IT-BASED PURPOSE-DRIVEN KNOWLEDGE VISUALIZATION

Wladimir Bodrow and Vladimir Magalashvili

Department of Business Informatics, University of Applied Sciences Berlin, Treskowallee 8, 10318 Berlin, Germany

Keywords: Knowledge visualization, knowledge transfer, knowledge management.

Abstract: Knowledge visualization is currently under investigation from different points of view especially because of

its importance for Artificial Intelligence, Knowledge Management, Business Intelligence etc. The concepts

and technology of knowledge visualization in the presented research are considered from a purpose

perspective which focuses on the interdependencies between different knowledge elements. This way the

influence of these elements on each other in every particular situation can be visualized. This is crucial e.g.

for decision making.

1 KNOWLEDGE TRANSFER AS

THE ESSENTIAL ACTIVITY IN

KNOWLEDGE MANAGEMENT

PROCESSES

Looking back onto more than ten years of

knowledge management history we detected that

there is still no universal definition of knowledge

management. Some valuable attempts to define

knowledge management were made by Probst

(Probst et al., 1997), Davenport and Prusak

(Davenport/Prusak, 1998), Nonaka and Takeuchi

(Nonaka/Takeuchi, 1995), Maier (Maier, 2004) etc.

Most of today’s accepted definitions describe

knowledge management as creation,

communication, and application of knowledge. The

main goal of knowledge management is therefore to

improve these processes. Outgoing from different

perspectives and different aims correspondently the

descriptions of the activities in the knowledge

management process vary significantly. But almost

all of them (Bodrow/Fuchs-Kittowski, 2004, Maier,

2004) emphasize knowledge transfer - which is also

called sharing, diffusion, exchange, dissemination,

or distribution, together with knowledge application

as one of the most important activities in the

knowledge management process. Below we will use

the term transfer synonymously for sharing and

exchanging of knowledge as well as for diffusion,

dissemination and distribution of knowledge,

knowing that sharing and exchange refer to bi-

directional processes in opposition to dissemination,

diffusion and distribution which represent the uni-

directional (knowledge) flow. In respect to the

presented research this difference is useless

therefore only the transfer term will be applied.

The efficient transfer of knowledge has proven to

be a difficult task. In this context the adequate

visualization of knowledge can significantly

improve its transfer. Therefore in the following

analysis we will concentrate on this particular aspect

of the knowledge transfer.

2 WHY KNOWLEDGE

VISUALIZATION?

A well-known saying, that a picture is worth 1000

words, leads us to the suggestion that the

visualization of knowledge can increase the

effectiveness of its representation, understanding

and consequently of knowledge transfer.

Visualization can be considered as a way of

internalization (Nonaka/Takeuchi, 1995) of

knowledge (transformation from explicit to tacit

knowledge). But what exactly do we mean by

knowledge visualization? How does it differ from

visualization of information or data? Knowledge

visualization as opposed to information visualization

is a rather new field within knowledge management

research. It has received more attention recently due

to the business’s interests. There are already some

attempts to define knowledge visualization. Two

examples of such definitions are presented below.

194

Bodrow W. and Magalashvili V. (2007).

IT-BASED PURPOSE-DRIVEN KNOWLEDGE VISUALIZATION.

In Proceedings of the Second International Conference on Software and Data Technologies - PL/DPS/KE/WsMUSE, pages 194-197

DOI: 10.5220/0001339001940197

 SciTePress

3 KNOWLEDGE

VISUALIZATION TODAY

Following Drosdol (Drosdol/Frank, 2005)

knowledge visualization refers to “the result of

transformation from information to knowledge,

representation of connections and links, designing

the space between information elements,

development of meaning, creating meaningful

structures fitting the contents, helping to generate

new knowledge which can be used by people, staff,

leaders, decision-makers”.

Burkhard (Burkhard/Maier, 2004, Burkhard,

2005, Eppler/Burkhard, 2004) defines knowledge

visualization as “the use of visual representations to

improve the transfer and creation of knowledge

between at least two persons”. Moreover he

describes the difference between knowledge and

information visualization. The latter is not trivially

derivable from the presented definition. Information

visualization also uses “visual representations to

improve the transfer of knowledge”, even if its

primary goal is to retrieve the information.

According to Burkhard’s definition it can be

considered as knowledge visualization. The recipient

(depending on their capabilities) can obtain or

perhaps create new knowledge only by getting the

visual information. There are many Software-tools

that visualize a huge amount of data and

information. Experience gathered in this field is very

helpful i.e. for development of decision support

systems. Obviously the presented definition is too

general to be accepted as a definition for knowledge

visualization.

Our approach compared to other definitions is

not knowledge element-driven, but purpose-driven.

It is based on an appropriate application of the

different interrelations between the knowledge

elements according to the selected purpose. We

consider the knowledge element oriented approach

as very similar to information or data visualization

where the different declared attributes of the

particular object can be visualized using graphics

and other media. Alternatively we follow the idea,

that the most important aspect in visualizing

knowledge (especially!) is the multi-valence of

explanations for the interdependencies between

knowledge elements.

4 HOW DO WE

DEFINE KNOWLEDGE

VISUALIZATION?

How can we define knowledge visualization from a

knowledge management perspective (not from a

view of cognitive psychology, pedagogy or graphic

design)? Our aim is not to define a visualizing

technique (like sketch, diagram, image etc.), but a

general proper way for the representation of

knowledge using visualization techniques.

If somebody tries to illustrate a solution of a

complex (for example business) problem, they do

not only visualize single elements of a transferred

concept based on its attributes, but also the

connections and/or interdependencies of these

elements. However it is usually not enough for the

recipient to understand the logic of the concept (and

to accept the proposed solution). What the recipient

needs is an explanation of those dependencies in

respect to the task or problem to be solved. Why are

the selected elements connected to each other in the

considered case or in general? How do these visual

dependencies help understand the knowledge to be

transferred? Why does the knowledge have to be

visualized based on a selected concept (motivation)?

How is this visualization going to be helpful for the

solution investigated and for other applications?

Which role do the skills and preferences of both

partners play in the particular knowledge transfer

and its visualization?

From our point of view knowledge visualization

has to answer these questions to be classified as

such. Without explaining the meaning and purpose

of the connections between the different visual

elements, the visualization loses its value. It reduces

to something like data or information visualization –

visual representation of abstract data. (Card et al.,

1999, Chen, 1999, Chen/Geroimenko, 2003). For

instance according Card “information visualization

is the use of computer-supported, interactive, visual

representation of abstract data to amplify cognition”

(Card et al., 1999).

Summarizing the features and perspectives

mentioned above the following definition of

knowledge visualization can be derived:

Definition:

Knowledge visualization is a set of graphical entities

used to transfer knowledge from an expert to a

person (or group of persons), which clarifies its

complexity and explains the meaning and the

purpose of the relevant interdependencies.

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195

Firstly, according to the definition above the sender

of knowledge can be both: human or artefact,

whereas the recipient from today’s perspective can

be a single person or a group of persons.

Secondly, the visualization should represent a task

or problem to be solved (e.g. business workflow

process, structure of a business unit with its

responsibilities etc.). This way it provides the

answer for the question why the knowledge has to be

transferred.

In this research we only consider the dependencies

of the first order in the visualized structure (see

Figure 1). That means we only analyze the

connections (uni- or bidirectional) between different

but single elements and not between groups of

elements or indirect relations (n-way dependencies).

The connections can be considered from two

perspectives:

Why this connection? – What is the purpose of this

connection? Why does this connection have to be

used? Which problems can be solved based on it?

Which particular dependency or influence is used in

this connection? – It should explain the connection

between two selected knowledge elements.

Accordingly the dependency can be interpreted as a

specialization for the more general or strategic

formulated purpose of the single connection between

two knowledge elements.

Figure 1: First order and second order dependencies

between elements.

According to the previous discussion we can define

knowledge visualization formally as

KnowVis = F (E, D, P) where

F is a certain function of

E – a set of knowledge elements (

different visual

features as tables, charts, nodes of trees, circles etc.

)

D – a set of dependencies/influences between

knowledge elements

P – a purpose(s) of interdependencies.

From another perspective each dependency can be

defined as

D = f (e1, e2, s12, s21, p12, p21)

Where e1, e2 are two knowledge elements from E

p12, p21 represent the corresponding purposes s12,

s21 are the strengths of the influence of e1 on e2 and

vice versa.

One should only concentrate on the most

important dependencies between knowledge

elements in order to avoid extreme complexity in the

visualized structure. Therefore it sounds reasonably

that the connections have such attributes as the

“strength” of interdependency.

Our concept has something in common with the

idea of Novak’s concept maps (Novak/Gowin,

1984). Novak defines concept maps as tools for

organizing and representing knowledge. They

include concepts (enclosed in circles or boxes), and

relationships between concepts or propositions.

These relations are indicated by a connecting line

and a linking word (often a verb).

But the key difference from Novak’s to our

concept is that each relation in knowledge

visualization is provided by the explanation of its

purpose. How does this explanation support the

whole idea of knowledge transfer?

The choice of visualization technique certainly

depends on the type of knowledge transferred and on

the recipient’s capabilities.

As just mentioned, knowledge visualization

should clarify the purpose of the connections

between visual entities. This does not mean that the

recipient receives only one “right application”. The

given explanations will contain a description of how

the sender would apply this knowledge. Those

application suggestions will help the recipient to

utilize the best practice by creating his own

analogies and associations during his individual

decision making. The way in which the obtained

knowledge can be applied depends on the

effectiveness of the visualization (choice of visual

self-describing features, clear dependencies, etc.)

and the intellectual (abstract thinking, logical

conclusions, experience, etc.) capabilities of the

recipient.

Figure 2: The purpose-driven knowledge visualization

metaphor.

An example for purpose-driven knowledge

visualizations is presented in Figure 2. The

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196

explanations menus for all connections as shown

above can overload the graphic. Therefore they

should rather be implemented as context sensitive

menu-boxes appearing after a mouse click on the

connection to be clarified.

Which advantages can be expected from such

visualizations?

Firstly, it is easier for the recipient to understand

the knowledge transferred from the sender.

Secondly, this explanation of the dependencies

and purposes of the relations will simplify the

process of logical and analogical reasoning by the

recipient.

5 IMPLEMENTATION

The concept described in this report is currently in

realization. The implemented prototype is being

investigated in the context of various applications

where the knowledge transfer plays an essential role

(e.g. different knowledge management systems, e-

Learning tools etc.) Its important features are listed

below:

 Editor for knowledge elements and n-

dimensional connections between them.

 Flexible edition of the facets/attributes of these

connections to define the interdependencies

between elements.

 Context sensitive visualization of

interdependencies within the particular case

analyses.

 Activation of the context sensitive pull-down

menu with different interdependencies between

selected knowledge elements

 Possibilities for generalization as well as for

specialization of the solution based on the same

concept.

6 CONCLUSIONS

The approach of knowledge visualization described

in this paper provides a new basis for knowledge

transfer. In contrast to other definitions, in this

research knowledge visualization is investigated

from the purpose perspective. Following presented

purpose-driven approach it is important to extend the

usual map of relations between different knowledge

elements with explanation of their

interdependencies. The implementation of this

approach allows context sensitive visualizations of

these interdependencies in respect to the purposes of

knowledge transfer or tasks under investigation. The

clarification of the purposes integrated into the

visualization of interdependencies between

knowledge elements significantly improves the

recipient’s understanding and acceptance of the

knowledge transferred.

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