Knowledge Management and Event Processing

Data is acquired from different sources (e.g. automation devices, IT systems, web services). Usually, this data is stored and managed in relational databases, preferably with its surrounding context information.

Traditionally, knowledge management (KM) is employed as an offline activity to determine new knowledge or update existing knowledge using well established techniques like data mining and online analytical processing (OLAP). Further, the knowledge is codified as rules, ontologies and so on. This new knowledge, on number of occasions, is utilized to redesign and optimize relevant processes (e.g. business and manufacturing processes). On contrary, emerging online technologies like (complex) event processing (EP) can be engaged to monitor and control the aforementioned processes in (near) real-time. Predominately, EP is applied in the financial domain for various purposes like algorithmic trading, credit card fraud detection, and intrusion detection.

Both KM and EP can benefit from a more seamless integration or interaction. KM can be employed to extract knowledge, which can be used to enhance the execution of EP. Similarly, KM can benefit from EP. For instance, the triggered / identified events can be engaged to improve the KM process. Overall, this direction of interaction needs to be explored by the research community.

Hence, the workshop aims at fostering the integration and interaction between KM and EP. In this workshop, we are interested in exchanging ideas, experiences, and industry / research results about


Contact Details:

Prof. Dr.-Ing. Manfred Grauer

Information Systems Institute

University of Siegen

57068 Siegen, Germany