Chapter 5
Knowledge Capture Systems:
Systems that Preserve and
Formalize Knowledge
Chapter Objectives
 To describe what are knowledge capture
systems
 To explain how to elicit and store organizational
and individual knowledge
 To discuss the value of organizational
storytelling for knowledge capture
 To explain the two types of knowledge capture
systems
 To capture knowledge in educational settings
 To capture tactical knowledge
What are Knowledge
Capture Systems?
• Knowledge capture systems support process of
eliciting explicit or tacit knowledge from people,
artifacts, or organizational entities
• These systems can help capture knowledge existing
either within or outside organizational boundaries,
among employees, consultants, competitors, customers,
suppliers, and even prior employers of the organization’s
new employees
• Knowledge capture systems rely on mechanisms and
technologies that support externalization and
internalization.
Knowledge capture systems
• The development of models or prototypes, and
the articulation of stories are some examples of
mechanisms that enable externalization.
• Learning by observation and face-to-face
meetings are some of the mechanisms that
facilitate internalization
Using Stories for Capturing
Tacit Knowledge
Organizational stories:
 “a detailed narrative of past management actions,
employee interactions, or other intra- or extraorganizational events that are communicated
informally within organizations”
• include a plot (or plan), major characters, an
outcome, and an implied moral
• play a significant role in organizations characterized
by a strong need for collaboration
Organization stories ...
• Important to capture and transfer tacit
knowledge
• stories make information more vivid, engaging,
entertaining, and easily related to personal
experience and because of the rich contextual
details encoded in stories, they are the ideal
mechanism to capture tacit knowledge
Using Stories for Capturing
Organizational Knowledge
• Guidelines for organizational storytelling
(Dave Snowden, 1999):
 Stimulate the natural telling and writing of stories
 Rooted in anecdotal material reflective of the community
in question
 Should not represent idealized behavior
 An organizational program to support storytelling should
not depend on external experts for its nourishment
 Organizational stories are about achieving a purpose, not
entertainment
 Be cautious of over-generalizing and forgetting the
particulars
 Adhere to the highest ethical standards and rules
Eight steps to successful storytelling
1.
2.
3.
4.
5.
6.
7.
8.
•
Have a clear purpose.
Identify and example of successful change.
Tell the truth.
Say who, what, when.
Trim detail.
Underscore the cost of failure.
End on a positive note.
Invite your audience to dream.
In story telling, it is not just what you say but how you
say it, that will determine its success.
Using Stories for Capturing
Organizational Knowledge
• Important considerations:
 Effective means of capturing and transferring tacit
organizational knowledge
 Identify people in the organization willing to share
how they learned from others
 Use metaphors to confront difficult organizational
issues e.g. time is money
• Storytelling provides a natural methodology for nurturing
communities because it:
 builds trust
 unlocks passion
 is non-hierarchical (told in the form of peer dicussion)
Other consideration for
effective story telling
• People must agree with the idea that this could
be an effective means of capturing and
transferring tacit organizational knowledge.
• Identify people in the organization willing to
share how they learned from others about how
to do their jobs.
• Metaphors are a way to confront difficult
organizational issues.
• Stories can only transfer knowledge if the
listener is interested in learning from them.
Where can storytelling
be effective?
•
•
•
•
•
•
•
•
Igniting action in knowledge-era organizations
Bridging the knowing-doing gap
Capturing tacit knowledge
To embody and transfer knowledge
To foster innovation
Enhancing technology e.g e-mail can connect people 24/7
Individual growth – avoids competition, mutual benefit
Launching/Nurturing communities of practice
 thematic groups (World Bank)
 learning communities or learning networks (HP)
 best practice teams (Chevron)
 family groups (Xerox)
Techniques for Organizing and
Using Stories in the Organization
• Anthropological observation
 naïve interviewers
 asked innocent and unexpected questions
 caused the subjects to naturally volunteer their
anecdotes (or story) or subjective views
 curiosity resulted in a higher level of knowledge
elicitation
Techniques for Organizing and
Using Stories in the Organization
• Story-telling circles
 formed by groups having a certain degree of
coherence and identity
• Methods for eliciting anecdotes:
• Dit spinning (fish tales or legend) - —represents
human tendencies to escalate or better the
stories shared previously
• Alternative histories - are fictional anecdotes
which could have different turning points, for
example on a particular project’s outcome.
Techniques
• Shifting character or context - are fictional
anecdotes where the characters may be shifted
to study the new perspective of the story.
• Indirect stories -- allow disclosing the story with
respect to fictional characters, so that any
character similarities with the real-life character
are considered to be pure coincidence.
• Metaphor -- provides a common reference for
the group to a commonly known story, cartoon,
or movie
Knowledge Representation
through the use of Concept Maps
• based on interview sessions between a knowledge
• engineer and the domain expert, with the goal of jointly
constructing an expertise model.
• Although computers may understand the resulting
expertise models, these models may
• not directly meet the objective of capturing and
preserving the expert’s knowledge so
• it can be transferred to others, or in other words, so
others can learn from it.
• Based on Ausubel’s learning psychology theory
• Concepts, enclosed in circles or boxes. are perceived
regularities in events or objects designated by a label
• Two concepts connected by a linking word to form a
Additional methods
•
•
•
•
•
•
•
Interviews
Video recording
Observation
Codification – writing down what one knows
Group discussion
Collaborative software tools such as wikipedia
Etc
Concept Map about Concept
Maps
• Concept maps as a knowledge-modeling tool.
• Concept maps, developed by Novak (Novak, 1998)
aim to represent knowledge through concepts enclosed
in circles or boxes of some types, which are related via
connecting lines or propositions.
• Concepts are perceived regularities in events or objects
that are designated by a label
• Simple concept map contains just two concepts
connected by a linking word to form a single proposition,
also called a semantic unit or unit of meaning.
• “Concept maps represent organized knowledge.”
Concept Map about
Concept Maps
A Concept Map Segment from
Nuclear Cardiology Domain
Construction of Concept Maps
• Hierarchical
 the vertical axis expresses a hierarchical framework
for organizing the concepts.
 More general, inclusive concepts are found at the top
of the map with progressively more specific, less
inclusive concepts arranged below them.
 Emphasize the most general concepts by linking them
to supporting ideas with propositions.
 E.g Animal-> domestic -> cow
• Semantic networks,
 also called associative networks, are typically
represented as a directed graph connecting the
nodes (representing concepts) to show a relationship
or association between them.
 useful in describing, for example, traffic flow in that
the connections between concepts indicate direction,
but directed graphs do not connect concepts through
propositions.
 Does not indicate generalization from specific to
general
Knowledge Capture Systems:
CmapTools
• To capture and formalize knowledge resulting in context rich
knowledge representation models to be viewed and shared
through the Internet
• Alleviates navigation problem with concept maps
• Serve as the browsing interface to a domain of knowledge
• Icons below the concept nodes provide access to auxiliary
information
• Linked media resources and concept maps can be located
anywhere on the Internet
• Browser provides a window showing the hierarchical
ordering of maps
Segment from Nuclear
Cardiology using CmapTools
Explanation Subsystem
using CmapTools
Knowledge representation
through context-based reasoning
• Tactical knowledge
 human ability that enables domain experts to assess
the situation at hand (therefore short-term)
 myriad of inputs, select a plan that best fits current
situation, and executing plan
 recognize and treat only the salient features of the
situation
 gain a small, but important portion of the available
inputs for general knowledge
Knowledge representation
through CxBR
• Context - set of actions and procedures that
properly address the current situation
• As mission evolves, transition to other context
may be required to address the new situation
 For example knowledge sharing between supervisor
and subordinate and between subordinate
 In hospital and academic institutions
• What is likely to happen in a context is limited
by the context itself
Knowledge representation
through CxBR (context based reasoning)
• Mission Context - defines the scope of the mission, its
goals, the plan, and the constraints imposed -- e.g drive to
work (high way and local road)
• Main Context - contains functions, rules and a list of
compatible subsequent main Contexts (e.g high way
driving)
• Sub-Contexts - abstractions of functions performed by the
Main Context which may be too complex for one function
(e.g traffic light action)
• Only one action (e.g red light) occur but changed by events
from the environment. The agent knows the events
Knowledge representation
through CxBR
Knowledge Capture Systems
based on CxBR
• Context-based Intelligent Tactical Knowledge
Acquisition (CITKA)
 uses its own knowledge base to compose a set of
intelligent queries to elicit the tactical knowledge of
the expert
 composes questions and presents them to the expert
 result is a nearly complete context base can be used
to control someone performing the mission of interest
in a typical environment
Knowledge Capture Systems
based on CxBR
• CITKA consists of four modules of independent
subsystems:




Knowledge engineering database back-end (KEDB)
Knowledge engineering interface (KEI)
Query rule-base back-end (QRB)
Subject matter expert interface (SMEI)
Barriers to the use of
knowledge capture systems
• Barriers to the deployment of knowledge capture
systems from two perspectives:
 the knowledge engineer who seeks to build such
systems
 the subject matter expert, who would interact with an
automated knowledge capture system to preserve his
knowledge
Barriers to the use of
knowledge capture systems
• Knowledge Engineer requires developing some
idea of the nature and structure of the
knowledge very early in the process
 must attempt to become versed in the subject matter,
or the nature of knowledge
• An automated system for knowledge capture,
without a-priori knowledge of the nature, is
essentially not possible
Barriers to the use of
knowledge capture systems
• From the point-of-view of the expert:
 need to take the initiative of learning how to interact
with the system
 some people may be resistant to trying new things
 can be overcome, with adequate training and the
utilization of user-friendly interfaces
Using learning by observation
capture knowledge
• Research on how humans and animals learn
through observation has promise for
development of knowledge based systems
• Use of learning through observation to automate
the knowledge acquisition task
• Learning by observation shows promise as a
technique for automatic capture of expert’s
knowledge, and enable computers to
automatically “learn”
Conclusions
In this chapter we:
• Described knowledge capture systems
 design considerations
 specific types of such systems
• Discussed different methodologies and intelligent
technologies used to capture knowledge
 concept maps as a knowledge-modeling tool
 context-based reasoning to simulate human
behavior
• Explained how stories are used in organizational
settings to support knowledge capture