Model-Driven Event Query Generation for Business Process Monitoring

Abstract

Abstract. While executing business processes, a variety of events is produced that is valuable for getting insights about the process execution. Specifically, these events can be processed by Complex Event Processing (CEP) engines to deliver a base for business process monitoring. Mobile, flexible, and distributed business processes challenge existing process monitoring techniques, especially if process execution is partially done manually. Thus, it is not trivial to decide where the required business process execution information can be found, how this information can be extracted, and to which point in the process it belongs to. Tackling these challenges, we present a model-driven approach to support the automated creation of CEP queries for process monitoring. For this purpose, we decompose a process model that includes monitoring information into its structural components. Those are transformed to CEP queries to monitor business process execution based on events. For illustration, we show an implementation for Business Process Model and Notation (BPMN) and describe possible applications.

Predictive Task Monitoring for Business Processes

“…Third, a Complex Event Processing (CEP) system [10] is responsible for normalising events from different event sources, aggregating them to meaningful business events, and correlating them to task instances (RQ3). It must be capable of computing execution information against the specification set in the process model, too (RQ4), e.g., [3]. Fourth, a deviation prediction system aims at evaluating whether the task execution evolves as expected or deviates, and at informing proper participants (RQ5).…”