From: omk@jyu.fi (Oiva M Kuittinen)
Subject: AI & EDI
Organization: University of Jyvaskyla, Finland
Date: Thu, 30 Jul 1992 14:28:24 GMT

I have followed the recent AI & EDI discussion with great interest.
Some readers of this list will remember that, last autumn, I was looking
for ideas on the use of Knowledge Engineering in EDI. I have a number of
reasons not to use the acronym "AI" - one of them is that the concept is
too broad. Although I dropped KE & EDI as a research subject, I did my
best to find related material and ideas: therefore, I now intend to 
summarize my findings (at the end of this posting).

First, however, for some comments on the EDI-L discussion. Bill Laidley's
posting of 19 Jul mentioned an AI Expert column - I have not seen it yet
but am familiar with the international contracting work done by Lee and
Dewitz. Having introduced the notion of a "performative network" supporting
legal procedures and coexisting with other EDI-related services, they 
discuss the usage of AI to help model legal reasoning (together with Petri
nets). Prof. Lee has implemented a CASE tool for contracting & natural
language translation support. While interesting, this is nowhere near actual
implementation and usage. Also, Lee & Dewitz do not describe the AI
component of their work in great detail.

As for the excerpts from the column, natural language processing based
format conversion could be possible: an example would be a program which
would try to find out which in-house file fields correspond to X12/EDIFACT
data elements (with rules like: "Look for a 30-40 character field with
a name like CUST*"). This would be computer-assisted data mapping. I agree
that "intelligent" EDI software packages will have an appeal, but not
before the right development targets have been found.

John Nagle's vision (21 Jul) is a good illustration of what the ISO 
Open-edi model is all about: a rule-based "business" layer atop the data
oriented EDI stack. A United Nations working group is looking at Interactive
EDI which would support this kind of "conversations". This seems to be
the way to go, but not before most of the problems hampering EDI development
have been solved. I join Randall Smith, then, in wondering when this all
will happen. Obviously a lot of research needs to be done in the meantime.

Then for Bill Laidley's 28 Jul posting where he covers different aspects
of "AI". Expert systems (which I equate with Knowledge Engineering - the
kind of Artificial Intelligent I have personally been looking at) could
indeed assist in mapping (e.g. in the way described above) and maybe
standards usage, but wouldn't network message explanation be stepping on
providers' toes? *grin* Rule-based transaction validation also seems to
be a fruitful problem domain. As for CASE tools, there is a methodology &
tool set called EDICASE, produced by a (presumably Belgian) company 
called ITS. Should any one of the list readers have the contact details for
ITS, I am sure many people would be interested. As for the rest, I don't
think Object Oriented Analysis/Design/Programming are really AI (although
objects are also used for knowledge representation), no comments on the
other categories.

Now, at long last, for what I found out about current and potential use
of Knowledge Engineering in EDI. Apart from the Lee & Dewitz research
mentioned earlier, I know of research started in Australia (on audit of
EDI transactions, system integration, project management and intelligent
directory services) and in Finland (application level protocols). I've
heard a Japanese bank uses an expert system for EDI message error
diagnostics. Finnish EDI software developers suggest that knowledge-based
techniques could be used for transaction control and security, semantic
error analysis, log visualization and a number of other things - but this
is all mere speculation. My own development efforts had to do with a
knowledge-based system for analyzing errors in received EDI messages
on the basis of error information provided by (conventional) EDI software.
An example would be finding out if the occurrence of alphabetic data in
a numeric field is due to a difference in how the sender and the recipient
apply transaction sets or to a separator character having been "lost" while
the data was being transferred. Finding rules proved (not surprisingly)
to be hard. Experts seem to solve such analysis problems in a manner
resembling the so-called case-based reasoning paradigm.

Finally, I drafted a model of EDI knowledge (expertise) which could be
used as a framework for classifying EDI expert tasks. In my view, EDI
knowledge can be organizational, application (such as invoicing system),
system integration, standards, communications, or EDI software related.
I would be grateful if anyone interested in discussing this model could
contact me.


Oiva Kuittinen (Internet: omk@jyu.fi, Bitnet: omk@finjyu)
University of Jyvaskyla, Finland










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