OK. Full circle. To John an "ontology" is what somebody had in his head when
he wrote the legacy software.
I thought we had agreed sometime back that FOR THIS FORUM, we need a stricter
definition of 'ontology' that relates to explicitly engineering knowledge in a
formal language that can support inference.
Now, John may believe that there are 'ontologies' written in COBOL, but I do
not find it productive to this community to agree. (01)
As David said, the legacy system will not have an 'ontology' with which any
formal 'ontology' could reasonably 'interoperate'.
The legacy system will include the encoding of a great many knowledge elements
and operating rules in data-centric terms. For the most part, "interoperation"
between an ontology-based application and the legacy information system will be
a matter of converting the information in the legacy system to a form useful to
the technology used in the new system. The real problem lies in determining
how to perform that step correctly, based on whatever documentation, clues, and
expert knowledge are available. (02)
-Ed (03)
--
Edward J. Barkmeyer Email: edbark@xxxxxxxx
National Institute of Standards & Technology
Engineering Laboratory -- Systems Integration Division
100 Bureau Drive, Stop 8263 Office: +1 301-975-3528
Gaithersburg, MD 20899-8263 Mobile: +1 240-672-5800
________________________________________
From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx
[ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of John F Sowa
[sowa@xxxxxxxxxxx]
Sent: Saturday, February 16, 2013 2:12 AM
To: ontolog-forum@xxxxxxxxxxxxxxxx
Subject: Re: [ontolog-forum] Architectural considerations in
Ontology Development (04)
On 2/15/2013 11:26 PM, David Eddy wrote:
> And since pretty much by definition there is NO ontology for the legacy
> systems. (05)
No. That's not true. (06)
Every application program is based on an ontology of the entities
and processes in the application. The primary difference is in
the way that ontology is represented and used: (07)
1. Implicit: The only ontology about the subject is in the mind
of the programmer, and not in any form that can be examined
and used by any other agent -- human or computer. (08)
2. Stated in the requirements. The ontology is represented,
formally or informally, in some document that specifies the
domain of the application and requirements for what it does. (09)
3. Object level. The ontology is represented in a form that can be
processed by programs that use it to reason about the subject. (010)
4. Object level + Metalevel. The ontology is explicitly represented
in a form that can be processed by tools that reason about the
ontology, translate it to object-level operations on the data,
and use it to reason about and process the data. (011)
In our discussions in Ontolog Forum, we have focused on levels 3
and 4. Levels 1 and 2 also use ontology, but not in form that is
formally represented and processed. (012)
> Unless, of course, there's some magic that can extract usable
> ontologies from existing systems in a week or so. (013)
There is. In fact, the first major application of VivoMind software
did exactly that. It analyzed software (COBOL programs and other
computational and database resources), developed a hierarchy of
the types and relations in the software and the names used to
refer to them, and translated the information to conceptual graphs. (014)
Then it used that information to analyze English documents about
the software -- manuals, reports, emails, comments, etc. It
generated cross-indexes of the documentation and the software
and checked for discrepancies. For further discussion, see
Slides 138 to 146 of (015)
http://www.jfsowa.com/talks/goal.pdf (016)
> But I'm pretty sure such practical reverse engineering is
> of minimal interest to the Ontology world. (017)
That depends on which world you're talking about. Certain people have
no interest in anything except proving theorems about decidability.
That application was very interesting to the people who paid for it. (018)
> This week I've seen what appeared to be a promising corporate glossary. (019)
Just look at those slides. As a by-product of the analysis, the
program generated a data dictionary for computer use and a glossary
for human use with cross references to both the software and the
documentation about it. (020)
John (021)
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