Published by the IEEE Computer Society
|The Dagstuhl Seminar|
|In This Issue|
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• Lean management structures rely on decision making at all organizational levels.
• Short product development schedules require the tight integration and management of knowledge of different departments.
• Fast-changing markets require up-to-date views of customer behavior and strategic activities of competitors.
• Organizations must set clearly specified objectives for developing knowledge management solutions. Later, they can use these objectives to evaluate a solution's success. Objectives might vary substantially from company to company and might be split into the objectives of the enterprise and of the individuals.
• Information technology is a crucial success factor, but not the most important one. Unless organizational and human resource management aspects are also addressed, an information technology solution will not be successful.
• Knowledge management applications must be embedded in organizational structures that enable organizational learning.
• Knowledge management often must be embedded in processes, which must be reengineered to accommodate knowledge management.
• Successful knowledge management applications rely on the involvement of all respective stakeholders. Setting up a successful knowledge management project requires explicit, strong support from (top-level) management.
• In "Knowledge Management: Problems, Promises, Realities, and Challenges," Gerhard Fischer and Jonathan Ostwald describe an application for urban planning and decision making. Their Envisionment and Discovery Collaboratory approach considers knowledge as an artifact that must be designed and constructed in a cooperative environment that supports and links all stakeholders of an envisioned knowledge management application.
• In "Better Knowledge Management through Knowledge Engineering," Alun Preece, Alan Flett, Derek Sleeman, David Curry, Nigel Meany, and Phil Perry discuss the development of a knowledge management system in a drilling firm. They argue that knowledge management applications should profit from knowledge-engineering methods and tools.
• In "How Knowledge Reuse Informs Effective System Design and Implementation," Daniel O'Leary analyzes knowledge management data from a consulting and professional services firm. His analysis indicates that the different service domains of such companies reuse knowledge in significantly different ways.
• In "Knowledge Processes and Ontologies," Steffen Staab, Rudi Studer, Hans-Peter Schnurr, and York Sure discuss a system for analyzing chemical industry mergers and acquisitions. They show how an ontology-based approach to knowledge management that is embedded into well-defined knowledge (meta) processes opens the way to the management of knowledge contents instead of knowledge containers.
• In "Facilitating the Legislation Process Using a Shared Conceptual Model," Tom van Engers and Erwin Glassée describe a knowledge management application in the Netherlands' Tax and Customs Administration. This application demonstrates how knowledge management helps create a corporate knowledge corpus that makes knowledge traceable and certifiable.
Daniel E. O'Leary is a professor at the Marshall School of Business of the University of Southern California. He received his BS from Bowling Green State University, his master's from the University of Michigan, and his PhD from Case Western Reserve University. He is the editor in chief of IEEE Intelligent Systems and is a member of the AAAI, ACM, and IEEE. Contact him at USC, 3660 Trousdale Parkway, Los Angeles, CA 90089-1421; email@example.com.
Rudi Studer is a professor in applied computer science at the University of Karlsruhe. His research interests include knowledge management, intelligent Web applications, knowledge engineering, and knowledge discovery. He received his doctorate in mathematics and computer science and a Habilitation in computer science from the University of Stuttgart. He is a member of the IEEE, ACM, AAAI, and German Informatics Society (GI). Contact him at the Univ. of Karlsruhe, Institute AIFB, D-76128 Karlsruhe, Germany; firstname.lastname@example.org.