Aligning Object-Centric Event Logs with Data-Centric Conceptual Models.

Recently, the consideration of data aspects has seen a surge in interest both from the perspective of designing processes as from a model discovery perspective. However, it seems that both research domains (models for design and model discovery) use different conceptualisations of data/object-aware systems. In an ideal situation, when (designed) models are implemented, the resulting information systems are equipped with logging functionalities that allow the rediscovery of the models based on which the information systems were implemented. However, there is a lack of guidelines on how to set up logging. From a logging perspective, logging formats are unclear about the granularity of events: the logging may be done at the level of entire tasks or at the level of the operations on individual objects, or a single log may even contain a mix of events at different granularity levels. The lack of clarity in this matter complicates the correct interpretation of log information. The goal of this paper is therefore to investigate how the concepts of object-centric logging and those for data-aware process modelling may be better aligned. This will facilitate setting up proper logging at system implementation time, and facilitate the connection of discovered models to models-for-design. The investigation resulted in iDOCEM, a meta-model that aligns the DOCEL and the Merode meta-model. Comparing iDOCEM to different other logging meta-models demonstrates that the proposed meta-model is complete enough to capture (more than) existing logging formats.