Conformance checking visualizations: development, evaluation, and demonstration of a taxonomy

Abstract Organizations use conformance checking, a sub-discipline of process mining, which compares process executions with predefined process models, to identify deviations in business processes. These capabilities make conformance checking highly relevant. To make its results accessible and tailored to specific tasks, effective visualizations are essential. Although the need for such visualizations has already been identified and acknowledged by researchers in process mining, so far, the development of these visualizations has been left to tool providers, leading to visualizations that are highly different and difficult to compare. A better understanding of these existing visualizations and their components would support research to gain deeper insights and assess them more closely. To address this gap and establish a foundation for future research, this paper provides an overview of the existing breadth of characteristics of conformance checking visualizations in the form of a taxonomy. It enables to describe and assess existing visualizations in a structured manner, achieving a detailed understanding, which was not possible before. It consists of six dimensions, which systematically highlight what information is displayed and how this is visualized across academic and commercial tools. We evaluate the taxonomy through expert interviews and demonstrate its applicability through four individual exemplary visualizations and an assessment of common visualizations across tools. Our research enhances the comprehension of visual analytics in process mining, particularly for conformance checking, and highlights promising future research avenues.