A Virtual Knowledge Graph Based Approach for Object-Centric Event Logs Extraction

Abstract

AbstractProcess mining is a family of techniques that support the analysis of operational processes based on event logs. Among the existing event log formats, the IEEE standard eXtensible Event Stream () is the most widely adopted. In , each event must be related to a single case object, which may lead to convergence and divergence problems. To solve such issues, object-centric approaches become promising, where objects are the central notion and one event may refer to multiple objects. In particular, the Object-Centric Event Logs () standard has been proposed recently. However, the crucial problem of extracting logs from external sources is still largely unexplored. In this paper, we try to fill this gap by leveraging the Virtual Knowledge Graph () approach to access data in relational databases. We have implemented this approach in the system, extending it to support both and standards. We have carried out an experiment with over the Dolibarr system. The evaluation results confirm that can effectively extract logs and the performance is scalable.