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Re: [okmds-convene] Definition of Decision Support

To: Ontology in Kowledge Management & Decision Support <okmds-convene@xxxxxxxxxxxxxxxx>
From: Harold Lehmann <lehmann@xxxxxxxx>
Date: Wed, 02 Jan 2008 10:31:12 -0500
Message-id: <6hqbgh$4enn7@xxxxxxxxxxxxxxxxxxxxxx>
If I might add $.02---First, it is often important to recognize the line that separates workflow/functions, explicable to stakeholders and users, from design/implementation.

"Decision support" is "above" the line, because system designeres should be able to communicate the type of support users receive in language they understand; "ontologies  lie "below".the line, because of the technical knowledge needed to appreciate them. "Documents" are above the line, because they are directly readable by users. Ontology structures are, again, below, because they are primarily machine readable.

What I don't see discussed in KM postings---and perhaps I misunderstand scope or realities---is knowledge representation (KR): transforming above-the-line knowledge into computable formats other than ontologies, such as rules, guidelines, logic rule bases, probability networks, etc. I

s there a reason why the focus on KR seems always to be on the ontology to support document access and retrieval rather, as was mentioned, than the decisions (alternatives) and utilities/tradaeoffs, as well as other decision-theoretic concerns, like underlying probabilities, structures, time horizons, outcomes, applicability, and perspectives? (acronym: You SHOULDT: You (perspective), Structure, wHo (applicability), Outcome, Uncertainty, List of aLternatives, Desires/traDeoffs, Time horizon).

Harold


At 01:07 AM 1/2/2008, you wrote:
Thanks for your perspective.  See my comments below.

On Tue, 1 Jan 2008, Phil Murray wrote:

> Ken --
>
> Excellent way to start the discussion. I agree with everything you propose,
> but -- especially given the Project's broad goals ("The need to effectively
> administer 'knowledge space' to yield meaningful connections that are
> scalable and sustainable is a strategic challenge of all institutions,
> whether that knowledge resides primarily within, outside, or across an
> institution's span of control.") -- I would add some perspective and points
> of emphasis. My comments are interspersed, below.
>
>
> On Jan 1, 2008 12:16 AM, Ken Baclawski <kenb@xxxxxxxxxxx> wrote:
>
>
> KB> Welcome to the New Year!  I propose that the first "resolution" for the
> OKMDS community this year should be to examine the definition of decision
> support.
>>
>> It is easy enough to define "decision support system" to be a
> computer-based information system that supports decision making activities.
> However, this says very little, since so many activities are related to
> decisions in some way.  As a result, decision support is a very broad
> concept, and there are many different kinds of system that are considered to
> be decision support systems. This may partly be due to the fact that
> decision making is a process.  A particular decision support system will
> usually be designed for and have an impact on only a few parts of the
> decision making process.  The decision making process has at least the
> following parts:
>>
>> 1. Acquire relevant background knowledge.  This could include other
> decisions.
>
> I would emphasize the *discovery* aspects of knowledge acquisition.
>
> And the "knowledge" discovered should be expressed in a way that is ...
>
> -- Easily understood -- in a variety of contexts -- by a broad cross-section
> of participants.
>
> -- Retrieved and managed predictably and easily by applications.
>
> -- Encapsulated in such a way that the decisions (or, perhaps more broadly,
> the "assertions") can be referenced easily. (Also relevant to your point
> #2.)
>

Excellent points.

>>
>> 2. Identify the alternatives from which a choice must be made.
>
> Given the potentially very large set of assertions that could be contributed
> in an open community, we need to address the negative in a positive way --
> that is, we need explicit ways to quickly evaluate any assertion as
> irrelevant. Separating the wheat from the chaff effectively is especially
> important when making important decisions.

Agreed.  It is important both to eliminate the irrelevant alternatives and
to avoid missing alternatives that might not immediately be seen to be
relevant.  However, this is a rather different notion of relevance than
that used by search engines, even search engines that are sensitive to
ontologies.

>>
>> 3. Determine the criteria that should be used to distinguish the
> alternatives from one another (typically in the form of a value or utility
> for each alternative).
>>
>> 4. Select the best alternative.
>>
> Here's where the ambitious goals of the OKMDS community present a challenge,
> which you also address in points #1 and #2 of "managing the process," below.
>
>
> Decision support (whether in the model of military situational awareness or
> in making decisions that reflect enterprise business strategy) typically
> involves a limited set of alternatives and a relatively small number of
> vetted participants. The "collaborative environment" of the OKMDS needs
> scalable methods and tools for evaluating assertions.
>
> One of the first things we need is to have participants in this community
> help identify the strategies and technologies that most effectively enable
> distributed evaluation of a *large* set of alternatives. Of course, I'm not
> talking about a popularity contest. This isn't "American Idol." (Give
> yourself 5 culture points if you *don't* understand the reference.) Or Digg.
>
> If John Sowa, Leo Obrst, Pat Hayes, or Ken Baclawski submits an evaluation
> of an assertion, that evaluation should be worth more than, well, mine. Is
> this where we get into some form of Social Network Analysis?

There is a place for popularity in a democracy.  In that context my vote
is worth the same as any other.  However, it would much better if the
choices presented to the electorate were in terms of the outcomes
(utilities) rather than the alternatives.  The role of the experts should
ideally be to elucidate and quantify the relationships between the
alternatives and the outcomes.  This is where there is a distinction
between individuals and where social network analysis could be valuable.

>
>> Both knowledge management and ontologies can play a role in each of these
> parts.  They can also play a role in managing the process, such as:
>>
>> 1. Manage the process workflow in structured decision making processes.
>>
>> 2. Provide a collaboration environment for decision making.
>>
>> 3. Manage the documents associated with the process.
>
> But, as noted above, not just the documents ... or multimedia. We also need
> to manage the decisions themselves.

Agreed.  However, that is what I meant by #1 and #2 above.

-- Ken

>>
>> I suggest that this framework could be the starting point for a more
> in-depth discussion of decision support.
>>
>> Kenneth Baclawski
>> College of Computer and Information Science Northeastern University
> Thanks,
>
> Phil Murray
> Founding Member
> The Center for Semantic Excellence http://www.semanticexcellence.org
>
 
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*******************************************************************************
Harold P. Lehmann, MD PhD
Associate Professor, Health Sciences Informatics
Joint: Pediatrics, Health Policy and Management
Johns Hopkins University
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