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

Process 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 (XES)
is the most widely adopted. In XES, 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 (OCEL) standard has been
proposed recently. However, the crucial problem of extracting OCEL logs
from external sources is still largely unexplored. In this paper, we try
to fill this gap by leveraging the Virtual Knowledge Graph (VKG) approach to access data in relational databases. We have implemented this
approach in the OnProm system, extending it to support both XES and
OCEL standards. We have carried out an experiment with OnProm over
the Dolibarr system. The evaluation results confirm that OnProm can
effectively extract OCEL logs and the performance is scalable.