Introduction

During the past years a shift in the fundamental understanding of the aims of Computer Science, especially in AI, could be observed. While early research in AI aimed at replacing the human being with better tools, the prevalent current vision is nowadays to support him in his tasks. This shows up in the rise of research areas like communities of practice, knowledge management, web communities, and peer to peer. In particular the notion of collaborative work -and thus the need of its systematic analysis -becomes more and more important.

On the other hand, techniques for analyzing such structures have a long tradition within sociology. While in the beginnings, researchers in that area had to spent huge efforts in collecting data, they nowadays often come for free in the WWW. Popular examples are citation and coauthor graphs, friend of a friend etc.

Thus there exists an increasing interest of the social network analysis community in the web. The semantic web provides an additional aspect as it distinguishes between different kinds of relations, allowing for more complex analysis schemes.

Our aim is to bring the two communities together in order to learn from each other. We expect especially that the semantic web community can largely benefit from the long tradition present in social network analysis.

Besides analyzing social networks and cooperative structures within the (semantic) web, our second aim is to exploit the results for supporting and improving communities in their interaction. An important research topic is thus how to include network analysis tools in working environments such as knowledge management systems, peer to peer systems or knowledge portals.