Hans,
I agree that conceptual and social realities are important. I view them as
part of physical reality, but be that as it may. My concern is that the physical
realities that I mentioned do not appear to have received much discussion, and
they are critically important for many applications of ontology to be
successful.
Henson
Sent: Thursday, February 20, 2014 5:49 PM
Subject: Re: [ontolog-forum] Making use of
ontologies
Henson,
I
wouldn’t limit what needs to be described in ontologies to the physical world.
Much of what we do concerns itself with conceptual and social realities, not
just physical realities. For example, the existence and structure and
relationships of organizations, governments, social institutions and cultures
can’t really be detected as such in the physical world, although there might be
some physical manifestations of these conceptual/social realities. In your
closing down a bank example, for instance, there’s a whole lot more involved
than shutting the bank building, and much of that involves non-physical
relationships and non-physical “money” (unless you consider bits and bytes on a
computer as the physical reality of the money that the bank manages). Of course,
these kind of realities can cause physical actions, and may be impacted by
physical actions, but you can’t rely simply on physics/chemistry to determine
what those actions and impacts might be. You have to interact with people or
representations of people created knowledge and constructs to get a complete
picture of all the operational realities involved in whatever you are trying to
accomplish, like trying to determine what food processing standards the plant in
question might need to comply with.
Hans
From:
ontolog-forum-bounces@xxxxxxxxxxxxxxxx
[mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of
henson
Sent: Thursday, February 20, 2014 5:25 PM
To:
ontolog-forum@xxxxxxxxxxxxxxxx
Subject: [ontolog-forum] Making use of
ontologies
In my experience, we and our machines
use ontologies to describe and interact with the physical world. This means that
for ontologies to be useful they have to have some accompanying physical
semantics, not just a translation into some other concepts or words, or even an
axioms to describe their meaning. I am of course strongly in favor of axiomatic
semantics for ontologies. But even with axioms there need to be procedures for
constructing or recognizing if something is in a specific category. One might
call this an operational semantics. This is model theory in the sense of logic,
but it does not come for free, even when there is an axiomatic semantics.
Taking “if it walks like a duck, …” a
bit further, a vehicle design description may use an ontology with categories
such as physical object, with specializations for some particular kind of steel.
The physical semantics is generally a procedure to recognize or test for that
kind of steel. A big problem for
replacement parts for commercial aircraft is the presence of counterfeit parts.
Often these recognition procedures, as well as procedures for performing tests
and analyzing test results, are quite complex, with their own ontologies to
describe them. However, these ontology applications are only successful when the
physical semantics can be agreed on in the community where the ontology is used.
Practically the successful use of an
ontology depends on having a well-defined explicit operational semantics. It is
the operational semantic issues that cause the tears, and litigation. This does
not necessarily mean that everyone agrees with the definition, but they
understand how the concepts are being used in a given
context.
I presume that the customer who takes
possession of an oil refinery checks to see if it has all of the equipment which
the customer is expecting. I know this is the case with other large expensive
industrial products. If some regulatory agency is faced with closing down a
bank, or a food processing plant, the issue is likely to be how do we measure
the conditions which trigger action.
I am not sure that this aspect of
ontology use has gotten much attention in the recent
discussions
Henson Graves
Sent:
Wednesday, February 19, 2014 7:23 PM
Subject:
Re: [ontolog-forum] Good ontologies without good tools are
useless
Hi
Henson and all,
We are finding similar requirements in finance, as I'm
sure Mike Bennett would echo. The ontologies that are needed to support
compliance and understanding the nature, risk and opportunities related to
complex securities, annuities, and other financial instruments are necessarily
far richer and more rigorous in their definition than what I have seen over time
from a linked data / big data perspective (although the systems that do or will
use them are quite large and the data volume certainly qualifies as big
data). The services that are needed to support both regulators and bankers
require reasoning of various sorts, including but not limited to rule-based
inference, classification, and machine learning. Systems to support fraud
detection, anti-money laundering, insider trading detection, and many other
processes have been using rule-based reasoning for decades.
Use of UML
for software engineering has been fairly widespread in banking and insurance for
many years, and retraining information architects in those industries to use it
for ontology development (with ODM stereotypes) is not as big a leap as
attempting to get them to use Protege or other ontology tools. Another
advantage is that the UML models, which can be exported to OWL or some other
rule language, are available immediately for reuse in the software applications
folks are developing. This minimizes reinvention of the vocabulary used in
development. Use of the same ontologies in rule-based systems, again
rather than reinventing the vocabulary, also dramatically reduces error,
especially if the methodology includes analyzing the ontologies to ensure they
are logically consistent prior to reuse.
For those that are interested,
we are in the process of publishing a new version of the ODM at the OMG, which
addresses a number of deficiencies we've found in implementation over the last
several years. ODM 1.1 supports most of RDF 1.1 and provides better
support for OWL 2, although the work there is incomplete. We plan to have
a 1.2 version of the specification by sometime this summer that will fix the
remaining known problems and provide complete coverage of OWL 2. Both
specifications and related artifacts will be available from the OMG site once
they are approved by the membership. That process is largely complete for
ODM 1.1, with a couple more process steps remaining, but the spec should be
public soon. If I had to guess, I would say the 1.2 version will be
available by this fall, if not sooner. We considered waiting to publish
until we were "done", but so many changes had already been made that we really
needed a new baseline to work from.
For OMG members, the Ontology
Development Metamodel (ODM) 1.1 Revision Task Force (RTF) report, documents, and
all of the model artifacts are already available on the ODM 1.1 RTF work in
progress page. They should become public when the process hoops are
complete, possibly by sometime next month.
Members of the ODM revision
task force include some of the same folks who have been working on the SysML
specification, and who really understand the value proposition, as Henson puts
so well below. The task force also includes a couple of the major UML
vendors -- No Magic and Sparx -- and there are beta tools for both No Magic's
MagicDraw and Sparx EA available.
Best regards,
Elisa
On
2/18/2014 8:52 AM, henson wrote:
I
work with engineers who have a day job and recognize that they need ontologies
to do their work. [I have a lot of experience with being in their shoes.] The
ontologies are needed to model, i.e., describe and specify systems and their
operations in the real world. The models are used to design and analyze
vehicles, aircraft, etc. The recognition of the need for ontology is that the
operating environment descriptions need to be much more complex and are much
more changeable than they were 50 years ago. The use of ontology also
increasingly applies to some of the systems being built. They use ontologies
to process the enormous volume of data that they ingest at operation time, and
use some inference to take actions. The software of some of these
systems contains a model of the system as well as its environment which it
uses at runtime for flight control and threat avoidance.
To
be of any use the ontologies have to be imported into the development tools
which they use. The mostly UML based tools (including SysML) are now
robust, ordinary engineers can and do use them to develop large complex
systems. By and large these folks cannot or will not use traditional logic
syntax. Also there are not commercial grade tools that have been proven in the
industrial context. This doesn’t mean that these language don’t need a formal
semantics, and need extensions to handle the applications that they are being
used for. They do. I have been arguing for a long time that the formal methods
folks should focus on retrofitting and evolving these tools, rather than
attempting to develop new ones.
As
a practical note, I believe that the SysML community is more receptive to
something such as William Frank advocates than the UML community. The reason
being that sociologically the engineering community has to deal with a much
broader scope of applications than the UML community. If the battery fire on a
commercial aircraft causes a crash then the manufacturer will certainly be
sued and will be asked to produce the analysis and test results that were used
to declare the aircraft safe to fly. If these results are not compelling the
manufacture is in big trouble. Engineers are beginning to get this.
As
a comment on Ron Wheeler’s comment the ontologies I see in the big data world
if they deserve the name ontologies, are currently much simpler than the kind
of ontologies mentioned here. However, if these systems are to be used for
medical diagnosis, and drug design and analysis then they will have to have
the complexity of the ones I am talking about.
I
do not know of anywhere within a university context material relevant to this
discussion is being taught. There presently doesn’t even seem to be any
traditional departments willing to pick this up, in my limited
experience.
By
the way, I am passing along John’s slides to a group I am working with which
is in desperate need of an upper ontology.
Sent:
Tuesday, February 18, 2014 9:15 AM
Subject:
Re: [ontolog-forum] Good ontologies without good tools are
useless
Yes,
UML based on a many-sorted higher order predicate calculus with Henkin
semantics, and a simple upper ontology represented by the sorts -
this
is what we (Joauquin Miller, Kevin Tyson, and I) proposed for UML 2, in Clear,
Clean, Concise (3C) UML
Communications
of the ACM, Nov 2002, volume 45, no. 11 pages 79 - 81.
"The
Clear, Clean, Concise (3C) UML2 proposal makes the language
easier to
understand and enables it to describe a broader
range of systems, from Web
agents and services to entire
business
communities."
This
was never going to happen, at that point. The agenda was set by Oracle
and IBM, with no regard for the benefits to the long term future of systems
engineering. Also, I misunderstood people so much that instead of
referencing the science, I simply explained the BENEFITS, and showed how
simple it was to use this language, so I now suspect they thought this
was some new off-the-wall approach invented by us three.
I
agree with all you say below, John, but add that an equally important feature
integrated into a cosistent set of of UML models, along with the 4 you list,
are state - transition models, the backbone, in my opinion, for precise
behavior specifications. Myself, I find UML diagrams, with my OWN
simple simple common logic semantics, the most effective way to ensure a
system consistency, because of all these integrated models.
On
Tue, Feb 18, 2014 at 9:11 AM, John F Sowa <sowa@xxxxxxxxxxx>
wrote:
John
M, Henson, et al.,
....
Just imagine how things might have developed
if Guha -- who had been
the associate director of Cyc and later the chief
designer of RDF --
had adopted UML in the mid 1990s.
Guha said that
the reason why he designed RDF is that CycL was too
difficult for most
users. I agree with him. But software developers
in the 1990s
were happily using UML diagrams. The UML notations,
tools, and
methodologies can support
1. Type hierarchies (the backbone of
every ontology),
2. ER diagrams (logical signatures and
cardinality constraints),
3. Activity diagrams (links between
the logic and the procedures),
4. Controlled natural languages
(more readable than OCL for stating
rules and
constraints that go beyond #1, #2, and #3).
I admit that I'm making
these criticisms with 20-20 hindsight.
In fact, I blame myself even more
than I blame Guha or anybody else
-- because in the mid 1990s I was
participating in ISO working
groups on standards for a conceptual schema
(i.e., ontology).
At that time, I was proposing logic as the
foundation. If I had
proposed UML and points #1, #2, #3, #4 defined
in FOL, an ISO standard
for ontology (AKA conceptual schema) might be
mainstream IT
today.
John
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