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Abstract

The Fraunhofer Competence Center Knowledge Management presents in this second edition its up-dated and extended research results an business-process oriented knowledge management, pro-active change management, KM strategy, knowledge structuring and KM audit, reviews the latest advancements in measuring intellectual capital and classifies more than 100 KM tools. Best Practices in KM are described by the Swiss Benchmarking Center TECTEM at University St. Gallen and in case studies from pricewinning companies like Aventis and Siemens as well as from Arthur D. Little, British Aerospate plc., Hewlett-Packard, IBM, Phonak and Roche. New survey results an KM from EFQM, OECD and an "The Future of Knowledge Management" are presented. The book concludes with an overview an research funded by the European Commission in order to make "KM Made in Europe" a reality.

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Abstract

This book explores the software design, social practices, and collaboration theory that would be needed to support group cognition - collective knowledge that is constructed by small groups online. Innovative uses of global and local networks of linked computers make new ways of collaborative working, learning, and acting possible. In "Group Cognition", Gerry Stahl explores the technological and social reconfigurations that are needed to achieve computer-supported collaborative knowledge building - group cognition that transcends the limits of individual cognition. Computers can provide active media for social group cognition where ideas grow through the interactions within groups of people; software functionality can manage group discourse that results in shared understandings, new meanings, and collaborative learning. Stahl offers software design prototypes, analyses empirical instances of collaboration, and elaborates a theory of collaboration that takes the group, rather than the individual, as the unit of analysis. Stahl's design studies concentrate on mechanisms to support group formation, multiple interpretive perspectives, and the negotiation of group knowledge in applications as varied as collaborative curriculum development by teachers, writing summaries by students, and designing space voyages by NASA engineers. His empirical analysis shows how, in small-group collaborations, the group constructs intersubjective knowledge that emerges from and appears in the discourse itself. This discovery of group meaning becomes the springboard for Stahl's outline of a social theory of collaborative knowing. Stahl also discusses such related issues as the distinction between meaning making at the group level and interpretation at the individual level, appropriate research methodology, philosophical directions for group cognition theory, and suggestions for further empirical work.

Footnote

Rez. in: JASIST 59(2008) no.9, S.1531. (C. Caldeira): "Successful, real-world organizations employ groups to get work done. Despite the large number of years of collaborative models in work-group paradigm, it is a little surprising that there are very few books about the subject. Furthermore, most of those studies are mainly focused on work group performance management and work productivity. This text belongs to the advanced type, and is a valuable resource for graduate students in a wide range of courses and for a large spectrum of professionals interested in collaborative work. Due to its advanced level, some topics are relatively difficult to understand if the reader does not have some background in collaborative work and group cognition. Students who use this book will rapidly understand the most important topics of the science of collaboration for computer-supported cooperative work and computer-supported collaborative learning, and their relation to the business world of our days. The main concern and fundamental idea of this book is to set its focus primarily on work group, and not on individuals. Stahl's baseline is to use the science of collaboration for computer-supported cooperative work and computer-supported collaborative learning to conduct comparative studies on group interaction, group meaning, group cognition, group discourse, and thinking. The book is divided into three distinct parts. The first one is about the design of computer support for collaborative work and presents eight studies centered on software tools and their particular applications: The first three are AI applications for collaborative computer-supported cooperative work and computer-supported collaborative learning, the fourth and the fifth are about collaborative media, and the last ones are a combination of computational technology and collaborative functions. The second part is focused on the analysis on knowledge building in the collaborative work of small groups. It is developed with support on five essays published by Stahl from 2000 to 2004. In the first of those chapters, he describes a model of collaborative knowledge building and how to share knowledge production. The second criticizes some cooperative work and collaborative learning research methodologies that make the collaborative phenomena hard to perceive. The remaining chapters mostly provide mechanisms to understand in new and better ways collaborative processes. The third part contains the theoretical corpus of the book. Chapters 14 through 21 contain the most recent of Stahl's contributions to the theoretical foundations of computer-supported cooperative work and computer-supported collaborative learning. Chapters 16 to 18 provide much material about topics directly related to group cognition research and collaborative work in modern organizations. Finally, the last part of the book contains an exhaustive list of references that will be of great value to all interested in the multiple aspects and fields of cooperative work and collaborative learning."

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Abstract

Unternehmen sehen sich heutzutage regelmäßig der Herausforderung gegenübergestellt, aus umfangreichen Mengen an Dokumenten schnell relevante Informationen zu identifizieren. Dabei zeigt sich jedoch, dass Suchverfahren, die lediglich syntaktische Abgleiche von Informationsbedarfen mit potenziell relevanten Dokumenten durchführen, häufig nicht die an sie gestellten Erwartungen erfüllen. Viel versprechendes Potenzial bietet hier der Einsatz von Ontologien für das Information Retrieval. Beim ontologiebasierten Information Retrieval werden Ontologien eingesetzt, um Wissen in einer Form abzubilden, die durch Informationssysteme verarbeitet werden kann. Eine Berücksichtigung des so explizierten Wissens durch Suchalgorithmen führt dann zu einer optimierten Deckung von Informationsbedarfen. Jan Hermans stellt in seinem Buch ein adaptives Referenzmodell für die Entwicklung von ontologiebasierten Information Retrieval-Systemen vor. Zentrales Element seines Modells ist die einsatzkontextspezifische Adaption des Retrievalprozesses durch bewährte Techniken, die ausgewählte Aspekte des ontologiebasierten Information Retrievals bereits effektiv und effizient unterstützen. Die Anwendung des Referenzmodells wird anhand eines Fallbeispiels illustriert, bei dem ein Information Retrieval-System für die Suche nach Open Source-Komponenten entwickelt wird. Das Buch richtet sich gleichermaßen an Dozenten und Studierende der Wirtschaftsinformatik, Informatik und Betriebswirtschaftslehre sowie an Praktiker, die die Informationssuche im Unternehmen verbessern möchten. Jan Hermans, Jahrgang 1978, studierte Wirtschaftsinformatik an der Westfälischen Wilhelms-Universität in Münster. Seit 2003 war er als Wissenschaftlicher Mitarbeiter am European Research Center for Information Systems der WWU Münster tätig. Seine Forschungsschwerpunkte lagen in den Bereichen Wissensmanagement und Information Retrieval. Im Mai 2008 erfolgte seine Promotion zum Doktor der Wirtschaftswissenschaften.