Reworking k representation

Knowledge representation is complex, confusing, difficult, emerging and evolving - So how do we deal with it?

What is k representation?

Ad hoc sketches, informal, qualitative and physical models, scenario construction, concept maps, rule sets, structured text, voice and video recordings all serve as representation, reflecting the expectations and experience of their creators, they connect collaboration to future use. They serve a dual role: (a) to facilitate design and critique and (b) to serve as the holder for the product to be, they are affordances in design, which they can enhance or inhibit.

Representations, clarify, extend, complete and move unique experiences and abstract ideas toward the essential and typical. Representations are physical, tangible and material, they allow ideas and experience to have an independent existence in an externalized form, they help to capture emergent thought. Like a lump of clay, a representation is tangible and tactile, it can be pointed to, passed around, played with, reshaped and stored. It takes thought experimentation one step further, eliciting new ideas.

On the formal side representations can be used for inference, in reasoning and as symbols, think rule sets, cases, predicate logic, spatial reasoning.

Representation as container

Boundary objects (concept maps, ontologies, source documents) serve as a vehicle, container and carrier, for ideas and meaning (reification). When a representation crosses (community) boundaries, there is often a loss of meaning and context, which is counter-balanced by an opportunity for new negotiations, different views and altered meaning. This points to the importance of establishing rationale & context in use or practice, an essential non-represented aspect associated with any formalism. All representations are situated in use. An important aspect of a memory object is its trajectory, i.e. the consequences of later use.

Capturing knowledge?

We use stories, cases, tags, metaphor, rules, heuristics, diagrams, patterns, templates, FAQs, lessons learned, learning histories...... what we then capture may be information rather than knowledge - if our key knowledge is tacit, embedded, emergent, present as a flow rather than a store, requires continual interaction and negotiation, is situated and distributed. No representation can stand on its own, we need an appreciation of the setting as situatedness, is ubiquitous, subtle and mostly represents a context that is just 'below our radar'.

Annotation (in the widest sense) is emerging as the forgotten stepchild of e-Learning and knowledge creation. This goes way beyond appending PosIt notes, writing in the margin or sequential replies to the editor; to collaborative writing & editing, refractoring, annealing text, awareness, pull notification and joint work at the artifactual level. Annotation is as much about continual 'access to edit your words', i.e., changing from serial static publication to continual revisiting and revising the script, as it is about telling your cohorts to come and 'see', comment, change and interact. These two aspects,: (a) empowerment to change another's text, and (b) unintrusive notation must join the representation dance together.

• Hargadon & Sutton, HBR May/June 2000, 157-166, talk about keeping ideas alive by encapsulating them in prototypes, metaphor, collecting and playing with junk. Stories are recognized as important representation for conveying values and meaning.

Collaborative concept mapping is a useful way to capture, refine and extend ideas and to explicate relationships. There are some interesting tools emerging as part of web2.0 that cover this.

There is no single formalism that is optimal under all circumstances, so be aware of these attributes when you select a way to represent knowledge - rather think in terms of a mix - a representation ecology :

• Do I need to capture values, context and allow for a flexible 'translation'? - stories, analogy, metaphor
• Will I make use of formal (automated) reasoning? - rules, predicate logic, cases
• Is it important to capture emergent thoughts? - wiki, open-space, sketch walls, PosIT notes & white-board, digital audio / visual recorder
• Do we need flexibility to gather and arrange emergent stuff? - index cards, white-boards, tags
• Is context and sequence important? - patterns, flow diagrams
• Are relationships and flows a key aspect? - maps, networks, concept mapping
• What type of knowledge will be involved? - declarative, procedural, inherited, inferential, temporal...

How then do you capture knowledge?

 

Comments

[Rosie]

These comments have been invaluable to me as is this whole site. I thank you for your comment.

[Sean Murphy]

I think Michael Schrage made an excellent point that effective collaboration reqires a shared workspace. It can be a cocktail napkin that two people can take turns sketching on, a sheet of graph paper, a whiteboard, "paper dolls" (cards or cut outs that present aspects of a configuration).

From his interview with Tom Peters
http://tompeters.com/cool_friends/content.php?note=007965.php

But what I saw—company after company—was that the innovation wasn't just about creative individuals, but about creative relationships—and particularly collaborative relationships.

And collaborative relationships need shared space (any collaborative medium—cocktail napkin to computer modeling that serves as communication space that two or more people share). After my first book came out, Shared Minds, I realized that I had to focus on this ... if we care about the future of collaboration we have to care about the future of shared space ... there's a real ecology there. Then prototypes became a fabulous vehicle for interacting within the process of innovation, within a shared space.

When I was a new reporter I was concerned with getting good quotes. Now, when I work with teams and consult, the gap between what people say and what they do is far more interesting. I became much more concerned about behaviors around prototyping, whether it's designers around the screen or marketers around models; design behaviors take a big shift around prototypes.

Behavior changes matters more than technological change.

In the world of newspaper journalism, language, fidelity to fact, and the interpretation of those facts in print are central concerns. In the real world—behavioral issues are much more critical. (In the real work of innovation) I view models and prototypes as battleground for thought and behaviors.

[David Locke]

Saying that "Representations are physical, tangible and material, they allow ideas and experience to have an independent existence in an externalized form" should not be taken to mean that the representation is necessarily explicit.

It will have to be explicit for KM practitioners to attempt to sell it like they do, as they cannot handle the implicit or tacit and certainly can't maximize the value of such resources as was the promise of KM.

You capture that knowledge without explicitness. And, you use it while it is still explicit. No, you don't have to capture it in text or wikis or boundary objects.