Types of ontologies?

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Erick Antezana

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May 23, 2017, 5:04:41 PM5/23/17
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Dear all,

I am sure this question has already been asked long ago; however, I was not able to find any good pointer in the ontolog archives...so here it is (possibly again): could you recommend some documentation/definitions about the types of ontologies? 

I typically develop and work on 'domain ontologies' and 'application ontologies' (in the life science arena). To some extent, I have (re)used 'upper level ontologies'... We want to review the way we name and classify those different types of artifacts. Any pointers would be highly appreciated.

I know there could be different classifications, based on specific dimensions such as expressiveness, purpose, coverage, etc. (http://www.springer.com/cda/content/document/cda_downloaddocument/9780857297235-c1.pdf?SGWID=0-0-45-1193345-p174120365). however, I was wondering whether there is any "relatively widely accepted" classification?

thanks,
Erick

 

rrov...@buffalo.edu

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May 24, 2017, 8:26:28 AM5/24/17
to ontolog-forum, Erick Antezana
It's an interesting topic. As far as I know there's isn't such a classification.
Probably because of (a) the varied views and approaches of ontology among industry, academia, gov't, and other developers and users.
One question is: would the types of ontologies differ according to each sector? E.g. is an application onto different to an industry ontologist than academia, etc.
It might also be because, as you suggested, (b) like classification in general, there can be many dimensions along which to classify.

The link you provided makes some informative points. See this paper for ideas relative to web info extraction: http://olp.dfki.de/pkdd04/labsky-final.pdf

I've seen these names: 'domain ontology', 'application ontology', 'hybrid ontology', 'reference ontology' 'foundational ontology' upper-level ontology', 'mid-level ontology', 'lower-level ontology', 'top-level ontology', 'lightweight ontology', 'heavyweight ontology', , 'interface ontology'.

The distinction between domain and application ontologies has been contested, as well as the concept of levels.
One reason to contest the former is that some given domain ontology may not actually cover the domain thoroughly to be accurately called a 'domain ontology'.
Another reason is that the given ontology might only present a conceptualization or model of the domain according to a specific group or a certain perspective, which raises the question for all domain ontologies: has there been a sufficiently diverse set views and input of the domain?
Another reason is the delineation of a domain: a domain may be demarcated in different ways, and many domains overlap.

Consider looking at other computational artifacts and see if they have classifications.
One question you can ask (and I'd be interested to hear your answer) is if the names and distinctions you've found are useful and if so/not, how/why.

Robert

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Matthew West

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May 25, 2017, 5:33:41 AM5/25/17
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Dear Erick,

It’s worth looking through the Ontology Summit Communiques. My recollection is there is at least some material there that addresses this question, at least indirectly.

 

Regards

 

Matthew West                           

Information  Junction

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Godfrey Rust

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May 25, 2017, 5:47:50 AM5/25/17
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I sense that somewhere in Borges' Library of Babel there must be book about work on the Ontology of Ontology Ontologies.

 

 

Godfrey Rust

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Doug McDavid

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May 25, 2017, 9:38:11 AM5/25/17
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Seems like the concept of 'domain' provides a commonly understood element of this meta-ontology being discussed.  It even seems, however, that we may harbor multiple referents for what we mean by, let's say, 'ontology domain'.  Should we describe domains, how they work, and how they may interrelate?  

Are these domains?
  • Accounting
  • Retail sales
  • Biomimicry
  • User interface
  • Upper ontology
  • etc.

Do they interrelate?

On Thu, May 25, 2017 at 2:47 AM, Godfrey Rust <godfre...@rightscom.com> wrote:

I sense that somewhere in Borges' Library of Babel there must be book about work on the Ontology of Ontology Ontologies.

 

 

Godfrey Rust

Rightscom Limited

+ 44 (0)20 8579 8655 

M +44 (0) 7967 963674 

www.rightscom.com   
Suite 1866, Kemp House, 152 City Road, London, EC1V 2NX.

 

 

From: ontolo...@googlegroups.com [mailto:ontolog-forum@googlegroups.com] On Behalf Of Matthew West
Sent: Thursday, May 25, 2017 10:34 AM
To: ontolo...@googlegroups.com
Subject: RE: [ontolog-forum] Types of ontologies?

 

Dear Erick,

It’s worth looking through the Ontology Summit Communiques. My recollection is there is at least some material there that addresses this question, at least indirectly.

 

Regards

 

Matthew West                           

Information  Junction

Mobile: +44 750 3385279

Skype: dr.matthew.west

http://www.informationjunction.co.uk/

https://www.matthew-west.org.uk/

This email originates from Information Junction Ltd. Registered in England and Wales No. 6632177.

Registered office: 8 Ennismore Close, Letchworth Garden City, Hertfordshire, SG6 2SU.

 

 

 

From: ontolo...@googlegroups.com [mailto:ontolog-forum@googlegroups.com] On Behalf Of Erick Antezana
Sent: 23 May 2017 22:05
To: ontolo...@googlegroups.com
Subject: [ontolog-forum] Types of ontologies?

 

Dear all,

 

I am sure this question has already been asked long ago; however, I was not able to find any good pointer in the ontolog archives...so here it is (possibly again): could you recommend some documentation/definitions about the types of ontologies? 

 

I typically develop and work on 'domain ontologies' and 'application ontologies' (in the life science arena). To some extent, I have (re)used 'upper level ontologies'... We want to review the way we name and classify those different types of artifacts. Any pointers would be highly appreciated.

 

I know there could be different classifications, based on specific dimensions such as expressiveness, purpose, coverage, etc. (http://www.springer.com/cda/content/document/cda_downloaddocument/9780857297235-c1.pdf?SGWID=0-0-45-1193345-p174120365). however, I was wondering whether there is any "relatively widely accepted" classification?

 

thanks,

Erick

 

 

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John F Sowa

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May 25, 2017, 10:54:15 AM5/25/17
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Dear Erik, Matthew, Doug McD, and Robert,

EA
> could you recommend some documentation/definitions about the types
> of ontologies?

MW
> It’s worth looking through the Ontology Summit Communiques.

Yes, but there should be a systematic directory that points to,
maintains copies of, and shows the relationships among the open-
ended variety of top levels, microtheories, and domain ontologies.

Maintaining such a directory is not appropriate for ISO.
But Part I of the proposed ISO standard should specify the
metadata and guidelines that any such directory would use.

The next step is to develop Part II of the proposed ISO standard:
a specification of some widely used top levels and microtheories,
each one described with the metadata and according to the guidelines
of Part I.

DMcD
> Seems like the concept of 'domain' provides a commonly understood
> element of this meta-ontology... Should we describe domains, how
> they work, and how they may interrelate?

Yes -- in Part I of the proposed ISO standard.

DMcD
> I was wondering whether there is any "relatively widely accepted"
> classification?

The fact that you, as a long-term subscriber to Ontolog Forum, need
to ask that question indicates a serious gap that should be filled.
That is job #1 for ISO, prior to any attempt to standardize content.

RR
> As far as I know there's isn't such a classification. Probably
> because of (a) the varied views and approaches of ontology among
> industry, academia, gov't, and other developers and users...
> (b) like classification in general, there can be many dimensions
> along which to classify.

Yes. And until we have such a classification, it's premature to
standardize any particular choice. Even with such a classification,
the ISO standard should remain neutral about any particular options.

Part II could specify and classify some widely used top levels and
microtheories. But the domain experts are the ones who should decide
which one(s) are best suited to their applications.

John

Doug McDavid

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May 25, 2017, 11:00:59 AM5/25/17
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No big deal, John, but I think you attributed something to me that I didn't say.

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John F Sowa

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May 25, 2017, 12:30:28 PM5/25/17
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On 5/25/2017 11:00 AM, Doug McDavid wrote:
> No big deal, John, but I think you attributed something to me that
> I didn't say.

I apologize if I misinterpreted anything:

> DMcD
>> I was wondering whether there is any "relatively widely accepted"
>> classification?
>
> The fact that you, as a long-term subscriber to Ontolog Forum, need
> to ask that question indicates a serious gap that should be filled.
> That is job #1 for ISO, prior to any attempt to standardize content.

In any case, the answer to that question is critical for any proposed
ISO standard. There are 30+ years of publications that specify
ontologies, applications of ontology, and various guidelines for
developing ontologies and mapping one to another.

The current proposal starts defining BFO as if nothing else existed.
Before standardizing any particular ontology, it's essential to map
the territory and show how each one relates to any others.

John

Frank Guerino

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May 25, 2017, 1:18:00 PM5/25/17
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Hi Erick,

I’m certainly interested in an answer to the same question.  A few months back, I tried to reverse engineer Ontology Types/Categories by collecting references to numerous ontologies (see third tab in the spreadsheet: https://docs.google.com/spreadsheets/d/1GJRGIg3-i5s93j4bVAA9kAC4u5BGckh4qLfE2932YpE/edit?usp=sharing).

I came to the conclusions that:

  1. Just like the Knowledge Management field struggles with the definition of Knowledge, after many decades of trying to define it, the Ontology field still can’t clearly define what an Ontology is.
  2. Because there is no clear definition for an ontology, there is no clear standard for consistently/repeatedly developing, representing, labeling, or classifying an ontology.
  3. Computer Science has allowed many people to create many different and highly unique constructs/structures that they call Ontologies.  Some structures are simpler (e.g. Glossaries and Dictionaries), while others can be quite complex (e.g. Semantic structures that attempt to represent the english language, including terms, tenses, definitions, synonyms, antonyms, direct translations to other languages, relationships to other meaningful constructs, etc.).

If you come across anything you feel is useful, I’d certainly like to see it.

My Best,

Frank
Frank Guerino, Managing Partner
The International Foundation for Information Technology (IF4IT)
http://www.if4it.com
1.908.294.5191 (M)


From: Erick Antezana <erick.a...@gmail.com>
Reply-To: Ontolog Forum <ontolo...@googlegroups.com>
Date: Tuesday, May 23, 2017 at 5:04 PM
To: Ontolog Forum <ontolo...@googlegroups.com>
Subject: [ontolog-forum] Types of ontologies?

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Rich Cooper

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May 25, 2017, 4:06:20 PM5/25/17
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I agree.  There are numerous ontologies, but they aren't used by anybody other than ontologists and their students, for the most part. 

Still, a typology is used in every software program, and that defines an ontology AFAIC, which can be operationalized by the software during execution.  Beyond that lie dragons. 

Sincerely,

Rich Cooper,

Rich Cooper,

Chief Technology Officer,

MetaSemantics Corporation

MetaSemantics AT EnglishLogicKernel DOT com

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http://www.EnglishLogicKernel.com

From: ontolo...@googlegroups.com [mailto:ontolo...@googlegroups.com] On Behalf Of Frank Guerino
Sent: Thursday, May 25, 2017 10:18 AM
To: Ontolog Forum
Subject: Re: [ontolog-forum] Types of ontologies?

Hi Erick,

I’m certainly interested in an answer to the same question.  A few months back, I tried to reverse engineer Ontology Types/Categories by collecting references to numerous ontologies (see third tab in the spreadsheet: https://docs.google.com/spreadsheets/d/1GJRGIg3-i5s93j4bVAA9kAC4u5BGckh4qLfE2932YpE/edit?usp=sharing).

I came to the conclusions that:

1.      Just like the Knowledge Management field struggles with the definition of Knowledge, after many decades of trying to define it, the Ontology field still can’t clearly define what an Ontology is.

2.      Because there is no clear definition for an ontology, there is no clear standard for consistently/repeatedly developing, representing, labeling, or classifying an ontology.

3.      Computer Science has allowed many people to create many different and highly unique constructs/structures that they call Ontologies.  Some structures are simpler (e.g. Glossaries and Dictionaries), while others can be quite complex (e.g. Semantic structures that attempt to represent the english language, including terms, tenses, definitions, synonyms, antonyms, direct translations to other languages, relationships to other meaningful constructs, etc.).

Edward Barkmeyer

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May 25, 2017, 6:46:13 PM5/25/17
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Doug,

 

FWIW, I understand the “domain” of an ontology to be the set of concepts needed to solve some set of problems in some community.  And the purpose of the ontology is to solve those problems for that community.  Mostly that means you can’t build an ontology for an undefined set of problems.

 

That said, “accounting” is a “domain” if the community is interested in reasoning about accounting issues, but it is probably inadequate if the concerns stretch to the business area that the accounting activities are supporting.  It is likely to be the case that accounting for the retail sales industry will involve retail sales concepts, like inventory, that accounting for manufacturing or healthcare provision takes a different view of, or has no interest in, while they in turn have differents view of equipment management, utilization, and amortization. 

 

The general problem is the same old “conceptual schema for the enterprise” problem.  You construct a schema/ontology that covers a certain set of known concerns/applications.  A year later, you add two more concerns, and you have to modify the overall schema to eliminate assumptions that are not valid in the larger scope, or to deal with the discovery that you have different views of a common elephant.  (The most common problem with the elephant is detailed views vs. aggregate views, which have complex functional relationships that will produce outright inconsistencies if both views are modeled as is.)

 

To combine independently developed ontologies for your problem area, you have to provide the glue, and sometimes a bit of “field adaptation” (*altering* the off-the-shelf component to fit the use).

 

Then again, my view of reuse (as distinct from simple ‘use’) of off-the-shelf software has pretty much always been “adapt it to fit”.  (One of my colleagues, however, was successful with the approach of “adapt my app to use it.”)

 

-Ed

 

 

 

From: ontolo...@googlegroups.com [mailto:ontolo...@googlegroups.com] On Behalf Of Doug McDavid
Sent: Thursday, May 25, 2017 9:38 AM
To: ontolog-forum <ontolo...@googlegroups.com>
Subject: Re: [ontolog-forum] Types of ontologies?

 

Seems like the concept of 'domain' provides a commonly understood element of this meta-ontology being discussed.  It even seems, however, that we may harbor multiple referents for what we mean by, let's say, 'ontology domain'.  Should we describe domains, how they work, and how they may interrelate?  

http://www.informationjunction.co.uk/

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This email originates from Information Junction Ltd. Registered in England and Wales No. 6632177.

Registered office: 8 Ennismore Close, Letchworth Garden City, Hertfordshire, SG6 2SU.

 

 

 

From: ontolo...@googlegroups.com [mailto:ontolo...@googlegroups.com] On Behalf Of Erick Antezana
Sent: 23 May 2017 22:05
To: ontolo...@googlegroups.com
Subject: [ontolog-forum] Types of ontologies?

 

Dear all,

 

I am sure this question has already been asked long ago; however, I was not able to find any good pointer in the ontolog archives...so here it is (possibly again): could you recommend some documentation/definitions about the types of ontologies? 

 

I typically develop and work on 'domain ontologies' and 'application ontologies' (in the life science arena). To some extent, I have (re)used 'upper level ontologies'... We want to review the way we name and classify those different types of artifacts. Any pointers would be highly appreciated.

 

I know there could be different classifications, based on specific dimensions such as expressiveness, purpose, coverage, etc. (http://www.springer.com/cda/content/document/cda_downloaddocument/9780857297235-c1.pdf?SGWID=0-0-45-1193345-p174120365). however, I was wondering whether there is any "relatively widely accepted" classification?

 

thanks,

Erick

 

 

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Frank Guerino

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May 26, 2017, 10:45:26 AM5/26/17
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Hi Rich,

So, let me ask you… What is your definition of a Typology?

My Best,

Frank
Frank Guerino, Managing Partner
The International Foundation for Information Technology (IF4IT)
http://www.if4it.com
1.908.294.5191 (M)

From: Rich Cooper <metase...@englishlogickernel.com>
Reply-To: Ontolog Forum <ontolo...@googlegroups.com>
Date: Thursday, May 25, 2017 at 4:05 PM
To: Ontolog Forum <ontolo...@googlegroups.com>
Subject: RE: [ontolog-forum] Types of ontologies?

John F Sowa

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May 26, 2017, 11:51:08 AM5/26/17
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Frank, Ed, and Rich,

For once, I find nothing to disagree with in any of your comments.
The central issue in all of them is that YAFO (Yet Another Formal
Ontology) is much less important than a clear set of guidelines
for analyzing, relating, and sharing data among ontologies.

To emphasize that issue, I'll shorten Frank's three points:

FG
> 1. The Ontology field still can’t clearly define what an Ontology is.
>
> 2. There is no clear standard for consistently/repeatedly developing,
> representing, labeling, or classifying an ontology.
>
> 3. Computer Science has allowed many people to create many different
> and unique constructs/structures that they call Ontologies.

But I would add a fourth point, which is essential for semantic
interoperability -- especially with and among legacy systems:

4. There is a desperate need for methods and guidelines for extracting
a consistent common core suitable for sharing data among systems
whose ontologies may be unstated or even inconsistent.

As an example of #4, there is abundant evidence of data sharing among
systems that have 4D ontologies with systems that have 3+1 D ontologies.

Neither side in this argument is ever going to concede to the other.
But the fact that some people successfully share data is an existence
proof that (a) a consistent core does exist, and (b) they found it.

Goal: Systematic methods and guidelines for extracting such a core.

EJB
> I understand the “domain” of an ontology to be the set of concepts
> needed to solve some set of problems in some community. And the
> purpose of the ontology is to solve those problems for that community.

That statement has several key words or terms: domain, ontology,
concepts, needed, solve problems, community, purpose.

I agree that all those key terms are important, and I won't quibble
about any which, if any, are more fundamental or independent or
primitive or derivative.

I'd also point out that the word 'intention' or 'intentionality',
which is often missing in many ontologies, is implicit in the terms
'needed', 'purpose', and 'community'.

EJB
> To combine independently developed ontologies for your problem area,
> you have to provide the glue, and sometimes a bit of “field adaptation”
> (*altering* the off-the-shelf component to fit the use).

I agree. And I believe that the "glue" and "field adaptation" are
closely related to point #4 above: find and extract the common core.

RC
> a typology is used in every software program, and that defines
> an ontology AFAIC

FG
> What is your definition of a Typology?

I'll let Rich state his own definition. But my definition would be
"the datatypes in the software and the kinds of entities that variables
of those types refer to in the world outside the computer."

I believe that the distinction between signs and their referents
is critical for ontology, but many versions fail to include signs
in their ontology. See http://www.jfsowa.com/pubs/signs.pdf

RC
> Beyond that lie dragons.

I agree. Most of those dragons come from philosophy. I have a high
regard for good philosophy, but even the philosophers apologize for
the proliferation of dragons -- some good and some bad. Sometimes
they kill the good ones, such as purpose and intentionality.

Another good dragon is the medieval suppositio. (See the attached
suppos.jpg.) The suppositio is the (nonexistent) referent of
nonphysical terms, such as abstractions and nonexistent dragons.
That's why many philosophers tried to kill them.

But every time an engineer talks about the plans for a bridge,
an airplane, or a possible oil well, the suppositio is imaginary
-- until the thing is built or discovered.

John
suppos.jpg

Rich Cooper

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May 26, 2017, 12:51:25 PM5/26/17
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Frank,

 

A type structure (typology) is the tree of type statements in a programming language such as Delphi.  The original typology was for Algol 68, which failed miserably in the market.  Then Pascal came along with a good tree structured typology.  Now, C++, Java, others are using type structures assembled by type statements in the program source. 

 

With the OO insights, type structures expanded slightly.  Ada for example had type structures, but didn't directly support OO compartments, until a few extra fillets were baked into the spec. 

 

Serious ontologists hate such things as type structures in programs.  Using generic domains such as integer, string, memory block, drives them nuts. 

 

Sincerely,

Rich Cooper,

Rich Cooper,

 

Chief Technology Officer,

MetaSemantics Corporation

MetaSemantics AT EnglishLogicKernel DOT com

( 9 4 9 ) 5 2 5-5 7 1 2

http://www.EnglishLogicKernel.com

 

From: ontolo...@googlegroups.com [mailto:ontolo...@googlegroups.com] On Behalf Of Frank Guerino
Sent: Friday, May 26, 2017 7:45 AM
To: Ontolog Forum
Subject: Re: [ontolog-forum] Types of ontologies?

 

Hi Rich,

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Frank Guerino

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May 26, 2017, 1:54:47 PM5/26/17
to Ontolog Forum
Thanks for your definition.

You wrote: “Serious ontologists hate such things as type structures in programs.  Using generic domains such as integer, string, memory block, drives them nuts.

This is funny because all natural languages have both generic and specific domains, too.

I always wonder if an aggregated set of source code files for software “X” makes for a better ontology than any intentional ontology I’ve ever seen generated for runtime communications between systems.  We’ve spent a tremendous amount of effort trying to create these ontology structures (separate from source code) that computers are expected to reference and/or pass around and use, from application to application.  Now, with serverless computing evolving, we’re learning that we can just pass the source code around, including specifications, functional behavior, data, and all.  Isn’t this far more powerful than any existing intentionally explicit ontology that has been created, to date?

Doug McDavid

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May 26, 2017, 5:35:04 PM5/26/17
to ontolog-forum
Ed, thanks for the response.  To pick up on the 'accounting' domain (for those who agree it's not an oxymoron to say 'accounting domain'), let's zero in on a couple of intersections.  For instance, I did some work with a wireless telco who did not have customer accounts.  But I also worked for several large companies whose ability to have full and distinct customer accounts led to the extremely generic 'party' concept, as in 'party to an agreement'. This is just mentioned as examples of the intersection of domains (professional discipline, industry) yielding different recognized concepts of concern.

Different 'kinds' of domains.  Some level of combinatorics.

On Fri, May 26, 2017 at 10:54 AM, Frank Guerino <Frank....@if4it.com> wrote:
Thanks for your definition.

You wrote: “Serious ontologists hate such things as type structures in programs.  Using generic domains such as integer, string, memory block, drives them nuts.

This is funny because all natural languages have both generic and specific domains, too.

I always wonder if an aggregated set of source code files for software “X” makes for a better ontology than any intentional ontology I’ve ever seen generated for runtime communications between systems.  We’ve spent a tremendous amount of effort trying to create these ontology structures (separate from source code) that computers are expected to reference and/or pass around and use, from application to application.  Now, with serverless computing evolving, we’re learning that we can just pass the source code around, including specifications, functional behavior, data, and all.  Isn’t this far more powerful than any existing intentionally explicit ontology that has been created, to date?

My Best,

Frank
Frank Guerino, Managing Partner
The International Foundation for Information Technology (IF4IT)
http://www.if4it.com
1.908.294.5191 (M)

From: Rich Cooper <metasemantics@englishlogickernel.com>
Reply-To: Ontolog Forum <ontolog-forum@googlegroups.com>
Date: Friday, May 26, 2017 at 12:50 PM
To: Ontolog Forum <ontolog-forum@googlegroups.com>
Subject: RE: [ontolog-forum] Types of ontologies?

Frank,

 

A type structure (typology) is the tree of type statements in a programming language such as Delphi.  The original typology was for Algol 68, which failed miserably in the market.  Then Pascal came along with a good tree structured typology.  Now, C++, Java, others are using type structures assembled by type statements in the program source. 

 

With the OO insights, type structures expanded slightly.  Ada for example had type structures, but didn't directly support OO compartments, until a few extra fillets were baked into the spec. 

 

Serious ontologists hate such things as type structures in programs.  Using generic domains such as integer, string, memory block, drives them nuts. 

 

Sincerely,

Rich Cooper,

Rich Cooper,

 

Chief Technology Officer,

MetaSemantics Corporation

MetaSemantics AT EnglishLogicKernel DOT com

( 9 4 9 ) 5 2 5-5 7 1 2

http://www.EnglishLogicKernel.com

 


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Rich Cooper

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May 26, 2017, 6:58:44 PM5/26/17
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Frank Guerino wrote:

      Isn’t this far more powerful than any existing intentionally explicit ontology that has been created, to date?

In a word, yes. 

Sincerely,

Rich Cooper,

Rich Cooper,

Chief Technology Officer,

MetaSemantics Corporation

MetaSemantics AT EnglishLogicKernel DOT com

( 9 4 9 ) 5 2 5-5 7 1 2

http://www.EnglishLogicKernel.com

From: ontolo...@googlegroups.com [mailto:ontolo...@googlegroups.com] On Behalf Of Frank Guerino
Sent: Friday, May 26, 2017 10:55 AM
To: Ontolog Forum
Subject: Re: [ontolog-forum] Types of ontologies?

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Edward Barkmeyer

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May 26, 2017, 7:13:59 PM5/26/17
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Doug,

 

You wrote:

> Different 'kinds' of domains.  Some level of combinatorics.

 

+1

 

-Ed

 

 

 

From: ontolo...@googlegroups.com [mailto:ontolo...@googlegroups.com] On Behalf Of Doug McDavid
Sent: Friday, May 26, 2017 5:35 PM
To: ontolog-forum <ontolo...@googlegroups.com>
Subject: Re: [ontolog-forum] Types of ontologies?

 

Ed, thanks for the response.  To pick up on the 'accounting' domain (for those who agree it's not an oxymoron to say 'accounting domain'), let's zero in on a couple of intersections.  For instance, I did some work with a wireless telco who did not have customer accounts.  But I also worked for several large companies whose ability to have full and distinct customer accounts led to the extremely generic 'party' concept, as in 'party to an agreement'. This is just mentioned as examples of the intersection of domains (professional discipline, industry) yielding different recognized concepts of concern.

 

Different 'kinds' of domains.  Some level of combinatorics.

 

 

 

 

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Hans Polzer

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May 26, 2017, 8:57:59 PM5/26/17
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Powerful for what purpose? Maybe for the users and operational domain/purpose for whom the software was designed. But if any other entity on the network wants to interact with that software it would be hard-pressed to discover what that implicit, but powerful, ontology might be. The issue I’m concerned with is dynamic discovery and interoperability by/with entities on the network that were unanticipated by the software creator. In some cases, and increasingly with service oriented architecture, software developers make some key subset of their implicit ontology visible and accessible to entities outside their software perimeter. While useful, this still hides a lot of information/services inherent in the software from outside entities. That’s fine if there are legitimate security/privacy reasons for doing so, but it otherwise limits the potential utility of the software in the networked environment.

 

Hans

Rich Cooper

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May 26, 2017, 9:34:58 PM5/26/17
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Hans, you wrote:

      In some cases, and increasingly with service oriented architecture, software developers make some key subset of their implicit ontology visible and accessible to entities outside their software perimeter. While useful, this still hides a lot of information/services inherent in the software from outside entities. That’s fine if there are legitimate security/privacy reasons for doing so, but it otherwise limits the potential utility of the software in the networked environment.

Yes, the products have APIs and URLs that can be referenced.  Those objects, classes and actions are supported because the development costs of supporting those objects, classes and actions have been paid. There has been testing done to the level of supporting those functions, ensuring they perform as speced. 

But the idea of opening a program suite to people who will reference the internals, not previously designed with sharing in mind beyond the development team, is naïve IMHO, and ignores the development costs (not paid) of making that internal architecture available to the general public. 

I disagree for that reason. 

Sincerely,

Rich Cooper,

Rich Cooper,

Chief Technology Officer,

MetaSemantics Corporation

MetaSemantics AT EnglishLogicKernel DOT com

( 9 4 9 ) 5 2 5-5 7 1 2

http://www.EnglishLogicKernel.com

John F Sowa

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May 27, 2017, 8:16:12 AM5/27/17
to ontolo...@googlegroups.com
Rich and Frank,

RC
> Serious ontologists hate such things as type structures in programs.
> Using generic domains such as integer, string, memory block, drives
> them nuts.

No. There is nothing wrong with having an ontology of "integer,
string, memory block" or any other collection of data types.
What is wrong is to define an employee as a character string.

A digital computer is a semiotic processor that uses physical
things such as transistors and disk drives to represent and
process data types. Instances of those types may be used as
signs that refer to entities inside the computer, entities
outside the computer, and other signs of any kind.

Any ontologists who "hate such things" are probably using an
ontology that cannot represent signs, their referents, and the
process of using signs to refer to something (including signs).
Such ontologists are guilty of ontological malpractice and
should be sent out for remedial re-education.

FG
> Now, with serverless computing evolving, we’re learning that we can
> just pass the source code around, including specifications, functional
> behavior, data, and all. Isn’t this far more powerful than any existing
> intentionally explicit ontology that has been created, to date?

No -- because the specifications include the ontology. Passing the
specifications around or printing them on paper does not change them
in any way. And it has no effect on whether the ontology in the spec's
happens to be implicit or explicit.

The primary reason for making the ontology explicit is to enable
the designers to reuse it for multiple related projects. If you're
a carpenter building a cabinet or a farmer planting corn, you
probably don't need a detailed ontology.

But if you're designing an airplane, you would like the software
that simulates it to have a precise mapping to the physical object.
And you want to simulate that plane and its operations as thoroughly
as possible before, during, and after the time that it's being built.

If you have a precisely defined ontology, you can reuse it many times:
in designing the plane, the software, various parts by subcontractors,
equipment and buildings used with the plane, interior designs tailored
for different purposes, etc.

John

Frank Guerino

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May 27, 2017, 10:32:32 AM5/27/17
to Ontolog Forum
Hi John,

I believe you missed my statement that behavior, along with specification and data, can be passed from system to system.  When passing behavior between entities, the receiving entity can create new ontologies or modify the existing ontology, can create new data or modify existing data, and (most importantly) can evolve and change based on what we know about past, present, and future state.

You mentioned airplane simulation as an example.  My background is in (and for many years was my expertise) semiconductor synthesis, simulation, acceleration, emulation, and fabrication.  My teams and I built solutions for each of these areas (both hardware and software), for almost every major and minor company in the world that designed semiconductors.  I say this because I intimately understand your statement of precise mappings.  However such precise mappings do not come from ontologies.  They come from detailed domain-specific schematics and from domain-specific rules & behaviors for working with such schematics.

You wrote: “If you have a precisely defined ontology, you can reuse it many times: in designing the plane, the software, various parts by subcontractors, equipment and buildings used with the plane, interior designs tailored for different purposes, etc.” 

I would respectfully suggest that the idea of a precisely defined ontology is a unicorn because not even you can precisely define what an ontology is.

Have a great holiday weekend,

Frank
Frank Guerino, Managing Partner
The International Foundation for Information Technology (IF4IT)
http://www.if4it.com
1.908.294.5191 (M)

John F Sowa

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May 27, 2017, 1:14:02 PM5/27/17
to ontolo...@googlegroups.com
On 5/27/2017 10:32 AM, Frank Guerino wrote:
> I would respectfully suggest that the idea of a precisely defined
> ontology is a unicorn because not even you can precisely define
> what an ontology is.

I did not say that. Please note exactly what I said:
> On 5/26/2017 11:51 AM, John F Sowa wrote:
>> The central issue in all of them is that YAFO (Yet Another Formal
>> Ontology) is much less important than a clear set of guidelines
>> for analyzing, relating, and sharing data among ontologies.
>>
>> To emphasize that issue, I'll shorten Frank's three points:
>>
>> FG
>>> 1. The Ontology field still can’t clearly define what an Ontology is.

I was agreeing with your comment that the *field as a whole* has
not stated a clear definition that everyone can use. They keep
repeating a hopelessly vague statement that *nobody* understands:
> An ontology is a formalization of a conceptualization.

That statement defines a fairly simple word 'ontology' in terms of
two words that are much more difficult to define. The third word
'conceptualization' refers to some unknown psychological process of
creating concepts. And 'concept' itself is difficult to define.

By comparison, the word 'ontology' is quite easy to define at
the level of a typical English dictionary. It has two senses:
> 1. Ontology is the branch of philosophy the studies the kinds
> of things that exist or may exist.
>
> 2. An ontology is a classification and specification of what
> exists or may exist in some subject or field of interest.

For computer implementation, a *formal ontology* is specified in
some version of logic. The ontology consists of the functions,
relations, and types defined by statements in that logic. What
exists or may exist in such an ontology is the set of referents
of quantified variables as determined by that specification.

That is a clear English definition, followed by a computable
version that has been implemented many times in different logics.

FG
> I believe you missed my statement that behavior, along with
> specification and data, can be passed from system to system.

I didn't know what you meant by "passed from system to system".
It just seems to mean "copied". But you added much more:

FG
> When passing behavior between entities, the receiving entity can
> create new ontologies or modify the existing ontology, can create
> new data or modify existing data, and (most importantly) can evolve
> and change based on what we know about past, present, and future state.

What you're talking about is related to what I said in point #4:
> 4. There is a desperate need for methods and guidelines for extracting
> a consistent common core suitable for sharing data among systems whose
> ontologies may be unstated or even inconsistent.

If that's close to what you meant, then we can agree.

The only quibble I'd add is that putting the spec's in a cloud may
speed up the process, but it doesn't affect the "desperate need for
methods and guidelines for extracting a consistent common core."

Those methods and guidelines should be the focus of Part I of the
proposed ISO standard. The collection of YAFOs belong in Part II.

John

Hans Polzer

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May 27, 2017, 10:21:36 PM5/27/17
to ontolo...@googlegroups.com

Rich,

 

I agree that there are business model challenges in the general case for explicitly exposing more of any given software/information capability’s internal ontology. But I don’t agree that the developer’s sponsor is in general fully aware of the potential value to others on the network of doing so. That value may be economic or socio-political in nature, and may have advocates who see that value and who are different from the developer’s sponsor. The main challenge is to discover the appropriate business model to best justify the developer investment necessary to release/attain that value (and not necessarily for the general public, but maybe a larger set of potential users/uses/markets than originally envisioned by the developer’s sponsor). But that’s also true of all the discussion on this forum regarding development of domain ontologies or ontologies of ontologies.

Michael DeBellis

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May 27, 2017, 11:41:55 PM5/27/17
to ontolog-forum, hpo...@verizon.net
>> the idea of opening a program suite to people who will reference the internals, not previously designed with sharing in mind beyond the development team, is naïve 

I agree.  And I don't think its just business model or cost challenges.  There are major technical challenges as well. This reminds me of the early days of object-oriented programming. When it came to integration there were for a while two camps. One camp that wanted to get integration by having organizations agree on object models and having deep integration by sharing objects. The other wanted much shallower integration by only allowing messages, the interfaces to systems and those messages would usually take very flat data types as parameters, Simple datatypes like strings or integers rather than complex objects. 

If you are familiar with how integration is done now that may be hard to believe but I remember going to conferences and taking part in heated arguments between the two camps. There is no question that the message (as in message oriented middleware not method invocation) won out and that most domains standardized on message based standards such as HL7 for healthcare rather than standardizing on the underlying object model. 

This idea of sending huge chunks of code around seems to have all the drawbacks of the standard object model approach and then some. Two in particular jump out at me:

1) Security. Sending code to users seems like just begging for major security headaches.

2) Maintenance.  One of the major wins of the OO approach is encapsulation. That we hide the implementation details because we don't want people to code to those details. That makes it much easier for systems to evolve without breaking other systems that use or communicate with them. 

I don't understand how this code sharing technology works but it seems to me that its inevitable that it would make these kinds of issues exponentially more complicated and risky. 

Also, from a business perspective I'm always a fan of walk before you run. I'm rather disappointed that the Semantic Web hasn't taken off more than it has so far. I think one reason (this could merit a conversation of its own) is that a lot of companies such as Microsoft and Google see the Machine Learning approach as the easier way to go. Rather than try to put a more logical layer underneath the existing Internet why not just use Machine Learning to organize the existing sites without all the effort of building ontologies? I think there are good answers to that question but I can see why it would be appealing to big corporations that already dominate the Internet as is. So before we start thinking about what is much cooler and better than ontologies I think we need to make sure that ontologies are actually seen as practical, scalable, and useful. I don't think they are seen that way by many people yet. Which is also why I'm not a fan of BFO and other upper model ontologies that try to model all of reality. Most of the business users that I've worked with would start zoning out and checking their watches when the conversation got around to Continuants vs. Occurents. 

One last thought, speaking of HL7.  That would be where I would look for an idea of what an ontology of ontologies should look like: the various domain and technical integration standards groups and the things that they've standardized on. Most of them (again, HL7 is a good example) have already done a good job of decomposing their domains into sub-domains, in the case of healthcare: Labs, Medical Records, Billing, Admissions, etc. And looking at the messages that are defined for integration would also give a good first cut at what the ontology for that domain would need to address. 

Michael



On Saturday, May 27, 2017 at 7:21:36 PM UTC-7, Hans Polzer wrote:

Rich,

 

I agree that there are business model challenges in the general case for explicitly exposing more of any given software/information capability’s internal ontology. But I don’t agree that the developer’s sponsor is in general fully aware of the potential value to others on the network of doing so. That value may be economic or socio-political in nature, and may have advocates who see that value and who are different from the developer’s sponsor. The main challenge is to discover the appropriate business model to best justify the developer investment necessary to release/attain that value (and not necessarily for the general public, but maybe a larger set of potential users/uses/markets than originally envisioned by the developer’s sponsor). But that’s also true of all the discussion on this forum regarding development of domain ontologies or ontologies of ontologies.

 

Hans

 

From: ontolo...@googlegroups.com [mailto:ontolo...@googlegroups.com] On Behalf Of Rich Cooper
Sent: Friday, May 26, 2017 9:34 PM
To: ontolo...@googlegroups.com
Subject: RE: [ontolog-forum] Types of ontologies?

 

Hans, you wrote:

In some cases, and increasingly with service oriented architecture, software developers make some key subset of their implicit ontology visible and accessible to entities outside their software perimeter. While useful, this still hides a lot of information/services inherent in the software from outside entities. That’s fine if there are legitimate security/privacy reasons for doing so, but it otherwise limits the potential utility of the software in the networked environment.

Yes, the products have APIs and URLs that can be referenced.  Those objects, classes and actions are supported because the development costs of supporting those objects, classes and actions have been paid. There has been testing done to the level of supporting those functions, ensuring they perform as speced. 

But the idea of opening a program suite to people who will reference the internals, not previously designed with sharing in mind beyond the development team, is naïve IMHO, and ignores the development costs (not paid) of making that internal architecture available to the general public. 

I disagree for that reason. 

Sincerely,

Rich Cooper,

Rich Cooper,

Chief Technology Officer,

MetaSemantics Corporation

MetaSemantics AT EnglishLogicKernel DOT com

( 9 4 9 ) 5 2 5-5 7 1 2

http://www.EnglishLogicKernel.com

From: ontolo...@googlegroups.com [mailto:ont...@googlegroups.com] On Behalf Of Hans Polzer
Sent: Friday, May 26, 2017 5:58 PM
To: ontolo...@googlegroups.com
Subject: RE: [ontolog-forum] Types of ontologies?

Powerful for what purpose? Maybe for the users and operational domain/purpose for whom the software was designed. But if any other entity on the network wants to interact with that software it would be hard-pressed to discover what that implicit, but powerful, ontology might be. The issue I’m concerned with is dynamic discovery and interoperability by/with entities on the network that were unanticipated by the software creator. In some cases, and increasingly with service oriented architecture, software developers make some key subset of their implicit ontology visible and accessible to entities outside their software perimeter. While useful, this still hides a lot of information/services inherent in the software from outside entities. That’s fine if there are legitimate security/privacy reasons for doing so, but it otherwise limits the potential utility of the software in the networked environment.

Hans

From: ontolo...@googlegroups.com [mailto:ont...@googlegroups.com] On Behalf Of Rich Cooper
Sent: Friday, May 26, 2017 6:58 PM
To: ontolo...@googlegroups.com
Subject: RE: [ontolog-forum] Types of ontologies?

Frank Guerino wrote:

Isn’t this far more powerful than any existing intentionally explicit ontology that has been created, to date?

In a word, yes. 

Sincerely,

Rich Cooper,

Rich Cooper,

Chief Technology Officer,

MetaSemantics Corporation

MetaSemantics AT EnglishLogicKernel DOT com

( 9 4 9 ) 5 2 5-5 7 1 2

http://www.EnglishLogicKernel.com

From: ontolo...@googlegroups.com [mailto:ontolog-forum@googlegroups.com] On Behalf Of Frank Guerino
Sent: Friday, May 26, 2017 10:55 AM
To: Ontolog Forum
Subject: Re: [ontolog-forum] Types of ontologies?

Thanks for your definition.

You wrote: “Serious ontologists hate such things as type structures in programs.  Using generic domains such as integer, string, memory block, drives them nuts.

This is funny because all natural languages have both generic and specific domains, too.

I always wonder if an aggregated set of source code files for software “X” makes for a better ontology than any intentional ontology I’ve ever seen generated for runtime communications between systems.  We’ve spent a tremendous amount of effort trying to create these ontology structures (separate from source code) that computers are expected to reference and/or pass around and use, from application to application.  Now, with serverless computing evolving, we’re learning that we can just pass the source code around, including specifications, functional behavior, data, and all.  Isn’t this far more powerful than any existing intentionally explicit ontology that has been created, to date?

My Best,

Frank

Frank Guerino, Managing Partner

The International Foundation for Information Technology (IF4IT)
http://www.if4it.com
1.908.294.5191 (M)

Rich Cooper

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May 27, 2017, 11:59:04 PM5/27/17
to ontolo...@googlegroups.com

Hans,

I agree that the developer's sponsor (as you describe the capitalist role in this example) very likely does not understand all the repercussions of the internal types, functions, data structures and states.  The capitalist wants to maximize returns, and that is best done by expanding marketing along the most profitable lines, while sacrificing anything not in that project directly

The max return usually is not, definitely not, looking for littler markets that could drain the capital needed to pursue the most profitable markets.  If I can grow by 65% in the most profitable line, why would I spend my time trying to also grow 32% in the next most profitable? 

All the books teach focus, focus, focus.  In the fifties and sixties, conglomerates were all the management rage, but they faded out because they couldn't compete with the singularly focused companies with their accelerators floored. 

Rich Cooper

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May 28, 2017, 12:07:08 AM5/28/17
to ontolo...@googlegroups.com, hpo...@verizon.net

Michael wrote:

      I don't understand how this code sharing technology works but it seems to me that it's inevitable that it would make these kinds of issues exponentially more complicated and risky.

Agreed whole heartedly.  People who have not been involved in software engineering don't get to see the 80% of that effort that goes into finding and fixing errors.  Even the design of a program suite has to anticipate errors and use exception handlers to recover from errors that have never been encountered before.  Exponentially more complicated, more risky, and therefore more expensive than the single layer API. 

Sincerely,

Rich Cooper,

Rich Cooper,

Chief Technology Officer,

MetaSemantics Corporation

MetaSemantics AT EnglishLogicKernel DOT com

( 9 4 9 ) 5 2 5-5 7 1 2

http://www.EnglishLogicKernel.com

From: ontolo...@googlegroups.com [mailto:ontolo...@googlegroups.com] On Behalf Of Frank Guerino
Sent: Friday, May 26, 2017 10:55 AM
To: Ontolog Forum
Subject: Re: [ontolog-forum] Types of ontologies?

Thanks for your definition.

You wrote: “Serious ontologists hate such things as type structures in programs.  Using generic domains such as integer, string, memory block, drives them nuts.

This is funny because all natural languages have both generic and specific domains, too.

I always wonder if an aggregated set of source code files for software “X” makes for a better ontology than any intentional ontology I’ve ever seen generated for runtime communications between systems.  We’ve spent a tremendous amount of effort trying to create these ontology structures (separate from source code) that computers are expected to reference and/or pass around and use, from application to application.  Now, with serverless computing evolving, we’re learning that we can just pass the source code around, including specifications, functional behavior, data, and all.  Isn’t this far more powerful than any existing intentionally explicit ontology that has been created, to date?

My Best,

Frank

Frank Guerino, Managing Partner

The International Foundation for Information Technology (IF4IT)
http://www.if4it.com
1.908.294.5191 (M)

John F Sowa

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May 28, 2017, 2:35:51 AM5/28/17
to ontolo...@googlegroups.com
On 5/27/2017 11:41 PM, Michael DeBellis wrote:
> This idea of sending huge chunks of code around seems to have all
> the drawbacks of the standard object model approach and then some.

Semantic interoperability has very little to do with code sharing,
and everything to do with data sharing. That is why the database
pioneers took the lead in developing the conceptual schema and
logic-based query and specification languages.

Does anybody remember CORBA? The Common Object Request Broker
Architecture, which OMG developed as a standard in 1991?

The goal of CORBA was to enable software written in different
object-oriented languages to make cross-language calls. That
seemed like a good idea in 1991.

But data sharing was far more important, implementable, and usable.
The WWW was based on data sharing, not program sharing.

For the history and publications, see http://www.jfsowa.com/ikl

John

Hans Polzer

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May 28, 2017, 1:36:22 PM5/28/17
to ontolo...@googlegroups.com

Well, Rich, not everyone has quite the narrow focus you describe/attribute to all capitalists, and not all sponsors are capitalists. Governments and non-profits often invest in such capabilities/standards. Furthermore, some capitalists in the Internet/globalist age realize that supply chain and consumer chain partners can be widespread and dynamic (i.e., changing over time). They often invest both directly and indirectly (through membership in industry associations and through partnerships with third-party brokers/exchanges) in capabilities and standards that promote gaining significant additional value from their investments (e.g., more global markets) with relatively little additional investment.

 

I agree that the mantra of “focus, focus, focus” is very prevalent in business, and for very good reasons. But sometimes too much focus allows competitors to eat into your potential markets and  makes you blind to the value of your capabilities or products/services outside your traditional markets. That’s why I often respond to people asking me what I did for a living that I “teach people unnatural acts and give them ‘out of body’ experiences”.

 

Regarding the issue of the value versus cost/risk proposition of exposing what might otherwise be called internals of software systems, I’d just like to point out that a lot of Internet businesses make their living by selling what in the past would have been considered internal audit trail information in traditional software systems – essential deriving business value or operational intelligence from user/agent behavior captured by such information. Of course, there may be internal book-keeping information that is of no value outside the software execution environment. And there is significant development cost associated with exposing such “internals” so some judgement is required. But the relative run-time and connection/communication costs associated with exposing this information are declining.

Rich Cooper

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May 28, 2017, 2:38:25 PM5/28/17
to ontolo...@googlegroups.com

Hans,

Even governments have budgets they have to negotiate.  The extra cost of developing the internals to a point where they can be exposed safely to naïve users is still a cost, and an accompanying schedule increase.  So exposing internals may or may not be worth that cost, whether it’s a government or a capitalist doing the development. 

Sincerely,

Rich Cooper,

Rich Cooper,

Chief Technology Officer,

MetaSemantics Corporation

MetaSemantics AT EnglishLogicKernel DOT com

( 9 4 9 ) 5 2 5-5 7 1 2

http://www.EnglishLogicKernel.com

John F Sowa

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May 28, 2017, 4:33:55 PM5/28/17
to ontolo...@googlegroups.com
Rich and Hans,

There are two independent issues in this debate: (1) the value of
a Plan B, and (2) questions about exposing some kind of "internals".

Rich
> If I can grow by 65% in the most profitable line, why would I spend
> my time trying to also grow 32% in the next most profitable?

Nobody knows how to predict markets or future innovations with
that level of precision. We could list dozens of examples where
the "Big Guys" lost $$$ billions by misjudging the markets and the
potential of certain innovations.

Hans
> I agree that the mantra of “focus, focus, focus” is very prevalent in
> business, and for very good reasons. But sometimes too much focus allows
> competitors to eat into your potential markets and makes you blind to
> the value of your capabilities or products/services outside your
> traditional markets.

Yes. As Yogi B. said, "It's hard to make predictions, especially about
the future." Therefore, "Don't put all your eggs in the same basket."
Plan B is to build or buy an extra basket.

Hans
> Regarding the issue of the value versus cost/risk proposition of
> exposing what might otherwise be called internals of software systems...

You have to distinguish the software from the data/ontology. Systems
based on different software can share data and interoperate -- as long
as they have compatible ontologies for specifying the data.

Conversely, systems can use exactly the same software, but they can't
interoperate if they use inconsistent ontologies.

Rich
> The extra cost of developing the internals to a point where they
> can be exposed safely to naïve users is still a cost...

Nobody exposes internals to naive users. Even if they exposed
the internals to experts, that would have no effect (pro or con)
on semantic interoperability. In fact, they could use identical
software, but be incompatible if they use inconsistent ontologies.

Oil companies, for example, are reluctant to share data and
ontologies because they want to protect trade secrets about
their business methods and locations. They may use the same
or similar software, but they keep their data secret.

John

Rich Cooper

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May 28, 2017, 7:04:04 PM5/28/17
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John,

The value of a Plan B is negative.  Companies that maintain a way to back out of its primary market nearly always fail.  It takes serious commitment to a Plan A to make a company successful.  The old statement "Don't put all your eggs in the same basket" never did work, but it took the experience of conglomerates to make that data clear.  Ask your entrepreneur buddies. 

The experience of the industry with data dictionaries shows that people interpret each name in a diversity of ways, not in one way.  The notion of an ontology is good for philosophers and logicians, but not very useful in most software projects. 

Sincerely,

Rich Cooper,

Rich Cooper,

Chief Technology Officer,

MetaSemantics Corporation

MetaSemantics AT EnglishLogicKernel DOT com

( 9 4 9 ) 5 2 5-5 7 1 2

http://www.EnglishLogicKernel.com

-----Original Message-----
From: ontolo...@googlegroups.com [mailto:ontolo...@googlegroups.com] On Behalf Of John F Sowa
Sent: Sunday, May 28, 2017 1:34 PM
To: ontolo...@googlegroups.com
Subject: Re: [ontolog-forum] Types of ontologies?

--

Hans Polzer

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May 28, 2017, 9:48:56 PM5/28/17
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Rich,

 

I agree completely. I don’t think I said anything in my previous email that implied otherwise.

Rich Cooper

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May 28, 2017, 10:30:30 PM5/28/17
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Hans,

You wrote:

      I agree completely. I don’t think I said anything in my previous email that implied otherwise.

Then we are in violent agreement!

rrov...@buffalo.edu

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May 28, 2017, 10:38:34 PM5/28/17
to ontolog-forum
Not to get off-topic, but just a note:
This statement in itself, I believe, is justification for trashing the current ISO TLO propsoal:
"The notion of an ontology is good for philosophers and logicians, but not v
ery useful in most software projects."
I know there are many who agree but whom do not voice their voices. I encourage you to do so.

rrov...@buffalo.edu

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May 28, 2017, 10:48:12 PM5/28/17
to ontolog-forum
A previous reply had these example definitions...

"1. Ontology is the branch of philosophy the studies the kinds
of things that exist or may exist.

2. An ontology is a classification and specification of what
exists or may exist in some subject or field of interest."

Consider also these Merriam-Webster Collegiate Dictionary definitions, that I number 3 and 4:
3 : "a branch of metaphysics concerned with the nature and relations of being"
4 : "a particular theory about the nature of being or the kinds of things that have existence"

Toward a definition, here is some input when considering these definitions...
(This should really go in any thread on defining 'ontology', but here it is)

#1 is ok for an intuitive or non-specialist reading, but the problem
is that philosophically kinds (natural kinds, categories) are contested in philosophy as well, which means the definition should be more general, i.e., should not presuppose that there are kinds. A casual reading does not necesary presuppose kinds, but uses 'kinds' in informally.
#3 solves this issue by address, but seems to imply that relations are distinct from the nature of being, which they are not necessary.
#4 is ok, but it should include potential existence (a good point in #2)

It fundamentally involves the distinction between the philosophical inquiry, which involves seeking to understand the nature of actual and potential existence; and the contemporary computational artifacts. The latter do NOT necessarily involve the former. This is where care must be taken, and this is why problem-solving should be primary.

Also, I think 'conceptualization' is ok to use, because as I understand to be a mental model or view of something.
'Formalization' is und​ertood--in my humble opinion--as an explicitly and systematically stated representation, e.g. in logics, or in some computable format.
Consider: what is 'to formalize'?

Hans Polzer

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May 28, 2017, 10:57:09 PM5/28/17
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John,

The value of Plan B is one way of characterizing the first issue, but I think it is more useful to think about this issue in terms of the potential value to a multiplicity of participants, not just the value to the sponsor of the software development. The business model challenges I referred to center around how the value to other participants can be converted to value for the sponsor of the software development. Expanding/diversifying the sponsor's potential market is one way of making the value apparent to the sponsor, but as Rich pointed out, this isn't always a convincing argument for a variety of reasons. Other approaches include some form of investment co-funding among the multiple participants, either as an independent third party effort or as some form of partnership with the original software sponsor. Of course, these approaches typically result in different software architectures, with different degrees of coupling/decoupling between the original software envisioned by the sponsor and that of the third-party effort. The degree of explicitness in the ontologies used in such couplings would typically be different as well, as your comments point out.

The second issue you mention regarding the value of exposing "internals", is, in my view, one of degree. Many software developers tend to assume a somewhat hard and fast boundary between what is internal housekeeping software and data structures, and what is data exposed to or received from the external environment/agents/users. But in many cases, some of what might be considered "internal" or housekeeping data is actually of value to others outside of the system boundary or the sponsor's purview, if appropriately represented and made accessible externally. But as Rich points out, there is a cost associated with doing the latter, and the development sponsor may not see the business case for doing so. My argument is simply that one should not dismiss the potential value of such information outside one's system boundary out of hand, and that there may be other business models that could justify the investment necessary to extract such value.

Hans


-----Original Message-----
From: ontolo...@googlegroups.com [mailto:ontolo...@googlegroups.com] On Behalf Of John F Sowa
Sent: Sunday, May 28, 2017 4:34 PM
To: ontolo...@googlegroups.com
Subject: Re: [ontolog-forum] Types of ontologies?

John F Sowa

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May 28, 2017, 11:17:41 PM5/28/17
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On 5/28/2017 7:03 PM, Rich Cooper wrote:
> The value of a Plan B is negative. Companies that maintain a way
> to back out of its primary market nearly always fail.

No. I did not say "back out". New technology means new markets.
No "primary market" remains primary for very long. Instead of
backing out, you use the old primary as the foundation for
building the new primary.

For example, IBM's primary market from 1916 to the 1950s was
"business machines". Throughout that period, IBM kept upgrading
and expanding their market. Their original "primary" market was
mechanical devices for processing punched cards and printing reports.

They kept enlarging their market with new kinds of devices
(electric typewriters, for example) which expanded their *monopoly*
(to use a word that IBM officially denied).

In the late 1940s and early '50s, IBM added some vacuum tube
technology to speed up some of the punched-card equipment.
Then they expanded to digital computers in the '50s, but
Univac was still the dominant player in the computer market.

By the late 1950s, IBM built better computers and their solid
foundation in the punched-card business enabled them to take
the major market share (monopoly) in digital computers.

The key words here are 'innovate', 'enlarge', and 'build on'.
IBM was late to the market in PCs, but when they entered in 1981,
they instantly dominated the PC market by building on their
strengths (monopoly).

Those of us who could see what was happening knew that PCs were
the wave of the future. In the mid 1980s, we could see that the PC
was growing much faster than the mainframes. But the mainframe
managers wanted to keep mainframes as the *primary* market. They
almost killed IBM.

It took an outsider (Lou Gerstner) to make the tough decisions.

The full story is much more complex than the above, but the
basic idea is simple: the market place is constantly changing
in unpredictable ways. Anybody who tries to define his or her
specialty as the "primary market" should be fired.

John

Rich Cooper

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May 29, 2017, 11:56:13 AM5/29/17
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John Sowa wrote:

      For example, IBM's primary market from 1916 to the 1950s was "business machines".  Throughout that period, IBM kept upgrading and expanding their market.  Their original "primary" market was mechanical devices for processing punched cards and printing reports.

Then, in 1981, IBM introduced a new market - PCs - which would take over from that Basic computer and the Series 1 which were previously the low price computers.  Just a small market at first, a few billion for a company as big as IBM wasn't worth dominating, so they let Bill G have it. 

See what I mean?

Sincerely,

Rich Cooper,

Rich Cooper,

Chief Technology Officer,

MetaSemantics Corporation

MetaSemantics AT EnglishLogicKernel DOT com

( 9 4 9 ) 5 2 5-5 7 1 2

http://www.EnglishLogicKernel.com

-----Original Message-----
From: ontolo...@googlegroups.com [mailto:ontolo...@googlegroups.com] On Behalf Of John F Sowa
Sent: Sunday, May 28, 2017 8:18 PM
To: ontolo...@googlegroups.com
Subject: Re: [ontolog-forum] Types of ontologies?

--

John F Sowa

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May 29, 2017, 3:11:12 PM5/29/17
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On 5/29/2017 11:55 AM, Rich Cooper wrote:
> Just a small market at first, a few billion for a company as
> big as IBM wasn't worth dominating, so they let Bill G have it.
>
> See what I mean?

You're trying to defend the indefensible. The decisions that were
made by IBM Boca Raton in the 1970s and '80s were made by some of
the most incompetent managers in IBM.

When IBM built that location in the early '70s, many old timers saw
it as an IBM-paid move to a retirement home in Florida. IBM did hire
some good young people, but most of the senior managers were abysmally
ignorant about computer system design. Examples:

1. In 1965, IBM had designed and sold thousands of excellent personal
computers: the IBM 1130. It was not a desktop computer, it was
a *desk* -- a desk with a built-in typewriter and printer, and a
drawer that had disk drive with a removable disk pack. Everybody
who had one loved it. See https://en.wikipedia.org/wiki/IBM_1130

2. In 1969, one of the engineers designed a follow-on to the 1130,
which he called the Quarter-to-Twelve. It was a one-board system
that had five-years of software development and thousands of users.
IBM could have delivered it in 1970 -- a head to head competitor
to the PDP-11, which had no software or users at the time.

3. But the idiot boys at Boca Raton had a brand new building, and
they didn't want a hand-me-down from another division. So they
designed the System/7. It wasn't a bad computer, but it was
more expensive than the PDP-11, it came several years later,
and it had no software. Very few customers bought it. The few
who did returned it because it had no software. In IBM, they used
the returned machines to control badge-readers at the doors.

4. If IBM had built the one-board 1145 in 1970, they could have
mapped it into a one-chip CPU a few years later. That would have
killed the Intel 8086. In any case, they were considering the
Motorola 6800, which had a clean design, big-endian addressing
and 16 registers. IBM Research had already modified System/370
compilers to generate Motorola code. But Intel panicked at the
thought that IBM might select Motorola. So they almost gave away
the 8088 CPU, which Intel themselves considered obsolete.

5. The choice of the Intel 8088 instead of the Motorola 6800 saved
$50 in manufacturing cost per PC -- but the retail price of the PC
was $6000. The Boca Raton idiots had no conception of the cost
of software. In any case, there were programmers at IBM Research
in both Yorktown and San Jose, who had written a good operating
system for the PC 6-wees time. But the idiots paid Bill Gates a
million dollars for QDOS (Quick and Dirty OS), which Gates bought
from the developer for $50,000.

There are many more bad decisions that came out of Boca Raton, but
this is sufficient to show that the loss of the PC market was caused
by pure and simple stupidity. IBM had won the low-end market in the
1960s with the 1130 and the process-control version called the 1800.
They lost that market for one simple reason: ignorant managers.

John

Matthew West

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May 29, 2017, 3:41:29 PM5/29/17
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Ha! An IBM 1130 was the first computer I used. Fond memories.
Regards
Matthew West


Edward Barkmeyer

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May 29, 2017, 5:15:05 PM5/29/17
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John,

Let us not get carried away calling the IBM 1130 a "personal computer". The one I worked on cost the organization $35000 in 1967, and was funded by a US Govt contract. The company I worked for was trying to sell small-business support in 1971-2 and could not find a suitable platform under $25000. 3 years later, it was possible with early microcomputers and garage assembly, and by 1978 (10 years after the 1130), there were $4000 "personal computers".

And IBM did build an excellent spinoff of the 1130, called the IBM 1800. It was designed for support of real-time control and it was quite successful in that market. The 1800 operating system (SPX?) was very efficient and had an elegant mechanism for plugging in drivers for diverse boards and devices. And importantly, the 1800 (and the 1130) had disk drives with good random access software support. Industrial control systems was the market that the Boca Raton unit served, and that area was largely ignored in Poughkeepsie. And there were a lot of competitors in that market -- including HP and Univac, as well as DEC. Boca was not a retirement community for the engineers!

As to your point 4, there are a lot of stories about the selection of the Intel 8086 for the IBM PC in 1981-2.

As I heard the tale, IBM considered the Xylogics Z80(00), the Motorola 6800(0) and the Intel 8086 as possible platforms, because IBM did not want to commit major funding to chip manufacture (which they saw as "commodity"). They rejected Xylogics because they could not produce the expected volume. The Motorola 6800 was the IBM Engineering preference, but Motorola would not agree to make the necessary manufacturing capacity available for IBM's projected demand. (Motorola in 1982 intended to use much of its increasing capacity to build for another market -- cell phones!) Thus they ended up with the Intel 8086, whose hardware architecture (a re-engineered 1968 design) could not run a 1980-style minicomputer operating system! Intel did not actually build a machine that could run a real operating system until 1994! So, the PC world was stuck with hack operating systems for 10 years. What Bill G saw (that IBM missed) was the seductive capabilities of cheap VGA display, however crude. (And two guys at Apple didn't miss it, either.)

As I said, there are "alternate facts" available. I'm only reporting what I heard from my contemporaneous sources at IBM.

-Ed


-----Original Message-----
From: ontolo...@googlegroups.com [mailto:ontolo...@googlegroups.com] On Behalf Of John F Sowa
Sent: Monday, May 29, 2017 3:11 PM
To: ontolo...@googlegroups.com
Subject: Re: [ontolog-forum] Types of ontologies?

John F Sowa

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May 30, 2017, 11:15:11 AM5/30/17
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Dear Matthew and Ed,

MW
> An IBM 1130 was the first computer I used. Fond memories.

Everybody who used one had fond memories. As Ed says, it was too
expensive for most people to have one full time. Most people would
sign up to use it for an hour or two (sometimes longer, late at night).
But while they sat at the desk, they used it in the same way that they
might use an IBM PC 16 years later. Earlier PCs were more like toys
for hobbyists than serious tools for engineering or business.

EJB
> My first computer was an IBM 1620 -- a serial decimal machine...
> IBM had created a hardware FP for it in 1962

The original version did decimal arithmetic by table lookup, so it
didn't have an adder. The project code name was CADET -- an acronym
for Can't Add, Doesn't Even Try.

The 1130 was a RISC machine. The CPU was designed by Dines Bjørner,
who used the barest minimum amount of circuitry to make it cheap and
fast. Even though the 1130 used IBM's cheapest and slowest chips,
its subroutines for floating point were faster than the FP of the far
more expensive System/360 model 30.

By the way, Dines designed the CPU at IBM San Jose (1963-64) before
going back to Europe. See http://www2.compute.dtu.dk/~dibj/node6.html

> And IBM did build an excellent spinoff of the 1130, called the IBM 1800.

They had the same CPU. The 1130 was configured for a programmer
sitting at a desk. The 1800 was a rack-mounted version designed for
applications, such as process control, in which no human was present.

> Industrial control systems was the market that the Boca Raton unit served

Those machines were designed in San Jose in 1965. The Boca Raton plant
wasn't even built at the time. Instead of extending a highly successful
platform with new technology, Boca management chose the incompatible
System/7 -- a decent computer, but it had no software.

> IBM did not want to commit major funding to chip manufacture

In 1969, a Fishkill engineer (where IBM manufactured chips) designed
a one-board version with System/370 technology. A few years later, it
could have been a one-chip CPU that would have run circles around an
8086 and run mature software that had been in use for over a decade.

> I'm only reporting what I heard from my contemporaneous sources at IBM.

I was at IBM at the time, and I knew many of the people who had been
designing and implementing the technology. I admit that there were
sourcing problems with Motorola. But there were also problems with
Intel. The demand for the PC far exceeded IBM's forecasts, and IBM
had to finance Intel's expansion in order to meet the demand. They
could have used that same money to expand the IBM Fishkill plant
-- if Boca hadn't screwed up.

> What Bill G saw (that IBM missed) was the seductive capabilities
> of cheap VGA display, however crude.

In 1981, Bill G was still focused on programming languages, primarily
Basic. When the Boca Raton guys were looking for an OS, Bill lied
(or bluffed, since he was a poker player) and said that he had an OS,
which he quickly bought for $50K and sold to IBM for a million.

Xerox PARC pioneered the WIMPy interface and hardware. But Xerox HQ
in Rochester was more clueless than Boca Raton management. Steve Jobs
visited PARC and was amazed by the technology. He implemented the
Apple Lisa at a price that nobody bought. In 1984, he released a
cheaper version called Macintosh.

> As I said, there are "alternate facts" available.

Many of the points can be backed up by material on the WWW. For IBM's
Future Systems fiasco, see the "comic book" on "The Adventures of
Task-Force Tim", which was drawn by one of my colleagues:
http://www.jfsowa.com/computer/tftim.htm

For more detail, including links to some public documents and some
that I scanned from my basement archives:
http://www.jfsowa.com/computer/afs/

John

Ron Wheeler

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May 30, 2017, 12:22:37 PM5/30/17
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I was at DEC in the late 1970's and they had a desktop version of the
PDP-11 that ran all of the mini-computer software that ran on the
regular PDP-11.
I suspect that they did not want to drop the price to compete with
Personal Computers since it would have killed their lucrative PDP-11
line in many applications.

It had a mature hardware architecture, supported DECnet networking and a
really large software suite.

My first machine that I worked on as an operator was an IBM 1401 (16kb
memory, no disk drive but 5 tape drives)
I learned to program on an IBM-7040 before getting onto one of the first
DEC-10s.
First video terminal was a Tektronix storage screen attached to a PDP-8.
Still have photos or artwork done on that machine in 1970.

Ron
--
Ron Wheeler
President
Artifact Software Inc
email: rwhe...@artifact-software.com
skype: ronaldmwheeler
phone: 866-970-2435, ext 102

Frank Guerino

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May 30, 2017, 12:26:15 PM5/30/17
to Ontolog Forum
Hi John,

My apologies.  I misread your statement.  Yes, we are in agreement.

I would add that the very vague definition “An ontology is a formalization of a conceptualization” leads us to the realization that just about anything which acts as a formalization can be argued to be an ontology. For example:

  • A specification could be argued to be an ontology.
  • A simple or complex data structure, such as built-in types or classes, could be argued to be an ontology.
  • A virtual or even a physical model could be argued to be an ontology.
  • A physical manifestation of a concept (like a final product) could be an ontology.
    • For example: A physical hammer is technically a formalization of the concept of a hammer.
    • For example: A physical car is technically a formalization of the concept of a car.

How do we eliminate the vagueness?

My Best,

Frank
Frank Guerino, Managing Partner
The International Foundation for Information Technology (IF4IT)
http://www.if4it.com
1.908.294.5191 (M)

Rich Cooper

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May 30, 2017, 12:44:53 PM5/30/17
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Frank,

You wrote:

      How do we eliminate the vagueness?

Let me suggest that it is that very vagueness in communication which is the strength of studying ontologies of various kinds.  Ontologies provide a sometimes well structured way to describe Things that can be communicated to other ontologists who happen to agree, vaguely, on the lexical naming of objects and assemblies of objects.  But what they individually conceptualize may not be at all the same. 

I have seen this within groups writing proposals for systems, among programmers defining software architectures, among managers deciding where to place a large investment, and among friends at a bar discussing work after hours. 

The ontology is just a glimmering wriggling structure.  It’s the studying of various ontologies that helps the studier think of more organized structures to use in the future.  But ontology itself, other than typologies, are not *direct* values.  They are ways to new means. 

Sincerely,

Rich Cooper,

Rich Cooper,

Chief Technology Officer,

MetaSemantics Corporation

MetaSemantics AT EnglishLogicKernel DOT com

( 9 4 9 ) 5 2 5-5 7 1 2

http://www.EnglishLogicKernel.com

From: ontolo...@googlegroups.com [mailto:ontolo...@googlegroups.com] On Behalf Of Frank Guerino
Sent: Tuesday, May 30, 2017 9:26 AM
To: Ontolog Forum
Subject: Re: [ontolog-forum] Types of ontologies?

Hi John,

My apologies.  I misread your statement.  Yes, we are in agreement.

I would add that the very vague definition “An ontology is a formalization of a conceptualization” leads us to the realization that just about anything which acts as a formalization can be argued to be an ontology. For example:

·       A specification could be argued to be an ontology.

·       A simple or complex data structure, such as built-in types or classes, could be argued to be an ontology.

·       A virtual or even a physical model could be argued to be an ontology.

·       A physical manifestation of a concept (like a final product) could be an ontology.

o       For example: A physical hammer is technically a formalization of the concept of a hammer.

o       For example: A physical car is technically a formalization of the concept of a car.

Erick Antezana

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May 30, 2017, 4:44:56 PM5/30/17
to ontolo...@googlegroups.com
Dear all,

thanks for the very interesting replies.

I had been still looking for a "typification" of ontologies. I have decided to stay (at least for the time being) with the one proposed by Guarino (classification according to their "level of generality"):


Such a classification will help me to better delineate the roles and responsibilities of groups I work/interact/collaborate with around our "ontology platform", which mainly holds top-level ontologies and domain ontologies.

@Frank G. : many thanks for sharing your spreadsheet. Very useful directory. FYI: the VEST directory (http://vest.agrisemantics.org/) might be useful to enrich your directory.

best regards,
Erick

On 30 May 2017 at 18:44, Rich Cooper <metase...@englishlogickernel.com> wrote:

Frank,

You wrote:

      How do we eliminate the vagueness?

Let me suggest that it is that very vagueness in communication which is the strength of studying ontologies of various kinds.  Ontologies provide a sometimes well structured way to describe Things that can be communicated to other ontologists who happen to agree, vaguely, on the lexical naming of objects and assemblies of objects.  But what they individually conceptualize may not be at all the same. 

I have seen this within groups writing proposals for systems, among programmers defining software architectures, among managers deciding where to place a large investment, and among friends at a bar discussing work after hours. 

The ontology is just a glimmering wriggling structure.  It’s the studying of various ontologies that helps the studier think of more organized structures to use in the future.  But ontology itself, other than typologies, are not *direct* values.  They are ways to new means. 

Sincerely,

Rich Cooper,

Rich Cooper,

Chief Technology Officer,

MetaSemantics Corporation

MetaSemantics AT EnglishLogicKernel DOT com

( 9 4 9 ) 5 2 5-5 7 1 2

http://www.EnglishLogicKernel.com

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Frank Guerino

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May 30, 2017, 10:46:53 PM5/30/17
to Ontolog Forum
Hi Rich,

You wrote: “Let me suggest that it is that very vagueness in communication which is the strength of studying ontologies of various kinds.

Since the foundation of scientific truth is to establish vagueness in favor of factual specificity, wouldn’t it be fair to say that your statement doesn’t sound very scientific?

You wrote: “Ontologies provide a sometimes well structured way to describe Things that can be communicated to other ontologists who happen to agree, vaguely, on the lexical naming of objects and assemblies of objects.

How do we know for sure?  Given that we can’t clearly define what an ontology is, at an objective level, isn’t your statement tied to your personal/subjective interpretation of what an ontology is?  I’m not saying this to be critical but to bring up the point that anything anyone says about an ontology can be no more than unsupported opinion or, at best, hypothesis without some form of a clear and repeatable baseline for a definition.

So, when you say: “The ontology is just a glimmering wriggling structure.  It’s the studying of various ontologies that helps the studier think of more organized structures to use in the future.”  Do you know you’re studying real ontologies or what people subjectively call and believe to be ontologies?

If we were to say: An ontology contains “these things,” what would such things be that everyone could agree upon?  I believe we both know that this question would lead to an endless debate driven by opinion more than science.

My Best,

Frank
Frank Guerino, Managing Partner
The International Foundation for Information Technology (IF4IT)
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1.908.294.5191 (M)

From: Rich Cooper <metase...@englishlogickernel.com>
Reply-To: Ontolog Forum <ontolo...@googlegroups.com>
Date: Tuesday, May 30, 2017 at 12:44 PM
To: Ontolog Forum <ontolo...@googlegroups.com>
Subject: RE: [ontolog-forum] Types of ontologies?

Frank Guerino

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May 30, 2017, 10:58:14 PM5/30/17
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Hi Erick,

Happy to help.  Thanks for the reference to VEST.  I’ll definitely check it out.

FG
Frank Guerino, Managing Partner
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http://www.if4it.com
1.908.294.5191 (M)

From: Erick Antezana <erick.a...@gmail.com>
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Date: Tuesday, May 30, 2017 at 4:44 PM
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Rich Cooper

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May 30, 2017, 11:07:15 PM5/30/17
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Frank,

That is an interesting set of questions that you rose:

      Since the foundation of scientific truth is to establish vagueness in favor of factual specificity, wouldn’t it be fair to say that your statement doesn’t sound very scientific?

My statement is intended to reflect the actuality of how people fill in missing details for patterns that we expect to see, in the situations we expect to see them in.  That is well known from psychologists conducting experiments designed to show it.  So it wasn't intended to describe science, just to describe known behaviors. 

      You wrote: “Ontologies provide a sometimes well structured way to describe Things that can be communicated to other ontologists who happen to agree, vaguely, on the lexical naming of objects and assemblies of objects.”

I admit it.  What an object does in an ontology is to provide a common concept between the sender of a sentence and the receiver.  When there are more than two people involved, you may have noticed from our past discussion of specific ontologies, there is almost never agreement on much of anything.  So in my opinion, ontologies form in observers' heads in subjective ways dependent on that observer's past experiences of similar situations.  But people don't often get the same experience on the same concept.  So the concept varies from person to person. 

      How do we know for sure? 

That is the point; we can't know much of anything for sure.  We can just keep making up lines of argument, proofs, disproofs, whatever we can leverage the concepts with.  But concepts vary among us, as shown by this list's past history. 

      Given that we can’t clearly define what an ontology is, at an objective level, isn’t your statement tied to your personal/subjective interpretation of what an ontology is? 

Of course.  Just like everyone else's interpretation is personal/subjective because they all had unique experience bases to work from just as I did. 

      I’m not saying this to be critical but to bring up the point that anything anyone says about an ontology can be no more than unsupported opinion or, at best, hypothesis without some form of a clear and repeatable baseline for a definition.

I agree.

      So, when you say: “The ontology is just a glimmering wriggling structure.  It’s the studying of various ontologies that helps the studier think of more organized structures to use in the future.”  Do you know you’re studying real ontologies or what people subjectively call and believe to be ontologies?

Since I believe all personal interpretations are subjective by definition, I am studying my own exposure to many ontologies to help identify ways to treat odd or unusual conflicts in representation. 

      If we were to say: An ontology contains “these things,” what would such things be that everyone could agree upon?  I believe we both know that this question would lead to an endless debate driven by opinion more than science.

No, everyone can't agree on much of anything other than trivialities!  And yes, endless debate unless those on the list are old timers who have heard it endlessly before.  Yet still we persist. 

      My Best,

      Frank

Your best is excellent, thanks for the good questions.

Matthew West

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May 31, 2017, 4:18:52 AM5/31/17
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Dear Erick,

Not quite what you are after I’m sure, but here is a figure from my book “Developing High Quality Data Models” illustrating different types of data model. Note it is a Venn diagram with lots of overlap between the types.

 

Regards

 

Matthew West                           

Information  Junction

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From: ontolo...@googlegroups.com [mailto:ontolo...@googlegroups.com] On Behalf Of Erick Antezana
Sent: 30 May 2017 21:45
To: ontolo...@googlegroups.com
Subject: Re: [ontolog-forum] Types of ontologies?

 

Dear all,

 

thanks for the very interesting replies.

 

I had been still looking for a "typification" of ontologies. I have decided to stay (at least for the time being) with the one proposed by Guarino (classification according to their "level of generality"):

 

 

Such a classification will help me to better delineate the roles and responsibilities of groups I work/interact/collaborate with around our "ontology platform", which mainly holds top-level ontologies and domain ontologies.

 

@Frank G. : many thanks for sharing your spreadsheet. Very useful directory. FYI: the VEST directory (http://vest.agrisemantics.org/) might be useful to enrich your directory.

 

best regards,

Erick

On 30 May 2017 at 18:44, Rich Cooper <metase...@englishlogickernel.com> wrote:

Frank,

You wrote:

How do we eliminate the vagueness?

Let me suggest that it is that very vagueness in communication which is the strength of studying ontologies of various kinds.  Ontologies provide a sometimes well structured way to describe Things that can be communicated to other ontologists who happen to agree, vaguely, on the lexical naming of objects and assemblies of objects.  But what they individually conceptualize may not be at all the same. 

I have seen this within groups writing proposals for systems, among programmers defining software architectures, among managers deciding where to place a large investment, and among friends at a bar discussing work after hours. 

The ontology is just a glimmering wriggling structure.  It’s the studying of various ontologies that helps the studier think of more organized structures to use in the future.  But ontology itself, other than typologies, are not *direct* values.  They are ways to new means. 

Sincerely,

Rich Cooper,

Rich Cooper,

Chief Technology Officer,

MetaSemantics Corporation

MetaSemantics AT EnglishLogicKernel DOT com

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Some Types of Data Model.jpg

Michael DeBellis

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May 31, 2017, 12:42:49 PM5/31/17
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It occurs to me that while we discussed some very interesting things on this thread we didn't actually say much about the OP's question.  I just gave it a few minutes thought but for what its worth here is what I came up with. If I was doing an ontology of ontologies I would start by looking at the structure of the company that was creating the ontologies and I would base my model on that structure.  The business I'm most familiar with is consulting so I took a quick (like 5 minutes)  very rough cut of what an ontology of ontologies would like like for a large consulting firm such as Accenture.  This is just an example, I don't know the business of the OP and if I were doing it I would structure it as they structure their business but I used consulting just as an example. 

I have two main classes: Ontology (the actual ontologies) and Stakeholder (the people who use the ontology). Stakeholders have subclasses: Employees, Clients, and RegulatoryAgencies. Ontologies are divided along the lines that consulting firms divide their business: Service Offerings (Strategy, SystemIntegration, etc.) and Industries (Healthcare, FinancialServices, AerospaceAndDefense,...). Also, key technologies that are critical to the firm such as J2EE and Microsoft .NET (usually there are special nerd groups that just focus on technology rather than an industry or service line, I was always in one of those groups). Ontologies all have standard meta-data metrics such as who created, when created, etc. If I was doing this for real I would look at the literature on Digital Asset and Content Management. An ontology is essentially just another digital asset and I would look at the various meta-data that people have identified for indexing and managing digital assets. My toy example model is attached. 

Michael

On Tuesday, May 23, 2017 at 2:04:41 PM UTC-7, erick.antezana wrote:
Dear all,

I am sure this question has already been asked long ago; however, I was not able to find any good pointer in the ontolog archives...so here it is (possibly again): could you recommend some documentation/definitions about the types of ontologies? 

I typically develop and work on 'domain ontologies' and 'application ontologies' (in the life science arena). To some extent, I have (re)used 'upper level ontologies'... We want to review the way we name and classify those different types of artifacts. Any pointers would be highly appreciated.

I know there could be different classifications, based on specific dimensions such as expressiveness, purpose, coverage, etc. (http://www.springer.com/cda/content/document/cda_downloaddocument/9780857297235-c1.pdf?SGWID=0-0-45-1193345-p174120365). however, I was wondering whether there is any "relatively widely accepted" classification?

thanks,
Erick

 
OntologyModel.owl

Rich Cooper

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May 31, 2017, 3:06:49 PM5/31/17
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Michael wrote:

      It occurs to me that while we discussed some very interesting things on this thread we didn't actually say much about the OP's question.  I just gave it a few minutes thought but for what it's worth here is what I came up with. If I was doing an ontology of ontologies I would start by looking at the structure of the company that was creating the ontologies and I would base my model on that structure.  The business I'm most familiar with is consulting so I took a quick (like 5 minutes)  very rough cut of what an ontology of ontologies would like like for a large consulting firm such as Accenture.  This is just an example, I don't know the business of the OP and if I were doing it I would structure it as they structure their business but I used consulting just as an example.

      I have two main classes: Ontology (the actual ontologies) and Stakeholder (the people who use the ontology). Stakeholders have subclasses: Employees, Clients, and RegulatoryAgencies. Ontologies are divided along the lines that consulting firms divide their business: Service Offerings (Strategy, SystemIntegration, etc.) and Industries (Healthcare, FinancialServices, AerospaceAndDefense,...). Also, key technologies that are critical to the firm such as J2EE and Microsoft .NET (usually there are special nerd groups that just focus on technology rather than an industry or service line, I was always in one of those groups). Ontologies all have standard meta-data metrics such as who created, when created, etc. If I was doing this for real I would look at the literature on Digital Asset and Content Management. An ontology is essentially just another digital asset and I would look at the various meta-data that people have identified for indexing and managing digital assets. My toy example model is attached.

      Michael

    Yes, I agree.  Your point leads to different ontologies for different businesses, of course.  The partitions that best serve each org chart section depend on how they will be used by that section and by the decision makers who resource it. 

    Sincerely,

    Rich Cooper,

    Rich Cooper,

    Chief Technology Officer,

    MetaSemantics Corporation

    MetaSemantics AT EnglishLogicKernel DOT com

    ( 9 4 9 ) 5 2 5-5 7 1 2

    http://www.EnglishLogicKernel.com

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    Frank Guerino

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    May 31, 2017, 10:07:46 PM5/31/17
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    Hi Rich,

    First, I have to apologize for my moment of dyslexia.  I meant to state that the foundation of scientific truth is to establish factual specificity in favor of vagueness.  (This what happens when I rush.)

    I agree with much of what you stated.

    You wrote: “We can just keep making up lines of argument, proofs, disproofs, whatever we can leverage the concepts with.  But concepts vary among us, as shown by this list's past history.

    I just wanted to point out that I have seen and read many debates but not much in the way of true scientific research procedures to prove/disprove ontology assertions.  This is very interesting to me because the same problem exists in the Knowledge Management space, where almost everyone makes up the definition of knowledge to suite their debates.  One massive difference is that this ontology community is heavily rooted in complex data structures for the purposes of computing.  Therefore, maybe, the definition of an ontology for this community should revolve around something like:

    “An ontology is a complex computing or communications data structure or set of data structures that goes/go well beyond traditional Classes, in order to describe, define, and/or specify a bounded domain of operations, such that senders and receivers of such structures can efficiently and effectively interact with each other in a compatible manner."

    John Bottoms

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    May 31, 2017, 10:34:27 PM5/31/17
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    Frank,

    Ontology has to do with "being" if we follow the Latin meaning. My understanding is that this definition entails "all being" or at least "any being".
    Your definition sounds more like a closed world study of being. Do you not hold that open world view?

    -John Bottoms
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    Rich Cooper

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    May 31, 2017, 11:45:32 PM5/31/17
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    Frank,

    You wrote:

        First, I have to apologize for my moment of dyslexia.  I meant to state that the foundation of scientific truth is to establish factual specificity in favor of vagueness.  (This what happens when I rush.)

        I agree with much of what you stated.

        You wrote: “We can just keep making up lines of argument, proofs, disproofs, whatever we can leverage the concepts with.  But concepts vary among us, as shown by this list's past history.”

        I just wanted to point out that I have seen and read many debates but not much in the way of true scientific research procedures to prove/disprove ontology assertions.  This is very interesting to me because the same problem exists in the Knowledge Management space, where almost everyone makes up the definition of knowledge to suite their debates.  One massive difference is that this ontology community is heavily rooted in complex data structures for the purposes of computing.  Therefore, maybe, the definition of an ontology for this community should revolve around something like:

        “An ontology is a complex computing or communications data structure or set of data structures that goes/go well beyond traditional Classes, in order to describe, define, and/or specify a bounded domain of operations, such that senders and receivers of such structures can efficiently and effectively interact with each other in a compatible manner."

        My Best,

        Frank

    The computing part, I disagree with for most (but not all) of the description of an ontology for this group.  I have seen a whole lot of FOL examples and philosophical jargon ("continuants") for concepts I think are much more easily solved in computing than the solutions in the FOL examples. 

    Ronald Stamper

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    Jun 1, 2017, 10:21:37 AM6/1/17
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    Dear Colleagues,

     On 5th May, Frank Guerino asked:

     “If you come across anything you feel is useful, I’d certainly like to see it.”

     Well, I did consider presenting our very different solution to semantics, one based on the concept of ontological dependency that works astonishingly well in practice.  Previous attempts to do so have met with total disregard, so I conclude that a different way of presenting such ideas is needed.

     Therefore, can you help me and others interested in comparing different “ontologies” by pointing to simple canonical cases, small enough for clear exposition but rich enough to employ most of the key concepts and notations?  In the IFIP community working on the analysis and specification of business computer applications, we used the CRIS case about designing a system for administering international working conferences of the kind where the cases were discussed.

     For comparing “ontologies”, I suggest we need something similar.  For example, the case sketched by Berners-Lee et al in the 2000 paper in Scientific American, has it been used to made such comparisons?  If so, where can one find the proffered solutions?  

    Regards,

    Ronald Stamper

    Frank Guerino

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    Jun 1, 2017, 2:34:21 PM6/1/17
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    Hi John,

    I certainly agree with your assessment of my definition.  In theory, this shouldn’t be a real issue, given that just about every ontology is bounded to a specific domain.

    The, the alternative is we move forward with no clear definition and baseline(s) for what an Ontology really is.

    My Best,

    Frank
    Frank Guerino, Managing Partner
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    John Bottoms

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    Jun 1, 2017, 10:57:52 PM6/1/17
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    Thanks Frank,

    But then I wonder. If the ontological work is done within a domain, is there a classifier that recognizes when you are getting close to a domain boundary and prevents entities that would cross that domain boundary? I'm not convinced that SME's can even agree on bounds and one can always argue that bounds should vary depending on context.

    -John

    Ron Wheeler

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    Jun 1, 2017, 11:18:41 PM6/1/17
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    as Led Zeppelin said
    "'Cause you know sometimes words have two meanings."

    If you want to use English or any other human language to describe an ontology, you are going to have to know what domain you are describing.

    If you live in one domain, you stand a very good chance of not being able to know when you have crossed a boundary and are starting to use words that have two meanings.

    Ron
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    Frank Guerino

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    Jun 2, 2017, 12:19:07 AM6/2/17
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    Hi John,

    Good question.  I think it’s fair to say that computers always work within the domain that is specified.  For example, we can create a domain specification for calculating healthcare pathways.  It is fair to say that such algorithms will never accidentally cross into a totally different bounded space and spit out optimal layout calculations for, let’s say, a semiconductor circuit.  However, a human can certainly find a way to combine the two domains in order to create a new broader domain specification, should it make sense to do so and should it become technically viable.  We see this in simpler business domains, where tools like ERP or GRC application have grown to cover needs and collapse applications across what used to be very silo-ed spaces.  Moore’s Law was always a big enabler for such domain combining.

    So, while someone can argue that boundaries should vary depending on context, what we give a computer to work with is “always” bounded in some way, shape, or form.

    An interesting concept is that, while the human mind appears to have endless capabilities to imagine things beyond perceivable boundaries, all human creations (outside the mind) are always bounded.  Hence, we can conclude there can be no such thing as an unbounded ontology because they are all human-created structures that exist outside the mind.

    Matthew Kaufman

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    Jun 2, 2017, 1:22:49 AM6/2/17
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    wordnet is wonderful for this....

    not just 'domain' but also sense.  1 domain could probably have the ability or liklihood of having multiple senses of the meaning of the term inology even within a single domain.

    https://wordnet.princeton.edu/



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