Demo Track

Call for ICPM Demo Track Extended Abstracts

The ICPM 2022 Demo Track is intended to showcase innovative Process Mining (PM) tools and applications that may originate either from research initiatives or from industry. The Demo Track will provide an opportunity to present and discuss emerging technologies with researchers and practitioners in the PM field.

To be included in the Demo Track, tools will be evaluated on the basis of relevance to the PM community as well as on novelty and innovativeness. Previously demonstrated tools are also welcome if there is clear evidence of the value added to the previous version of the tool, such as new tool features and/or its adaptation and use for new practical applications. The tools will also be evaluated on their maturity, complexity and robustness, such as the list of features, supported use cases, number and types of users. 

In order for reviewers to assess the maturity and robustness, the tools need to be available for testing. If the tool requires a license, it must be provided to reviewers, at least for the review period. The procedure to obtain the license must not disclose the identity of the reviewers.

The tool submission is to be accompanied by an extended abstract that discusses the relevance, novelty, innovativeness and maturity of the tool. The extended abstract, should describe at least the following information:

  1. The significance of the tool to the PM field;
  2. The innovations of the tool to the PM community and its main features;
  3. The maturity of the tool. For this section, one could provide a brief description of case studies performed using the tool, provide scalability data or pointers indicating where readers can find more information about these case studies;
  4. A link to a Web page where to ​download or use the tool​. If the tool requires a license, a paper’s appendix should describe how to obtain a (temporary) license. The procedure to obtain the license must not disclose the identity of the reviewers. The appendix will not be included in the final version for the proceedings, if the demo is accepted.
  5. A link to a ​video that screencasts and demonstrates the tool, preferably including voice, which must not be longer than 4 minutes

Submission and Review Process

The extended abstract should be submitted through the ICPM 2022 submission system, which is reachable at where one should select “ICPM Demo Track”.

Demo abstracts must be no longer than 2 pages in PDF format and must adhere to the guidelines of IEEE Computational Intelligence Society conference proceedings, using the 8.5″ × 11″ two-column format. Templates are available for Latex and Word here. Accepted submissions will be published as CEUR proceedings.

All demo submissions will be reviewed by the demo reviewing committee. The reviewing committee will also vote on the best demo to be granted the ICPM 2022 Best Demo Award.


The practical organization of the Demo Track will be communicated later. Please be aware that due to circumstances that the number of available places will be limited.

Key Dates

Extended abstract submission: September 2, 2022
Notification of Acceptance:  September 30, 2022
Camera-Ready: October 7, 2022


Program Committee

Richard Hobeck, TU Berlin
Felix Mannhardt, Eindhoven University of Technology
Amine Andaloussi, University of St Gallen
Giovanni Meroni, Technical University of Denmark
Claudio Di Ciccio, Sapienza University of Rome
Andrea Marrella, Sapienza University of Rome
Thomas Chatain, LSV, ENS Paris-Saclay, Cachan, France
Gerhardus van Hulzen, Hasselt University
Abel Armas Cervantes, The University of Melbourne
Irene Bedilia Estrada Torres, University of Seville
Sander J.J. Leemans, RWTH Aachen
Arik Senderovich, York University
Jorge Munoz-Gama, Pontificia Universidad Católica de Chile
Flavia Santoro, UERJ
Gert Janssenswillen, Universiteit Hasselt
Pavlos Delias, International Hellenic University
Luciano García-Bañuelos, Tecnológico de Monterrey
Andrea Burattin, Technical University of Denmark
Dirk Fahland, Eindhoven University of Technology
Manuel Resinas, University of Seville
Chiara Di Francescomarino, Fondazione Bruno Kessler-IRST
Eric Verbeek, Eindhoven University of Technology
Greg Van Houdt, Hasselt University
Jochen De Weerdt, Katholieke Universiteit Leuven