Quantitative Aspects of Process Mining 2022

@CAiSE 2022 (06-10 June 2022)


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.



Topics


Topics of interest include, but are not limited to:

  • Automated discovery of process models
  • Conformance Analysis
  • Decision Mining for Processes
  • Multi-perspective process mining
  • Predictive Process Monitoring
  • Prescriptive Process Monitoring
  • Process Simulation
  • Online Process Mining
  • Scalable Process Mining
  • Experimental Set Up for process mining
  • Process Mining Methodologies
  • Tools for Reproducible Process Mining


Dates


  • Paper Submission Deadline: 8 March 2022
  • Paper Decision: 8 April 2022
  • Camera-Ready: 15 April 2022
  • Registration Deadline Workshop Authors: 22 April 2022
  • Workshop: 6-7 June 2022

Program Committee


Han van der Aa, University of Mannheim, Germnay
Abel Armas Cervantes, The University of Melbourne, Australia
Adriano Augusto, The University of Melbourne, Australia
Robin Bergenthum, FernUni Hagen, Germany
Seppe vanden Broucke, KU Leuven, Belgium
Josep Carmona, Polytechnic University of Catalonia, Germany (co-chair)
Jochen De Weerdt, KU Leuven, Belgium
Benoît Depaire, Hasselt University, Belgium
Marlon Dumas, University of Tartu, Estonia
Dirk Fahland, Eindhoven University of Technology, The Netherlands (co-chair)
Gert Janssenswillen, Hasselt University, Belgium (co-chair)
Wolfgang Kratsch, Research Center FIM / Fraunhofer FIT, Germany
Sander Leemans, Queensland University of Technology, Australia

Xixi Lu, Utrecht University, The Netherlands
Massimiliano de Leoni, Uniersity of Padoa, Italy
Henrik Leopold, Kühne Logistics University, Germany
Felix Mannhardt, Eindhoven University of Technology, The Netherlands
Niels Martin, Hasselt Univesristy, Belgium
Jan Mendling, Humboldt-Universität zu Berlin, Germany
Jorge Munoz-Gama, Pontificia Universidad Católica de Chile, Chile
Marco Pegoraro, RWTH Aachen University, Germany
Artem Polyvyanyy, The University of Melbourne, Australia
Jana-Rebecca Rehse, University of Mannheim, Germany
Arik Senderovich, York University, Canada
Matthias Weidlich, Humboldt-Universität zu Berlin, Germany
Jan-Martijn van der Werf, Utrecht University, The Netherlands
Sebastiaan J. van Zelst, Fraunhofer FIT / RWTH Aachen University, Germany (co-chair)



Program


TBA