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Re: [ontolog-forum] Just What Is an Ontology, Anyway?

To: "Tolk, Andreas" <atolk@xxxxxxx>
Cc: "[ontolog-forum] " <ontolog-forum@xxxxxxxxxxxxxxxx>
From: "Burkett, William [USA]" <burkett_william@xxxxxxx>
Date: Wed, 28 Oct 2009 10:38:51 -0400
Message-id: <50993AD402A48B4F8C7E42A9CC2029540FEADF34@xxxxxxxxxxxxxxxxxxxxxxxxxxxxx>

Which makes perfect sense, Andreas, because my education and background is in Industrial and Systems Engineering.  I agree 100% with your observations here and I think ANY ontology, anywhere, is just another model that is biased with the some perspective, limited by the same scope as any other model, and designed with a purpose just like any other model. 

 

Bill

 

From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx [mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of Tolk, Andreas
Sent: Tuesday, October 27, 2009 12:54 PM
To: '[ontolog-forum] '
Subject: Re: [ontolog-forum] Just What Is an Ontology, Anyway?

 

This viewpoint is not completely new to everyone. In particular in the modeling & simulation community, the idea that each model represents – very similar to an ontology – a viewpoint needed to address a given challenge (the model was build to help solving a problem, and the viewpoint needed to solve the problem becomes the viewpoint of the model) becomes predominant. Each model is a purposeful abstraction and simplification of reality, again similar to an ontology. What George E.P. Box said about models (“All models are wrong, but some are useful.”) is true for ontologies as well. In other words: each ontology contributes a different facet to a description, and in order to get the whole picture, all facets are needed.

The only common ontology description integrating everything is the world (if we exclude imagination of what could be to make the problem a little bit easier), but we could not use the world to answer our problem in the first place, that is why we developed a simpler model for our use.

Long story short: we do not need a common ontology, but we need a common way to describe our work allowing the mediation of viewpoints. As our worldviews differ in scope (what we look at), resolution (detail we are looking at), and structure (categorization of what we are looking at), these mediations will not always be loss-free, but that is part of the nature of the beast.

It seems like we are starting to come to very similar observations and reach mappable conclusions in different scientific domains.

 

Andreas

 

 

From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx [mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of Burkett, William [USA]
Sent: Tuesday, October 27, 2009 2:30 PM
To: [ontolog-forum]
Subject: Re: [ontolog-forum] Just What Is an Ontology, Anyway?

 

Bravo, Rich – this is the first time I’ve heard anyone in any of these ontology/SUO forums stress so strongly the human-factor aspect of data semantics.   I’ve been trying to argue this point for years but to most CS-trained individuals it just falls on deaf ears.   I even have a nice little catchy name for the theory:  “Data Is Speech”.    As you suggest, there will be multiple ontologies (or whatever you want to call them) to formally represent different views of the word and they will need to be quickly adaptable to changing business requirements .  And the one significant missing and way way underserved ingredient is mapping and translation technology. 

 

Bill

 

From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx [mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of Rich Cooper
Sent: Monday, October 26, 2009 9:24 PM
To: '[ontolog-forum] '
Subject: Re: [ontolog-forum] Just What Is an Ontology, Anyway?

 

Sincerely,

Rich Cooper

EnglishLogicKernel.com

Rich AT EnglishLogicKernel DOT com

 

Dave McComb wrote:
Ontologies, in my mind, offer a way to help sort, categorize and organize the chaos we've created.  We have to integrate the old with the new as we go forward, but this isn't as hard as it sounds.  SOA has given us the general technological approach, Semantics is adding a layer of rationalization on top.

 

Nicely stated - I'm still reading Karl Popper's Logic of Scientific Discovery, which is a dramatic reminder of the subjectivity we brush aside so easily.  Remember that the people who entered all that data into the database in the first place were each individuals with their own internal ontologies.  

 

The first problem in any database, even prior to formalizing “the” ontology or (more effectively, “some” ontologies) is to find ways to ascertain the meaning of data recorded there.  I described that in detail on my web site at:

www.englishlogickernel.com-Patent-7-209-923-B1.PDF

 

For example, when a Yes/No answer is mixed with 1/0, 2/1, T/F, True/False, and MIXTURES of the above (yes, T/1/F/0, 2/1/0 and other mixtures are possible since people are not consistent systems).  Attempts to force fit the answer into a very precise type of form (T/nil) leads to frustrated users, GUI programming errors, confused analysts and lots of data entry errors because most users don't have a real stake in most systems they deal with.  

 

For a few lucky enterprises, there may have been "the" enterprise ontology by designers who thought it might be useful.  In my experience, every enterprise system database evolves faster than the IT staff allocated to manage it.  There is too big a loop between the user with her needs and the developers who make changes.  

 

Meaning is in the eyes of the people who provide the data, and lots of that meaning is subject to human judgment, valuation diversity, and just plain old personal preferences.  Then there is the meaning in the perceptions of data analysts who try to make sense of the user data, or find patterns there, typically not having the original users available at the analyst's moment of investigation.  

 

But between the data entry person and the analyst, there may be lots of other users reading, perceiving, populating, editing, and otherwise in their own eyes "adding" meaning to the data by changing the original source data cells – all to meet their own individual ontologies.  So the typical enterprise database is full of classes and properties that shouldn't be there (given “the” ontology), but in fact they are.  Even worse, the variations are the main source of information in businesses looking for ways to improve profit, service, quality or other metrics.  The changes in data, the variations, contain the most information.  

 

Education and training of staff to enter data "the right way" is a hopeful tactic, but almost a waste of time, and users mostly still do what they think is good on the spur of the moment, just like the rest of us.  People work in our own conceptual ways, we deal with everyday situations in our own lexicon, grammar and thought processes, and "education" applied in that way is more appropriately called "indoctrination".  It tries to “fix” the users’ dynamic flow of structural information instead of adapting to that changing flow by processing a changing ontology with changing projected user ontologies.  

 

So the only conclusion I can reach is that "the" enterprise ontology, if singular, is a dynamic and variable entity that is no more fixed than any other specification to be implemented real soon now.  Forget about selecting ONE, and expect multiple ontologies; the transition sequencing from one to another (the periodic version update) is likely to become more manageable that way.  Expect ontologies to be iterative and plural, not fixed and singular. 

 

I think every user might some day have her own ontology.  Localizations and personalization can be used to adapt "the" ontology to a wider range of individual user needs as much as writing specialized queries in SQL which takes development labor.  

 

Surely a "semantic" application will influence the user's GUI behaviors in some dynamic way.  So if "the" ontology is dynamic, then "her" ontology must be getting calculated from "the" ontology either very quickly or very incrementally to meet GUI performance requirements.  

 

JMHO,

-Rich


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