In this paper, we examine what roles state of the art knowledge management technologies can play in the cooperation between cluster members. We suggest that glossaries reconsidered in the light of other semantic data models and our experience with semantic web applications provide favourable conditions for the precise formulation and sharing of enterprise information assets.

In the everyday use of the term, a knowledge management (or representation) technology is used to express one of the standards developed for the formalization of knowledge at around the millennium; examples include RDF, OWL and Topic Maps. However, we extend the notion of knowledge management to cover “traditional” methods, e.g. glossaries, thesauri and encyclopaedias. The technology presented here enables its users to organize concepts in a psychologically justifiable manner. Our data model incorporates the strong points of various knowledge representation techniques, but is enhanced with features that target usability. All these aspects make our technology suitable for the effective codification of tacit enterprise knowledge.

Our aim is to help companies capture their knowledge and make effective use of information, therefore we present a system designed for the optimal interpretation of human knowledge. We claim that such systems should center around concepts (subject, topics) instead of documents, which is the traditional approach.

However, several questions arise: Is the interest in the applications of knowledge management sincere? Are cluster members willing to share their experience, and if so, what are the areas which, when disclosed, do not endanger the company’s competitive advantage? We show that knowledge management can face various obstacles (both human and technological) even within a single organization. Skeptics say that technology makes up only 10% of knowledge management; 20% is the impact of processes, and an outstanding 70% depends on the human factor (Marc Baker, 1998). We believe that revealing the factors that help or hinder knowledge sharing will shed a new light on the reason for the existence of such technologies, and furthermore, it may be a genuine addition to the discussion of problems in the cooperation between cluster members.