John (01)
Thanks, I like the explanation in points 1-3 and also last two bullets
on Science and Engineering. (02)
The question is: (03)
How is Ontology (Theoretical field like philosophy - which by the way is
often the basis for understanding science and phenomena also sometimes
called metaphysics by some physicists - and root of Mathematics) related
to Science?
- Are all Scientists in essence Ontologists also, especially as often
science is trying to understand and model or conceptualize objects (also
phenomena) and relationships (associations)?
- Are all Ontologists also Scientists whether or not they have a
concrete objective (i.e. Mathematicians are not always concerned with
this physical world phenomena but often concentrate on the abstracts,
will also come into category of Scientists here for this purpose)? (04)
Thanks. (05)
Ravi (06)
(Dr. Ravi Sharma) Senior Enterprise Architect (07)
Vangent, Inc. Technology Excellence Center (TEC) (08)
8618 Westwood Center Drive, Suite 310, Vienna VA 22182
(o) 703-827-0638, (c) 313-204-1740 www.vangent.com (09)
Professional viewpoints do not necessarily imply organizational
endorsement. (010)
-----Original Message-----
From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx
[mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of John F.
Sowa
Sent: Tuesday, May 20, 2008 5:12 PM
To: [ontolog-forum]
Subject: Re: [ontolog-forum] Data Models v. Ontologies (again) (011)
Sean, Ed, Anders, Adrian, and Sharma, (012)
I sympathize with your comments, but I'd like to make some points
that may clarify some of the issues: (013)
1. Ontology is a theoretical field (essentially a branch of
philosophy), and data modeling is an engineering field. (014)
2. Engineering fields frequently apply theories from more than
one branch of science. (015)
3. For data modeling, the theories include ontology, logic,
and a variety of theories developed in computer science
and information technology. (016)
SB> A data model assumes a set of entities, and the choice of which
> entity to use is implicit, both as natural language text in the
> data model, and in the input processes of the system embodying
> the data model. A data modeler is primarily concerned with
> meeting the information requirements of the system rather
> than characterising the entities, and records those aspects
> (attributes, properties, characteristics) of the entity of
> relevance to the functioning of the system. (017)
I'd replace the phrase "assumes a set of entities" with the phrase
"assumes an ontology". That makes it clear that some kind of
ontology is required for data modeling, but it's not the only one.
Those other concerns involve the applications and goals that are
not considered in purely theoretical studies. (018)
EB> First rule: "ontology" is IN; "data model" is OUT. (019)
I agree, but as one of the early adopters of the term 'ontology'
(in my book that appeared in August 1983), I almost wish that I
hadn't used the term. I tend to cringe at the way people use
it nowadays. (020)
SB> Characteristics which may be important to a data modeler,
> such as the time an entity was added to the system, would not
> be significant to the ontologist, since the time the entity is
> added in no way helps identify what sort of thing the entity
> is (where in the lattice it sits). (021)
That distinction is typical of an engineering discipline.
An engineer must consider many requirements of an application
that are outside the scope of various theories that are being
applied. Since an engineer will often use more than one theory
in the design of any system, it will rarely happen that every
aspect needed for the application is covered by every theory
that is applied. (022)
Sometimes an engineer's work will contribute to the scientific
field on which it is based. But it is always important to
distinguish the goals of the scientists (or ontologists) from
the goals of the engineers who apply their theories: (023)
- Science is the pursuit of knowledge, independent of any
particular application of that knowledge. (024)
- Engineering is the application of science for the purpose
of solving some problem within the limits of available
resources and deadlines. (025)
John Sowa (026)
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