| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 10321394 | Data & Knowledge Engineering | 2005 | 27 Pages |
Abstract
The indiGo project offers a solution for tackling resistance against and problems while executing process models: eParticipative Process Learning. Via moderated, web-based discussions, consensus about a process is created and process models are reviewed to achieve better understandability or other quality aspects. Furthermore, problems during the execution of a process are solved collaboratively and captured as lessons learned to facilitate upcoming process executions. In this paper, we present the method and technical infrastructure to support eParticipative Process Learning. To show that eParticipative Process Learning leads to improved and accepted process models, three case studies are described.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Björn Decker, Jörg Rech, Klaus-Dieter Althoff, Andreas Klotz, Edda Leopold, Angie Voss,
