Smolnik, Stefan; Nastansky, Ludwig: K-Discovery: Using Topic Maps to identify Distributed Knowledge Structures in Groupware-based Organizational Memories, in: Sprague, R. H. (Hrsg.): Proceedings of the 35th Hawaii International Conference on System Sciences, January 7-10, Big Island, Hawaii, CD-ROM, IEEE Computer Society Press, Los Alamitos CA, Washington, Brussels, Tokyo, Januar 2002, pp. 10.

THEMES: Smolnik, Stefan\...\Conference Pub... | Nastansky, Ludwig\...\Knowledge Mana...
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YEAR: 2002
 

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Summary
Many of today's organizations already have a strong integration of groupware systems in their IT-infrastructure. The shared databases of these groupware systems form organizational memories, which comprise the complete knowledge of an organization collected over the time of its existence. One key problem is how to find relevant knowledge or information in continuously growing and distributed organizational memories. The basic functionalities and mechanisms in groupware systems are not sufficient to support users in finding required knowledge or information. Topic maps provide strong paradigms and concepts for the semantic structuring of link networks and therefore, they are a considerable solution for organizing and navigating large and continuously growing organizational memories. The K-Discovery project suggests applying topic maps to groupware systems to address the mentioned challenges. Thus, the K-Discovery project introduces a conceptual framework, an architecture and an implementation approach to create knowledge structures by generating topic maps in organizational memories.