JUCS - Journal of Universal Computer Science 11(4): 452-472, doi: 10.3217/jucs-011-04-0452
KMDL - Capturing, Analysing and Improving Knowledge-Intensive Business Processes
expand article infoNorbert Gronau, Claudia Müller, Roman Korf
‡ University of Potsdam, Potsdam, Germany
Open Access
Existing approaches in the area of knowledge-intensive processes focus on integrated knowledge and process management systems, the support of processes with KM systems, or the analysis of knowledge-intensive activities. For capturing knowledge-intensive business processes well known and established methods do not meet the requirements of a comprehensive and integrated approach of process-oriented knowledge management. These approaches are not able to visualise the decisions, actions and measures which are causing the sequence of the processes in an adequate manner. Parallel to conventional processes knowledge-intensive processes exist. These processes are based on conversions of knowledge within these processes. To fill these gaps in modelling knowledge-intensive business processes the Knowledge Modelling and Description Language (KMDL) got developed. The KMDL is able to represent the development, use, offer and demand of knowledge along business processes. Further it is possible to show the existing knowledge conversions which take place additionally to the normal business processes. The KMDL can be used to formalise knowledge-intensive processes with a focus on certain knowledge-specific characteristics and to identify process improvements in these processes. The KMDL modelling tool K-Modeler is introduced for a computer-aided modelling and analysing. The technical framework and the most important functionalities to support the analysis of the captured processes are introduced in the following contribution.
Process-oriented Knowledge Management, knowledge-intensive Business Processes, Knowledge Modeling Description Language, K-Modeler