That was excellently summarized, and I
agree; what management thinks is knowledge in textual resources is most often wasted,
and the ontological aspects are at best secondary in importance to the context.
But that context, through computer assisted analysis, can calculate a de facto
ontology that fits the database’s actual contents.
A clear example is the USPTO patent
database, which provides valuable text structure in a well edited database
containing both structured columns and unstructured text columns. The
technical knowledge in that database is valuable, and could use such analysis
as described in
But I disclose that my self interest is
involved in suggesting it.
Rich AT EnglishLogicKernel DOT com
9 4 9 \ 5 2 5 - 5 7 1 2
[mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of Phil Murray
Sent: Tuesday, January 04, 2011
Subject: Re: [ontolog-forum] Quote
for the day -- KR and KM
This is actually rather humorous -- not because
it is wrong or unreasonable in any way, but because this is one classic
perspective on "knowledge management" (KM) ... and because the
majority of KMers decided that [this] was not possible and/or not the right
thing to do. By "this" I mean the following specific points:
Ed Barkmeyer wrote:
I think we are in agreement on this. My take, based primarily on
discussions with manufacturing executives and a handful of consultants,
is that what the senior executives want right now is three things:
(a) a means of organizing the captured corporate knowledge, so that it
can be searched and retrieved by people who discover they need it. The
problem with the captured knowledge is that it is mostly in text form,
with some formal models and structures in various languages and tools.
Yes, but KMers failed to make a well-reasoned distinction between internalized
("tacit") knowledge and knowledge that could be represented
explicitly, preferring instead to argue endlessly about the difference between
the two, framing (a) "tacit knowledge" as something that could only
be captured through personal experience and application and (b) "explicit
knowledge" as the stuff of search engines, content-management systems, and
(more recently) "social technologies."
Ironically, some early KM gurus coined the term "knowledge engineer"
to describe the activities of various KM professionals. They were completely
unaware that KR people had been using the term in a very specific way for many
In theory, this is the kind of thing we ought to be able to do better
with ontologies, and it is a direct application of some of the Semantic
Well, ontologies are not at the core of the problem as stated. Yes, ontologies
are an essential component of a much-needed overall model and associated
process that is built primarily on how people communicate, disambiguate,
evaluate, integrate, manage, and apply meaning. Such a model must enable
contributions and modifications in isolation, in the same way that
well-designed RDBMS applications do.
The answer is hardly limited to developing something to meet the needs of
reasoning tools alone -- except for well-defined requirements, of course. And
it is certainly not limited to Semantic Web ideas.
(b) a means of capturing corporate knowledge that may otherwise be lost
as senior staffers retire or are attracted to other firms.
Again, yes. In KM circles, this has been labelled
"brain drain" and a few other tags -- discussed ad nauseam. But the need is not at all
limited to senior staffers.
The idea here is to do the
knowledge engineering 'from the horse's mouth'.
Yes, but -- as noted previously -- the source of
working knowledge is not limited to experts ... nor is it, at the other
extreme, an emergent product of implementing social media.
Ontologies can provide formal definitions of classes
and properties (in terms of 'more fundamental' ones), which allows us to
deduce relationships, recognize (or declare) synonyms, and recognize
inconsistencies in the 'schemas' themselves.
And you will find KMers who sneer at such an ambition,
using our inability to capture "knowledge" perfectly as a false straw
man. Personally, I have never encountered a KR professional -- in person or in
this forum -- who claims that it is possible or desirable to do so.
The problem with delivering any of these results is tying the bell on
the cat's neck. Some team of knowledge engineers has to get down and
dirty with the text resources and the individual company practitioners,
and tease out and formulate all of the knowledge that is presumably
resident in them. And then the knowledge engineers have to go back to
many of these resources to resolve some of the confusion and conflict.
That is an expensive process for the CEO, not because of what the
consulting ontologists cost, but because of the time of his/her
corporate personnel assets that is consumed. Further, it is a risky
process, precisely because it exposes the knowledge that is the
corporate advantage to external eyes and ears. Unlike Toby's tag line,
this is an activity that must be done well -- thoroughly and carefully
-- to be worth doing at all.
Well, first of all, if you view the solution solely
from the perspective of C-level personnel (on the one hand) or
technologists/knowledge engineers (on the other hand) you've already lost the
The desirable starting point is the relationship between communication and work
as a method of producing value, efficiencies, or improvements -- *not*
representing and reconciling concepts, although the latter is also essential.
I repeat, Ed, that everything you say makes good sense. But these are lessons
managers of organizations should have learned already ... and didn't,
ironically, for many of the reasons you state.
Chief Knowledge Architect
The Semantic Advantage
Turning Information into Assets
Web site: http://www.semanticadvantage.com