Enhancing Data-Awareness of Object-Centric Event Logs

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.

NICE: The Native IoT-Centric Event Log Model for Process Mining

“…In the last years, several data formats have been adapted to IoT-enhanced event logs [9,20,28,22]. In this section, we present these new alternatives and compare them to our data format with respect to the requirements identified in [5].…”

“…Of these models, the least tailored one to IoT-enhanced logs is D-OCEL [9]. It is an extension of the OCEL [8] which introduces dynamic attributes, thereby solving one of the main issues faced by OCEL for IoT-enhanced event logs.…”