Knowledge-at-work

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?

 

Cycling to knowledge

• What do we really know about those knowledge practices that involve a strong cyclic component? 
• Can we alter the rate, depth, relevance and utility of knowledge generation by enhancing the cycle visibility, being mindful of our place in the cycle, changing frequency and other properties?

Idea generations and dialog turns

Would we build shared understanding faster if we supplied regular summaries or if we had strict time-limited events and interactions such as a turn taking rule in conversation and dialog? I guess the essential question is, will ideas (or memes) develop faster, be richer and go further, if we force the generations to turn over quicker? This assumes you buy into the notion of a thoughts or an idea birth, development (mutation?) and retirement / death in the first place.

What I'm trying to understand is the value of regular summarization and open group reflection to those participants already in the conversation? I can easily see the value to new arrivals and can appreciate the need to have diversity and participant churn.

For my money, it goes around the practice, value and depth of reflection, the opportunity for making new connections and surfacing novel insights afforded by good summary. What happens if the role of summarization is rotated in the group rather than falling on the single (same) shoulders each time?

OODA loops

A meta-practice in military thinking is to deliberately speed the Observe - Orient - Decide - Act  or discover - reflect - act cycle so as to disorientate and confuse an adversary. Being agile, willing to alter course, evaluating conditions and going with the flow, has proven to be useful for survival, speeding innovation and building resilience - but can it also improve intelligence and result in greater knowledge formation?

Enumerative description (ED)

Is an interesting way to capture local perceptions and experience of situations. Expert(s) gather to look for invariance across their domain and select the questions that best define the current situation. These questions are distributed in the form of a survey template. Individuals then supply answers in natural language. ED is integrated into a larger picture with work-flow, pre-processing to uncover the invariance and natural language tools to generate reports from the returned templates. The returns can be analyzed for variance (a measure of group alignment?), for longitudinal change and trends, after significant events. This human-in-the-loop may be essential for awareness & anticipation.

Argument mapping

Concept and reasoning mapping makes the rationale visible, explicit and shareable. Mapping revisions assist with making new connections, expose poor logic, capture thinking and augment group memory. The practice of visual thinking is still poorly defined. We know little about sequence, revision frequency, spatial location & clustering, influence of color, typing links and optimal ways to 'interrogate' a diagram.

Altering and imposing interventions on these cyclic activities can have far reaching cumulative consequences - changing how we may think, reason, interact, learn and decide!

Double loops on steroids.

Making connections!

Louis Suarez has bestowed the dubious honor upon me by tagging me in his recent post. I notice others have beaten me to the post and thus contributed to the propagation of this meme - nothing more powerful than asking a blogger to reflect on themselves!

What others may not know (or care to know?) about me:

My introduction to expert systems (hence KM) came during a visit to Saasveld South Africa in January 1985 by Professor Tony Starfield He talked about modeling decisions and capturing expert heuristics - a transformation on 01/13/1985 that changed my thinking forever.

Roughly 80% of my personal memory is still available via the Web Archive. We leave larger footprints than we ever imagine!

We have a very international family - daughter-in-law from Japan, son-in-law from Zimbabwe.

My roots are in ecology - forestry, soil science and geomorphology - now I make high tech carbon fiber bicycle components for Zipp, working on RFID, responsible for web site management, podcasts and internet sales.

I met Nancy White way back in 1998, Louis  Suarez in 2006 and  Patrick  Hindert in 2001, all virtually before we  connected f2f.

Tagged:  my KM  mentors:  Verna Allee,  Etienne Wenger, Philippe Baumard,  George von Krogh and Edwin Hutchins.

Case-hardened books

Certainly there is a change happening in the book world - from self-publishing http://www.lulu.com/ to wikipedia and blogs. Sure there are times when 'hard' copy is useful, structure & sequence, expert review and editorial skills do add value and a tangible asset just makes sense.

When I think about the affordances of the digital world (RSS, collaborative writing, facile annotation, networking, hyperlinking, multimedia) the increasing need to remain updated and aware, the ability to connect, converse and learn separated from time and distance - I'm starting to look at the book as being 'case-hardened' , frozen in place, immutable. When I consider the long editorial and publication cycles, I'm thinking out-moded, plodding, slow and being left behind.

The e-movement is certainly changing things. You may enjoy this new book / pdf / wiki / flick'r group / .... that looks at how knowledge itself is changing.

http://ltc.umanitoba.ca/KnowingKnowledge/index.php/Main_Page - the wiki form

Knowledge & knowing

New book just released

George Siemens has kindly released his new book as series of .pdf files  which you are free to download, or you can read and contribute to the wiki conversation, or you can thumb through the excellent graphics on Flickr

In this book George looks at ways the context around knowledge is changing and the influence this is having on knowledge itself:

1. The rise of the individual - ability to voice and show, blogs and YouTube
2. Increased connectedness -  affordances for conversation
3. Immediacy and 'now' - knowledge half-life is shrinking fast
4. Breakdown and repackaging - new tools allow rip, mix and burn
5. Prominence of the conduit - new publishing  media have opened things
6. Global socialization - networking everywhere from MySpace to SecondLife
7. Blurring worlds of physical and virtual - 'on the go' becomes the norm

KnowingKnowledge - wiki

The KnowingKnowledge wiki has been released along with a related wiki where George Siemens has invited readers to critique and contribute to his collaborative keynote addresses.

Thinking back to my review of KnowingKnowledge, it struck me that George pays relatively little attention to knowledge representation in his writing. This may be expected as he concentrates on how knowledge is changing and notes a shift from 'hard' to 'soft' knowledge, where soft = more immediate, more emergent, more closely tied to conversation than content. Knowledge says George is now more than ever about "the now', and connections trump content in a world of immediacy and 'know now'. As we capture more ephemeral content in audio and video files, I'm wondering what we need to do to get the most from these media as representations & knowledge stores?

Here is a screencast of his collaborative keynote address  and an interview text for Online Educa Berlin, in December '06.

IMO KnowingKnowledge is an important event, I'm looking forward to the hard copy book release (now 10/10 I'm hearing), publication of the graphics on flick'r, availability of pdfs for downloading and most of all to the conversations George wishes to build around his thinking.

This is a subject that matters more than most in KM - for without a clear understanding of what knowledge really is and how it is changing - KM will continue to go in circles. Please join in this important conversation, let's hear your opinion, beliefs, mental models, heuristics and practical tips so we can all grow a little wiser together.

KM principles

What would you select as the top knowledge management principles?

Here are some thoughts?

Choose engagement over a repository:
Knowledge emerges via interaction and dialog, connect people to people rather than people to objects / documents or things. If you need to record and gather things ensure there are affordances for facile annotation and back-channel connections. Pay attention to knowledge flows rather than stores.

Respect and appreciate the key role of trust & context:
Shared context, connections and trust allow knowledge to flow.  Knowledge, far more than information, is part of our identity. There needs to be empathy and purpose to make headway. You cannot toss knowledge over the wall and expect it to take root - knowledge requires an ecology to grow.

Collect stories, use metaphor, ethnography and analogy to build inquiry:
Knowledge is local, mostly tacit, emergent, distributed and tied to shared understandings. Measurement and collection via questionnaires is inadequate, questions are key. Take care to specify context, share distinctions, craft and verify patterns - best practices do not transfer easily.

Cultivate executive support:
No KM initiative can be sustained without some measure of (tacit) top level support. It does not help to have a signature, you need active engagement and behavior change to filter down the organization.  KM requires a core group to start & sustain the conversation, a legitimate forum or space to meet and purpose to guide attention.

The essence of KM

• increasing awareness
  Helping you (or your group) become aware of new things, changed situations, emergent players that may influence the domain you have chosen to work in.
• fostering learning
  assisting with making novel and useful connections between concepts, improving understanding and enabling environments for making and testing new insights.
• supporting sense-making
  KM needs to be proactive, help surface consequences, avoid past errors, generate worthwhile & inventive alternatives.

Decisions, solutions, agility, competitive advantage and other benefits follow from sustaining a questioning environment, encouraging creative abrasion & experimentation, promoting deep dialog and allowing space for learning from mistakes.

The key for KM then lies deeper than pragmatics, it gets close to sustaining an environment, building trust, promoting continual inquiry and testing beliefs.

KM, I then suggest is:
A practice concerned with increasing awareness, fostering learning, speeding collaboration & innovation and exchanging insights.

There is a delicate balance to be maintained between explicit and tacit, between personal and community, between collecting assets and enabling flows, between looking inward and externally, between mining and capturing insights and building on shared experiences.

Please share your KM principles.

KM in wikipedia

How would you write the definitive entry for knowledge management in Wikipedia?

We have seen many attempts to define, circumscribe, explain and codify KM within Wikipedia. The current version still leaves much room for improvement. So where would you start and what would you alter?

The article IMO tends to be written from 'software' perspective rather than an attempt to cover the topic, show the difficulties with KM definitions and bound the domain.

The initial section does not cover the KM domain adequately IMO. Key concepts that are missing are:

• A short definition - What KM is all about
• A summary (with links) to KM framework documents
• The origin and history - how and why did KM arise? What makes KM a worthwhile and pertinent distinction? What are the related domains?

I would like to see the section on key KM concepts expanded to cover:

• Knowledge types & nature - why this has been a difficult topic within KM
• Knowledge acquisition - missed anything on ethnography, narratives, metaphor, patterns, knowledge mapping
• Knowledge sharing & transfer - collaboration, innovation, awareness, learning, agility
• Intellectual capital - role in competitive advantage and innovation
• Corporate memory - approaches to 'knowing what we know' and retaining experience

KM drivers - this is great as is

KM enablers can be improved by:

• Linking to Web2.0 efforts and technologies
• References to advanced practices - concept mapping, pattern languages, visual thinking, ontologies, folksonomies, open editing, VoIP and more.
• Adding a piece on KM affordances - facile annotation, personal profiles & portfolios, voicing via blogs, social network analysis

I would rewrite the piece on 2nd generation KM to include KM maturity / capability models, explain recent thoughts on KM and complexity and the role of emergence, knowledge landscapes and core attractors.

The lack of any reference to PKM, and the omission of key authors such as George von Krogh, Dorothy Leonard, Karl Wiig and Etienne Wenger needs urgent correction.

So what is your take?

Building blocks of knowledge

When you put knowledge formation or creation under an ethnographic microscope what do you see?

At the heart of knowledge creation lies conversation, shared language, agreement on key distinctions, naming of prime concepts, sharing of experiences or beliefs, the explication and testing of patterns.

We need engagement, deep dialog and creative abrasion to suspend individual mental models, grab attention and overcome inertia, we need purpose, perceived value, common goals and difficult questions to drive inquiry, surface and explore connections, deepen our understanding and make sense of things.

Distinctions are knowledge atoms, the way we separate an object from its background and from similar objects. Once we recognize a meaningful difference and apply a name, we start to seek & make connections, explicate tacit feelings and beliefs, test utility, classify and assimilate, make predictions and examine assumptions.

Questions are the key to turning tacit know-how into social knowledge. Questions help knowledge emergence, test beliefs, guard against personal bias and incorrect mental models. The empowering environment or culture for knowledge formation is one where no one is afraid to ask dumb questions as there are really no dumb questions - just think back on the many times you have benefited when someone else had the courage to ask first!

Metaphor and analogy help with explanation, contrasting, connecting and meaning making. A metaphor establishes relationships, encourages finding obscure similarities, exploring emergent differences and improves communication. Metaphors are how we code experiences.

A shepherd that helps with pattern drafting, introduces the pattern to the community, assists with revisions and final scripting, is a key player in knowledge crafting.

When you next practice ethnography, looking to discover how knowledge flows, where it emerges, why it is hard to capture, who has it - think: distinction, questions, metaphor and pattern - those building blocks will help you make sense of a difficult task.

Boundary objects revisted

Reading the recent discussions around KM and ethnography hosted by Richard Cross at AOK, I was reminded of the very useful role boundary objects often play when you are looking to understand roles, activities, tacit knowledge and working methods.

I often use boundary objects as a framework in knowledge mapping, where they provide a useful way to organise observations, give the participants something tangible to hang their observations, gather their stories and focus the inquiry.

My practice is to identify the key BOs and then to track these across internal organizational boundaries, watching for language changes, differences in meaning, noting changes in importance, reification and seeking informal feedback that happens. Boundary objects are useful when searching for learning points, looking for process improvements, digging deeper into subtle meaning shifts and authority perceptions.

Boundary objects can be a useful starting point for developing an organizational taxonomy, they touch many communities, carry meaning, record status changes or serve as alerts. The passage of a BO initiates activities, enables self-organization, informs on progress, starts or sets time-lines.

My understanding of the role, nature and importance of BOs in knowledge work has been greatly helped by reading Edwin Hutchins "Cognition in the wild" and Susan Leigh Star's many papers.