Enhancing Data-Awareness of Object-Centric Event Logs

Lecture notes in business information processing, pp. 18–30

Abstract

Abstract When multiple objects are involved in a process, there is an opportunity for processes to be discovered from different angles with new information that previously might not have been analyzed from a single object point of view. This does require that all the information of event/object attributes and their values are stored within logs including attributes that have a list of values or attributes with values that change over time. It also requires that attributes can unambiguously be linked to an object, an event or both. As such, object-centric event logs are an interesting development in process mining as they support the presence of multiple types of objects. First, this paper shows that the current object-centric event log formats do not support the aforementioned aspects to their full potential since the possibility to support dynamic object attributes (attributes with changing values) is not supported by existing formats. Next, this paper introduces a novel enriched object-centric event log format tackling the aforementioned issues alongside an algorithm that automatically translates XES logs to this Data-aware OCEL (DOCEL) format.

Authors 4

1. Alexandre Goossens corresponding

   KU Leuven

   Affiliation as printed

   Leuven Institute for Research on Information Systems (LIRIS), KU Leuven, Leuven, Belgium

2. Johannes De Smedt

   KU Leuven

   Affiliation as printed

   Leuven Institute for Research on Information Systems (LIRIS), KU Leuven, Leuven, Belgium

3. Jan Vanthienen

   KU Leuven

   Affiliation as printed

   Leuven Institute for Research on Information Systems (LIRIS), KU Leuven, Leuven, Belgium

4. Wil M. P. van der Aalst Aachen Process and Data Science Chair

   RWTH Aachen University

   Affiliation as printed

   Process and Data Science (PADS) Chair, RWTH Aachen University, Aachen, Germany