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https://ceur-ws.org/Vol-3167/xpreface.pdf
Workshop Proceedings
Workshop on
Algorithms & Theories for the
Analysis of Event Data (ATAED’2022)
Workshop, June 24, 2022
supported by the IEEE Task Force on Process Mining
Satellite event of the conference
43rd International Conference on Application and Theory
of Petri Nets and Concurrency (Petri Nets 2022)
Edited by
Robert Lorenz, Jan Martijn van der Werf, and Sebastiaan J. van Zelst
.
Copyright © 2022 for the individual papers is held by the papers’ authors.
Copying is permitted only for private and academic purposes.
This volume is published and copyrighted by its editors.
Preface
Ehrenfeucht and Rozenberg defined regions more than 30 years ago as sets
of nodes of a finite transition system. Every region relates to potential condi-
tions that enable or disable transition occurrences in an associated elementary
net system. Later, similar concepts were used to define regions for Petri nets
from languages as well. Both state-based and language-based approaches aim to
constrain a Petri net by adding places deduced from the set of regions. By now,
many variations have been proposed, e.g., approaches dealing with multiple to-
kens in a place, region definitions for Petri nets with inhibitor arcs, extensions
to partial languages, regions for infinite languages, etc.
Initially, region theory focused on synthesis. We require the input and the
behavior of the resulting Petri net to be equivalent. Recently, region-based re-
search started to focus on process mining as well where the goal is not to create
an equivalent model but to infer new knowledge from the input. Process min-
ing examines observed behavior rather than assuming a complete description
in terms of a transition system or prefix-closed language. For this reason, one
needs to deal with new problems such as noise and incompleteness. Equivalence
notions are replaced by trade-offs between fitness, simplicity, precision, and gen-
eralization. A model with good fitness allows for most of the behavior seen in
the event log. A model that does not generalize is “overfitting”. Overfitting is the
problem that a very specific model is generated whereas it is obvious that the log
only holds example behavior. A model that allows for “too much behavior” lacks
precision. Simplicity is related to Occam’s Razor which states that “one should
not increase, beyond what is necessary, the number of entities required to explain
anything”. Following this principle, we look for the simplest process model that
can explain what was observed in the event log. Process discovery from event
logs is very challenging because of these and many other trade-offs. Clearly, there
are many theoretical process-mining challenges with a high practical relevance
that need to be addressed urgently.
All these challenges and opportunities are the motivation for organizing the
Algorithms & Theories for the Analysis of Event Data (ATAED) workshop. The
workshop first took place in Brussels in 2015 as a succession of the Applications
of Region Theory (ART) workshop series. From there on, the workshop moved to
Toruń (2016), Zaragoza (2017), Bratislava (2018), Aachen (2019), and virtually
in 2020 (due to the COVID-19 pandemic). After the success of these workshops,
it is only natural to bring together researchers working on region-based synthesis
and process mining again.
The ATAED’2022 workshop took place as a physical workshop on June 21st,
2022 and was a satellite event of the 43rd International Conference on Appli-
cation and Theory of Petri Nets and Concurrency (Petri Nets 2022), held in
Bergen, Norway.
Papers related to process mining, region theory and other synthesis tech-
niques were presented at the ATAED’2022, divided over three content-oriented
sessions, i.e., “Stochastics & Statistics”, “Region Theory” and “Strategies for Be-
havioral Analysis”. All the techniques presented have in common that “lower-
level” behavioral descriptions (event logs, partial languages, transition systems,
etc.) are used to create “higher level” process models (e.g., various classes of
Petri nets, BPMN, or UML activity diagrams). In fact, all techniques that aim
at learning or checking concurrent behavior from transition systems, runs, or
event logs were welcomed. The workshop was supported by the IEEE Task Force
on Process Mining (www.tf-pm.org/).
After a careful reviewing process, six papers (out of a total of ten submis-
sions) were accepted for the workshop. We thank the reviewers for providing the
authors with valuable and constructive feedback. We thank the authors and the
presenters for their wonderful contributions.
Enjoy reading the proceedings!
Robert Lorenz, Jan Martijn van der Werf, and Sebastiaan J. van Zelst
June 2022
Program committee of ATAED’2022
Abel Armas Cervantes, QUT, Australia
Luca Bernardinello, Universitá degli studi di Milano-Bicocca, Italy
Paolo Ceravolo, University of Milan, Italy
Jochen De Weerdt, KU Leuven, Belgium
Benoît Depaire, Hasselt University, Belgium
Jörg Desel, FernUni Hagen, Germany
Claudio Di Ciccio, Sapienza University of Rome, Italy
Chiara Di Francescomarino, FBK-IRST, Italy
Dirk Fahland, TU Eindhoven, The Netherlands
Stefan Haar, LSV CNRS & ENS de Cachan, France
Anna Kalenkova, University Adelaide, Australia
Jetty Kleijn, Leiden University, The Netherlands
Sander Leemans, RWTH Aachen University, Germany
Robert Lorenz, University of Augsburg, Germany (co-chair)
Lisa Mannel, RWTH Aachen University, Germany
Marta Pietkiewicz-Koutny, Newcastle University, United Kingdom
Andrey Rivkin, Free University of Bozen Bolzano, Italy
Daniel Schuster, Fraunhofer FIT/RWTH Aachen University, Germany
Arik Senderovich, York University, Canada
Ronny Tredup, University of Rostock, Germany
Lijie Wen, Tsinghua University, China
Alex Yakovlev, Newcastle University, United Kingdom
Jan Martijn van der Werf, Utrecht University, The Netherlands (co-chair)
Sebastiaan J. van Zelst, Fraunhofer FIT/RWTH Aachen University, Germany
(co-chair)