Replying to LO24828 --
Greetings,
Doc, thanks for taking up my questions re knowledge communities [LO24828]
let me test a few assumptions and dig deeper here:
Knowledge objects in your reply refers to the Outsights representation? I
wonder how adaptable your system is. If it is problem driven, does this
not keep the focus on yesterdays issues rather than casting your eyes to
the horizon for tomorrows needs?
>Patterns are key to creating redundancy and interconnectedness among
>knowledge objects and the structured complete thoughts (statements) which
>comprise a knowledge object.
You are talking about patterns between knowledge objects. How does this
fit with the pattern language of Christopher Alexander? I'm wondering if
you have experience of communities establishing links between their
knowledge objects and then using this to leverage communication and deeper
thinking?
How exactly do they balance awareness with problem solving and local
learning?.
Here I'm thinking about the relative amount of time and reflection given
over to scanning for new stuff, evaluating changes in the environment vs.
the learning from working with problems. Your answer seemed to suggest a
(major focus on?) on local problems as the route to learning.
My experience has been that groups that focus on explicit and formal
capture are way in the minority and that tacit => explicit knowledge
transfer mostly takes place in informal conversation than via a structured
data or knowledge base.
The connection between ontologies and alignment happens around the
negotiation & selection of concepts or in your case knowledge objects. I
guess an ontology in Outsights would be the collection of named objects.
Most of the knowledge communities I'm familiar with are far less formal in
terms of their adherence to explicit process than the Outsights community.
Their boundaries are a fuzzy us / them rather than access and security
rights to a knowledgebase and very explicit intellectual property.
Seems there are advantages to going the structured explicit (knowledge
object) route in terms of validation, workflow, finding gaps and laying a
basis for double loop learning. I wonder sometimes what the subtle
trade-offs are?
1) Reduced peripheral engagement?
2) Less scanning, client driven agenda?
3) Process dominance over free dialog?
4) Discarding insights that do not fit the model?
5) Lower or lack of significant social networking?
I can't help feeling a knowledge object approach is much like the rule
based expert systems we were building back then, bold, brittle and
bounded. Would greatly appreciate your feedback.
--"Grey, Denham C." <dgrey@iupui.edu>
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