Quite so.
That's why helping them understand their enterprise as a system, hopefully an
intelligent system, gives them the perspective to grok the strange distinctions
that ontologists need to make.
This starts with a little semantic modeling; then activity modeling of the
problematic situation (customers, markets, competitors, etc., and Their
customers, markets, competitors, etc.,); then formulating an intervention
strategy for serving unmet, even unrecognized, market needs better than can
competitors and rivals; then design/architecture of To Be enterprise; then
teasing out the infrastructure and modularization. All this must precede the
development on ontology (because ontology is a major facet of infrastructure). (01)
Ways of accomplishing intelligent enterprise systems architecting and
engineering are being evovled. (02)
Unfortunately the NOISE created by Business Process Management, Knowledge
Management, Business Rules management, Enterprise Architecture Frameworks (for
paint-by-numbers, i.e., ignorant, enterprises), etc., is precluding rapid
development of this capability. (03)
Meanwhile, there are already places that have recognized the need for
intelligent infrastructure. These are the current market targets for ontology
insertion. In general, it is any enterprise or market wherein He Who Learns
Fastest Wins. Specific examples are Military Intelligence, Business
Intelligence, Conference Management (evolving to social network interlocutor),
Learning Management (as modern education of youth is finally freed from
government intervention), and Autonomous System engagement management.
Personalized, Molecular-level medicine may become the Killer App. (04)
Make sense? (05)
On Mar 2, 2011, at 10:10 AM, John F. Sowa wrote: (06)
> Jack and Mike,
>
> I agree with that point, but I'd like to add some qualifications:
>
> JR
>> The primary purpose of a semantic model is to facilitate knowledge
>> exchange and choice making in a gaggle of humans in hopes of
>> morphing the gaggle into a system. A key usage is to inform the
>> development of an executable ontology, e.g., application software,
>> for automation of information flow and decision. Another key purpose
>> is to provide a basis for objective assessment of enterprise
>> situation (aka evidence-based management).
>
> MU
>> Yes, this is the kind of thing I'm after.
>
> The primary qualification is that the "gaggle of humans" can only
> agree on what they understand. The people who work in a field
> can all agree that a list of familiar words, as documented in
> their familiar texts, cover their familiar subject matter.
>
> But when ontologists start to axiomatize those terms in some
> arcane notation based on some arcane distinctions about
> endurants, perdurants, continuants, etc., all bets are off.
>
> John
>
>
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