Integrating Process Learning and Process Evolution - A Semantics Based Approach

Companies are developing a growing interest in aligning their information systems in a process-oriented way. However, current processaware information systems (PAIS) fail to meet process flexibility requirements, which reduces the applicability of such systems. To overcome this limitation PAIS should capture the whole process life cycle and all kinds of changes in an integrated way. In this paper we present such a holistic approach providing full process life cycle support by combining the ADEPT framework for dynamic process changes with the concepts and methods provided by case-based reasoning (CBR) technology. This allows expressing the semantics of process changes, their memorization and their reuse to perform similar changes in the future. If the same or similar process instance changes occur frequently, potential process type changes are suggested to the process engineer. The process engineer can
then perform a schema evolution and migrate running instances to the new schema version by using the ADEPT framework. Finally, the casebase related to the old schema version is migrated as well.