Proceedings of the 12th European Conference on Knowledge ...

Andrea Kő, Péter Fehér and Krisztián Varga
Figure 3: Graphical representation <strong>of</strong> a knowledge network (Anklam, 2009)
Anklam (2009) a gives <strong>the</strong> following representational rules and interpretational framework to <strong>the</strong>
knowledge networks (or communities <strong>of</strong> practice) (Figure 3):
Each circle (node) indicates one participant <strong>of</strong> <strong>the</strong> knowledge network.
A participant can be one person or an organization ei<strong>the</strong>r.
There is a line drawn between two nodes, if <strong>the</strong>y have any kind <strong>of</strong> a connection (<strong>the</strong>y know eacho<strong>the</strong>r,
<strong>the</strong>y communicate, <strong>the</strong>y are partners, etc.).
The size <strong>of</strong> a node is directly proportional to <strong>the</strong> number <strong>of</strong> connections it has. So <strong>the</strong> size is a
quantitative measurement unit, it depends on <strong>the</strong> number <strong>of</strong> connections only.
The thickness <strong>of</strong> a connection line indicates <strong>the</strong> quality <strong>of</strong> <strong>the</strong> connection. The stronger <strong>the</strong>
connection is (frequent communication, long-term partnership), <strong>the</strong> thicker <strong>the</strong> line is.
1.2 ICT Solutions in Knowledge Management and Knowledge Networks
Different approaches to knowledge management can be distinguished on <strong>the</strong> basis <strong>of</strong> <strong>the</strong> investigated
research questions, as <strong>the</strong> learning focused approach; <strong>the</strong> process focused approach; <strong>the</strong> technology
focused approach; <strong>the</strong> environment focused (ecological) approach and <strong>the</strong> purpose focused approach
(Klimkó, 2001). Researchers who follow <strong>the</strong> technology focused approach consider knowledge as a
transferable object. For representatives <strong>of</strong> this <strong>the</strong>ory <strong>the</strong> ultimate task <strong>of</strong> knowledge management is
to ensure accessibility and/or transferability <strong>of</strong> knowledge with <strong>the</strong> help <strong>of</strong> an information technology
tools, <strong>the</strong>refore <strong>the</strong>se researchers <strong>of</strong>ten come from <strong>the</strong> field <strong>of</strong> artificial intelligence.
There are several unanswered questions about <strong>the</strong> role <strong>of</strong> ICT played in <strong>the</strong> area <strong>of</strong> <strong>the</strong> management
<strong>of</strong> <strong>the</strong> organizational knowledge. Zack divides <strong>the</strong>se problems into four bigger categories (Zack 1999):
Uncertainty: being not enough knowledge available
Complexity: being too much knowledge available, which is hard to manage
Ambiguity: <strong>the</strong>re is not available any conceptual framework accepted uniformly for <strong>the</strong>
interpretation <strong>of</strong> knowledge
There are too many conceptual frameworks for <strong>the</strong> interpretation <strong>of</strong> framework.
The main role <strong>of</strong> ICT in knowledge management is to lower obstructive elements in knowledge
sharing and delivery radically. Knowledge elements can be accessed easier by electronic storage
capacity, and <strong>the</strong> development <strong>of</strong> <strong>the</strong> knowledge sharing process may become more effective
(Hendriks, 1999).
The information technology supports <strong>the</strong> organizations substantially in <strong>the</strong> treatment <strong>of</strong> problems
which are related to complexity e.g. with augmentation <strong>of</strong> information processing capacity. The ICT
still helps <strong>the</strong>m in treating <strong>the</strong> problems <strong>of</strong> uncertainty, because it provides localization and collection
<strong>of</strong> information and recognition <strong>of</strong> fields having not enough information available. For map, evaluate,
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