genomics/proteomics e.g. the NCI Ontology
> (developed in OWL), SNOMED, GALEN as well as Astrophysics e.g.
> ontologies developed for the NSF/NASA NVO project, etc. etc.
Sorry, I wasn't clear. My point here was to contrast treating semantics
using graphs (which is used to capture snapshots) vice using the field of
complex systems to capture dynamically changing relationships. /Roger
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