Re: [ontolog-forum] More by and about Turing

[Ravi Sharma <drravisharma@xxxxxxxxx>]

John and Tom

• Where can I find examples?
• Could we say that Gene Ontology, FIBO, OBO, NCBO are good examples of ontological tools and yes the pros will decide how good as they use or upgrade.
• John you have addressed in past and Tom has referenced these but summary is that what RDBMS' can not do alone, ontologies can do by providing additional info+ what RDBMS provide.
• Additional value in ontology tools comes from of course logic but also from richness in predicates as compared to "relational" (RDBMS) alone?
• How will Big-data analytics and machine learning be enhanced by ontology tools?

Regards,

Ravi

One more reference:

http://efasoft.blogspot.com/2011/08/why-do-we-need-ontologies-in-healthcare.html

On Sun, Jul 19, 2015 at 9:44 AM, Thomas Johnston <tmj44p@xxxxxxx> wrote:

Ravi,

I think that the greatest practical value of ontologies is to interpret the types which are expressed as tables and columns in relational databases whose rows are instances of those table types, and whose row-column intersections are instances of those column types. Table types are kinds, what Aristotle called secondary substances. Column types are properties or relationships. And so this task of interpreting those types uses an upper-level ontology which is basically Aristotelian to organize database-specific types. 

Further, I claim that this ontology is descriptive, not prescriptive. Basically, it's the ontology we use to think about Things. (I had to extend it, in BDTP, to include events.) Being descriptive, it follows that it is stable. Being the ontology (of Things) that we all use, it follows that (IMHO) it should be used as a universal core upper-level ontology.

If this were done, and if SQL were extended to maintain type data as well as instance data, then those who query databases could (i) express more general and thus more powerful queries than they can today, and (ii) could discover types of data (tables and columns) in databases so organized, that they did not already know were there.

I've already described this research program of mine in earlier comments. And I've already encountered disagreement with my contention that databases are mainly about instances of types -- about specific customers, not the type customer -- whereas their catalogs express the purely formal features of the property types and relationship types that define the tables themselves and the columns of those tables.

Regards,

Tom

On Sunday, July 19, 2015 2:11 AM, Ravi Sharma <drravisharma@xxxxxxxxx> wrote:

John

What are the gains from developing or using ontology tools/ solutions? Do they not put existing (verified independently) scientific theories and models (Content) in different light, e.g. better than relational data models / views of scientific data contents? etc.?

Regards,

On Sat, Jul 18, 2015 at 6:45 PM, John F Sowa <sowa@xxxxxxxxxxx> wrote:

Leo, Ravi, and John B.,

Leo
> Reality doesn't change; our descriptions/theories do...
> Metaphysics, from which philosophical ontology springs, is useful
> as a body of discriminating thought/reasoning, that helps you
> filter nonsense, provides guidance as you look at the world and
> the possible/probable things in it.

On those points, we completely agree.

Ravi
> Does not metaphysics include assumptions to define reality
> expressively even though one may understand their own model
> of nature of physical universe?

But assumptions about what?  We have to distinguish form and
content.  Science is always fallible.  We can be fairly sure
that most of what we believe about the world is reliable as
far as it has been thoroughly tested and verified by repeated
checking by independent observers.  But we can't be certain.

Ravi
> These heritages have early knowledge including discovery of zero,
> innumerability, infinity, and lot of early logic and arithmetic
> and decimal system.

Those are mathematical principles.  They are certain because the
assumptions (notations and axioms) are based on human conventions.
The conclusions are true because they follow from the assumptions
by a very rigid and precise logic.

But we can never be certain that any particular mathematical theory
is absolutely precise about any aspect of the world.  There is always
an experimental error.

And there are always surprises about areas that we hadn't tested
-- and even more surprises about things we couldn't even imagine.

General principles:

  1. There exists a reality that is independent of whatever we believe.

  2. Standards in science are *never* about content.  They're always
     about conventions.  For example, how do you measure anything,
     record the measurements, communicate them, and reuse them?

  3. All measurements are relative.  The only numbers that are
     absolutely precise are conventions:  One kilometer is exactly
     1000 meters.  One inch is exactly 2.54 cm.  One degree C is
     exactly 1.8 degrees F.

  4. Ontology can *never* be more certain than science.  Like science,
     the only certainties in ontology are conventions about form.
     No ontology can ever be more certain about any empirical content
     than the science that is devoted to studying that content.

John B.
> Interesting theory about interactions of particles, what does
> it say about gravity?

Nothing.  It's a recent discovery about the quantum mechanics of the
subatomic particles.  Nobody has yet integrated QM with gravity.

There are still many surprises left about issues as fundamental
as space, time, gravity, and the nature of matter and energy.
Any metaphysics that claims to be more certain about these issues
than physics is guaranteed to be *false*.

John

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Thanks.
Ravi
(Dr. Ravi Sharma)
313 204 1740 Mobile

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