3.8 Proceedings Paper

Enhancing Data-Awareness of Object-Centric Event Logs

Journal

PROCESS MINING WORKSHOPS, ICPM 2022
Volume 468, Issue -, Pages 18-30

Publisher

SPRINGER INTERNATIONAL PUBLISHING AG
DOI: 10.1007/978-3-031-27815-0_2

Keywords

Object-centric event logs; Process mining; Decision mining

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When multiple objects are involved in a process, object-centric event logs are an interesting development in process mining as they support the presence of multiple types of objects. However, the current object-centric event log formats do not fully support dynamic object attributes. This paper introduces the Data-aware OCEL format, along with an algorithm that automatically translates XES logs to this format, addressing the issues present in the existing formats.
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.

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