Matthew, Thomas, John, Pat,
Software engineering for DoD, for defense contractors, and for commercial
businesses had the same historic profile. Loads of fun early on, when
individuals were more able to solve problems in wide sweeping ways. Then
the management models for software engineering got enough constraints around
the problem to make it uninspiring, expensive, and nearly always late. And
with less quality to boot. But they have declared that a success because
they can control it now, and that is indeed a kind of success for the
managers.
The number of lines per month per programmer got ridiculously
low when the documentation loads built up, and the quality of the software, in
my opinion, went down as well as the management of software engineers got sweat
shop like. Every field tends to get more and more focused on less and
less.
Sincerely,
Rich Cooper,
Rich Cooper,
www DOT EnglishLogicKernel DOT com
Rich AT EnglishLogicKernel DOT com
( 9 4 9 ) 5 2 5-5 7 1 2
From:
ontolog-forum-bounces@xxxxxxxxxxxxxxxx
[mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of Matthew
West
Sent: Tuesday, March 17, 2015 1:09 PM
To: 'Thomas Johnston'; '[ontolog-forum] '
Subject: Re: [ontolog-forum] SME (subject matter experts) and Ontology
developement - principle? - Ethics?
Dear Thomas,
An anecdote that supports at least your view of IT HR was a time
when I was hiring data modellers/ontologists. The HR guy suggested I set some
metrics to judge the volume/quality of work that was being performed, helpfully
suggesting entity types per day as something suitable. I wrote back saying that
such a metric was problematic because a larger data model might easily be worse
than a smaller one for the same scope, and that one with fewer entity types
might be better and take longer to produce, but if he could think of metrics
that took this into account I would be very interested to hear about them. I
didn’t hear from him, but I did get the data modellers I wanted.
Regards
Matthew West
http://www.matthew-west.org.uk
+44 750 338 5279
From:
ontolog-forum-bounces@xxxxxxxxxxxxxxxx
[mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of Thomas
Johnston
Sent: 17 March 2015 15:45
To: [ontolog-forum]
Subject: Re: [ontolog-forum] SME (subject matter experts) and Ontology
developement - principle? - Ethics?
".... I would emphasize
that really good SMEs who can articulate
the implicit
assumptions in their expertise are rare. The few who have
those abilities are in high demand and can command high fees for their
work. Since your employment at Shell gave you access to experts in the
industry,
you had a luxury that is rarely available in most projects.."
I have worked for, consulted for, or contracted with twenty-four
enterprises over the course of a forty-five year career in commercial IT, a
third of them Fortune 500 companies (and a third of those Fortune 100). I can't
speak for how much value companies put on the (extremely rare) articulate SMEs
you refer to, since they are on the business side of the house. But I can
comment on how much value companies put on BAs who can extract ontological
commitments from relatively inarticulate SMEs (which are most of them), who can
clarify the SME's initially fuzzy requirements statements, and who can design
databases that are ontologically well-founded.
That value is -- nothing. Every company I have worked for has
regarded BA work and data modeling work as commodity tasks, as empty cubicles
(or contractor "pits") which can be filled by anyone who can impress
an interviewer (who usually doesn't know how to interview). The determining
factor is always money, because the hire decisions are made by low- to
mid-level management for whom ten dollars an hour less on a one-year contract
is quite a big deal.
This is not sour grapes. When my rates were forced down by the
fact that hiring managers had no understanding of the added value of my skills
as BA and data modeler, or when I lost out to novices who could just about get
the definitions of the first three normal forms right (about all the expertise
a hiring manager could recognize), well, there were some sour grapes back then.
But I just want to dispel the myths that management, in any
commercial enterprise, can differentiate experts from the rest. They can't.
There are occasionally non-management personnel in commercial IT who command
remuneration that busts the upper limits that HR sets for the job title they
have. Some of them are pretty good, but none of them are that good. Most of
them have a personal style that a senior manager -- VP or even C-level
executive -- has been impressed by. Most of them are distinguished from the
rest of us by nothing more than that.
I don't think that much can be done about this. Hiring managers in
IT departments are where they are because of the Peter Principle, and so the
notion that they would or could ever recognize the value of a BA or data
modeler who had a real facility with uncovering implicit ontologies, is nothing
but fantasy.
Again, I have attempted not to exaggerate. I have found things to
be really this bad. I would be interested in hearing from anyone else with real
world commercial IT experience, especially anyone whose experience is different
than mine.
Dear Matthew,
JFS
> For the future, I believe that we can and should develop*automated* or
> at least *semi-automated* tools that can help extract the underlying
> assumptions from anyone -- even a SME.
MW
> I admire the ambition. Generally, you can only automate things where
> you have reliable and repeatable procedures. We don't. At best we have
> methodologies that need training in, and experience of execution before a
> new member of the fraternity can be welcomed. Indeed at present if I had
to
> choose one of the SME or KE to develop an ontology for a domain, I'd go
for
> the KE. It will generally be easier for him to become an expert in some
> domain, than for the SME to become a KE.
I agree. But there are huge numbers of tasks that could benefit from
ontologies, but only large corporations or governments can afford to
train KEs to that level of expertise. Even large businesses don't
use ontologies as well or as often as they could because they require
a very clear "business case" before they would consider that expense.
Hashtags and folksonomies are a "poor man's" replacement for
ontologies.
The next step up are things like Schema.org, which are slightly more
than systematic terminologies. There are millions of people on that
continuum from hashtags to folksonomies to Schema.org to the highly
structured ontologies used at Shell.
And there are many people (VivoMind included) that are designing novel
technologies for addressing the continuum. For examples, look at the
methods for automatically extracting ontologies from documents:
http://www.jfsowa.com/talks/goal7.pdf
This is still a research area, but work is proceeding at many
institutions. I expect the new tools to revolutionize the methods
of software design and development. The examples in goal7.pdf are
promising steps. And such tools can also be used to enable today's
KEs to address new areas of expertise more rapidly and thoroughly.
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