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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.
Henson
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.
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