You can also look at Datamaster plugin for Protege that takes a relational
database and generates an ontology. (01)
Cecil (02)
-----Original Message-----
From: ontology-summit-bounces@xxxxxxxxxxxxxxxx
[mailto:ontology-summit-bounces@xxxxxxxxxxxxxxxx] On Behalf Of Arun
Sent: Wednesday, March 02, 2011 12:50 PM
To: Steve Ray
Cc: 'Ontology Summit 2011 discussion'
Subject: Re: [ontology-summit] An example of the worth of ontology
development (03)
Thanks Steve! (04)
I hope to hear of others - perhaps any that would do something like read
an S&T journal and spit out an ontology or if anyone is working on
something like that. (05)
-Arun (06)
On 3/2/11 3:38 PM, Steve Ray wrote:
> I'd say one of the closest tools to that is the Anzo tool from Cambridge
> Semantics, that takes an Excel spreadsheet and gives you a first cut at an
> ontology.
>
> Steven R. Ray, Ph.D.
> Email: steve@xxxxxxxxxxxx
> Phone: (650) 587-3780 (CA)
> (202) 362-5059 (DC)
> Cell: (202) 316-6481
>
> -----Original Message-----
> From: ontology-summit-bounces@xxxxxxxxxxxxxxxx
> [mailto:ontology-summit-bounces@xxxxxxxxxxxxxxxx] On Behalf Of Arun
> Sent: Wednesday, March 02, 2011 12:32 PM
> To: Ontology Summit 2011 discussion
> Subject: Re: [ontology-summit] An example of the worth of ontology
> development
>
> Does anyone have any tools that go from raw data to produce Ontologies
> as output or even proto-ontologies as outputs that humans can then edit
> and refine?
>
> On 3/2/11 12:50 PM, Jack Ring wrote:
>> 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).
>> Ways of accomplishing intelligent enterprise systems architecting and
> engineering are being evovled.
>> 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.
>> 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.
>> Make sense?
>>
>> On Mar 2, 2011, at 10:10 AM, John F. Sowa wrote:
>>
>>> 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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