SEKE 2012 Proceedings - Knowledge Systems Institute

it is often important t o know why certain decisions have
been made [6].
A. Codification of Knowledge
Explicit knowledge is represented i n a way that is easil y
transferred from one person to another. Data files, reports,
and other physical representations of knowledge are
explicit. Taci t knowledge is the knowledge that people
maintain inside themselves and is harder to formalize. It is
inferred through the behaviors of indivi duals. Access to
tacit knowledge is typ ically obtained through personal
contact and trust.
Nonaka describes how organizational a nd individual
knowledge are created through continuous dialogue among
individuals involving their tacit and explicit knowledge [7].
Organizational knowledge is created in a continual cycle
through: socialization, intern alization, externalization, and
combination. These four modes of knowledge creation are
described in Table 1.
TABLE I.
MODES OF KNOWLEDGE CREATION
To Tacit
To Explicit
From Tacit Socialization Externalization
From Explicit Internalization Combination
With socialization, the key to gaining tacit knowledge is
some form of shared experience through interactions with
individuals. The tacit-to-tacit socialization mode is initiated
when a group of people forms and int eraction begins.
Externalization encompasses the conversi on of tacit to
explicit knowledge and is trigg ered through the
documentation of shared tacit knowl edge and new
knowledge. This explicit know ledge is com bined with
existing data and available knowledge in the combination
mode, forming new concepts and concrete knowledge.
Internalization involves explicit to tacit knowledge; learning
occurs when participants translate explicit knowledge
gained into forms of individual tacit knowledge [7].
The combination mode of knowledge creation can b e
demonstrated through the engineering of new knowledge
from existing knowledge s ources. Lee et al. described the
use of knowledge engineering to visualize complexity in the
software engineering domain. This experience showed the
value of knowledge engineered from legacy application
metadata [8]. The goal of determining the risk as sociated
with each application was reali zed and successfully applied
to modernization strategy planning, supporting the goal of
reducing complexity in domains with high business risk.
Knowledge engineering of application meta-data into
estimates of resource impact and potential risks and costs is
applicable in a wide array of problem domains [8].
B. Personalization of Knowledge
Informal discussions represent a very important form of
knowledge sharing where cross-fertilization of knowledge
occurs. Finding a way to capture the knowledge exchange
in these informal communications is challenging. Informal
communication in communities can be promoted through
the use of social networks and expert lists. The willingness
of each person to participate is critical to success [5]. By
integrating a co mmunity-based environment with a
traditional knowledge repository approach, both tacit and
explicit knowledge sharing is encouraged and supported.
Communities of practice, informal networks of
individuals with shared interests, objectives, and social
networks highlight the important link between social capital
and knowledge resources in effecti ve knowledge
management. A community of practice refers to the process
of social learning that occurs and the shared practices that
emerge when people with common goals interact. A similar
concept is a community of interest, a group of people who
share a common interest. Communities reflect the “interests
and/or expertise of people that are free t o join one or more
communities for: receiving help on specific fields;
recommending or publishing a ny piece of information;
informally discussing on th emes; rating or inserting
comments on elements; and so on” [9]. A community
workspace may contain formal documents and informal
comments. A software project may be tied to se veral
communities. By und erstanding how these communities
can successfully maintain and s hare knowledge, the
potential exists to greatly e nhance sharing of knowle dge
[10]. Marks et. al. argue that th e stronger an individual
identifies with a group, the more apt that person is to share
information [11].
C. Knowledge Sharing Philosophy
Ezingeard et. al. discuss the importance of building a
knowledge sharing culture as a foundation. The knowledge
management sandcone in Fi g. 1 demonstrates this conce pt
[12] [13].
Figure 1. A depiction of the knowledge management sandcone concept
[12].
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