The Quantitative Aspects of Process Mining workshop provides a forum that welcomes process mining contributions, specifically including quantitative process mining experiments. This purpose is multi-faceted: on the one hand is the relevance of the analyses’ results in itself, while on the other hand is the significance of methodological and technical best practices. Over the past decades, there have been many developments of new techniques in the field of process mining, ranging from process discovery algorithms, conformance checking metrics, to predictive process monitoring models. As the field matures, there is a clear need to compare and evaluate different approaches, and examine how they react to certain phenomena, like noise or exceptional behaviour. Despite their relevance, setting up large scale experiments is not straightforward, and the efforts to do so have been limited. The challenges faced by researchers are technical, i.e., which tooling can support large quantitative experiments in a feasible manner, as well as methodological, i.e., what are the best practices with respect to experimental design and statistical rigour.

The workshop Quantitative Aspects of Process Mining (QAPM 2022) is a satellite event of the 34th International Conference on Advanced Information Systems Engineering (CAiSE 2022). The workshop aims to attract papers related to process mining, and, in particular quantitative aspects of these techniques. Process mining techniques translate behavioral descriptions (event logs, transition systems, etc.) into "higher level" process models (e.g., various classes of Petri nets, BPMN, or UML activity diagrams). Additionally various techniques exist for conformance checking, process enhancement, etc.
QAPM 2022 solicits papers related to all types of process mining technology, specifically combined with a solid quantitative evaluation. However, the scope is not limited to this. The program committee invites submission of full papers (up to 12 pages) and of short papers (up to 6 pages). Papers should be submitted as pdf-files using the Springer LNBIP-format. Papers need to be submitted via Easychair.