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   RE: Beyond Ontologies

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Roger, I like your table; good contrast between machine intelligence and
human intelligence. 


Bruce B. Cox
SA4XMLT
USPTO/OCIO/AETS
703-306-2606


-----Original Message-----
From: Roger L. Costello [mailto:costello@mitre.org] 
Sent: Sunday, September 28, 2003 4:22 PM
To: xml-dev@lists.xml.org
Subject: Beyond Ontologies

Hi Folks,

I think it is clear that except for trivial, academic cases RDF Schema
and OWL do not have the robustness to capture the dynamically changing
nature of real-world semantics.  To do so, we must go beyond these
ontology languages.

I have compiled a somewhat random (chaotic) list of statements which I
feel expresses much of what has been discussed:

- Ontology languages such as RDF Schema and OWL provide the ability to
*statically* capture semantic relationships.

- Semantics is constantly changing.  All of life is constantly changing.
In fact, change is the only constant.

- Capturing in an ontology constant change would require massive,
full-time ontology maintenance.

- The Zen art of mindfulness teaches how to see life (and change) as it
really is by being "here and now".

- The technology equivalent to the Zen art of mindfulness *may* be to
continuously sample communications.  That is, keep up with evolving
semantics by continuously sampling real communications.  Then apply
heuristic and statistical techniques to deduce semantics.

This table attempts to contrast what ontologies provides today vice what
is required:

Ontology                    Beyond Ontologies
-----------------------------------------------
Equilibrium, stability,     Structure, pattern,
static, deterministic       self-organization
dynamics

Identical resources          Resources separate
                             and different

Relationships are subtypes   Relationships are
and synonyms                 patterns and possibilities

No real dynamics in the      Semantics is constantly
sense that everything is     coalescing, decaying,
statically, declaratively    changing
expressed

Sees subject as               Sees subject as inherently
structurally simple           complex

Semantics as graphs           Semantics as high-complexity
                              science

Comments?  /Roger






 

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