Guided Interaction Exploration and Performance Analysis in Artifact-Centric Process Models

Abstract

Artifact-centric process models aim to describe complex processes as a collection of interacting artifacts. Recent development in process mining allow for the discovery of such models. However, the focus is often on the representation of the individual artifacts rather than their interactions. Based on event data, composite state machines representing artifact-centric processes can be discovered automatically. Moreover, the study provides ways of visualising and quantifying interactions among different artifacts. For example, strongly correlated behaviours in different artifacts can be highlighted. Interesting correlations can be subsequently analysed to identify potential causes of process performance issues. The study provides a strategy to explore the interactions and performance differences in this context. The approach has been fully implemented as a ProM plug-in; the CSM Miner provides an interactive artifact-centric process discovery tool focussing on interactions. The approach has been evaluated using real life data, to show that the guided exploration of artifact interactions can successfully identify process performance issues.

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