Ed Barkmeyer wrote:
> Ron Wheeler wrote:
>> I am not sure about the value of picking winners and losers.
> Well, if you don't, you spend more than half the funding on proposals
> and meetings and position papers and events like the Summit, none of
> which are _results_.
I guess that I should be more precise in my thoughts.
I am not sure that it is possible or desirable at this point in the
evolution, for any product or approach to be declared the winner.
On the other hand, I am aware that individual projects will have to
chose one set of products to work with. (01)
>> I think that too much focus is on words and not enough on software
>> What I want are better tools for building applications that are based on
>> the concepts behind the semantic web.
> I think this means "I'm not that interested in finding documents; I want
> decision support tools based on inferencing."
I am not interested in endless discussions about the nature of knowledge.
I would like to have discussions about the projects that people have
done and the tools that they have used. (02)
>> I would be happy if there were applications that actually could allow a
>> SME to easily describe the relationships between things and tools that
>> would let application developers build user friendly applications that
>> could draw reasonable conclusions based on the relationships.
> IMHO, that application of AI technologies is almost unrelated to the
> intent of the Semantic Web. And it seems to me that this is what
> "knowledge engineering" vintage 1990 was about -- decision support. So
> I would prefer not to confuse the Semantic Web with other applications
> of AI. (Others would no doubt prefer to confuse them, so as to enhance
> their probability of getting funding.)
> And the supporting AI technologies themselves are not so far advanced
> since 1990. (I'm not convinced that description logics are a great leap
> forward for anything other than information searches.) What we do have
> now is machines that are 200 times faster with searchable memories that
> are 1000 times larger, and that enables AI technologies that were
> impractical in 1990 to become useful for real decision support tools.
I am not sure that ontology can be applied to high value projects
without some elements of AI.
I am looking for intelligent agents (that are not humans - which I
think, implies artificial) that can draw actionable conclusions in
complex situations faster than humans. (03)
>> I would like a tool that will make it easy to build simulations and
>> serious games based on simple scenarios added to a base ontology that
>> describes a fair amount of the universe.
> And there lies the problem -- the technology is useless without the
> information base.
> But whose job is it to build the model of a fair amount of the universe?
> No one gets a Ph.D. for axiomatizing accepted knowledge, unless s/he
> does so in a way that demonstrates some unusual reasoning capability,
> which means that it can't be used by the commonly used reasoners. We
> prefer to grant Ph.D.s for even more technology that is useless because
> there is no information base.
> You can start with Pease's SUO or the Cyc SUO, but those are models of
> the universe from 50000 feet, which are not directly useful for any kind
> of decision support. And if you take any two efforts at useful derived
> ontologies, they are likely to be inconsistent with each other.
> Getting the axiomatic ontologies in place _is_ the great task remaining
> before us. But this Forum and I have the same problem -- we all talk
> about it instead of doing it. ;-)
The other side of the equation is the tool sets that make it easy for a
SME (Subject Matter Expert) to transfer his or her understanding of the
universe into a model. (04)
I failed to realize that the gaining of PhDs was the only goal in life.
(Too much time spent in the real world!) (05)
The SME has the job of building the model of a fair amount of the universe.
This SME might only have a high school education or junior college
degree but he is the guy most knowledgeable about the relationship
between valve 295 and the rest of the universe.
His knowledge may save a petrochemical plant as much money in one day as
a PhD makes in a lifetime and may save many more lives. (06)
The rest of us get to contribute to the background ontologies.
GoodRelations is a very nice contribution to the community. It will not
help in my example but the petrochemical industry as a whole can
certainly afford a similar investment in the chemical and process
ontologies that can be the base for work by the Process Unit 2 team of SMEs. (07)
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