- EdbA'24 -
Fifth International Workshop on Event Data and
Behavioral Analytics
Copenhagen, Denmark, 14 October 2024
Co-located at ICPM 2024

An activity from the IEEE Task Force on Process Mining
Over the past decades, capturing, storing and analyzing event data has gained attention in various domains such as process mining, clickstream analytics, IoT analytics, e-commerce and retail analytics, online gaming analytics, security analytics, website traffic analytics and preventive maintenance, smart homes and offices, just to name a few. It even resulted in the birth of new research domains such as behavioral informatics, behavioral analytics and behavioral operations research. The interest in event data lies in its analytical potential as it captures the dynamic behavior of people, objects and/or systems at a fine-grained level.
While each of these domains have their own applications and idiosyncrasies, they share the common denominator of event data and the objective to analyze behavior. Yet, these domains also differ in underlying assumptions and techniques used. Therefore, the objective of this workshop is to provide a forum to practitioners and researchers for studying a quintessential, minimal notion of events as the common denominator for records of discrete behavior in all its forms, and to study, develop and discuss techniques and methods for behavioral analytics based on all kinds of events.
The Event Data & Behavioral Analytics (EdbA) workshop considers as its starting point the presence of event data being recorded at various sources and contexts, being stored in various forms, and being considered for analysis of behavior of various kinds. Event data at different levels of granularity are considered, ranging from frequent sensor-based events in IoT settings to recordings of aggregate or long-running behavior involving time intervals and rich information. Behavior often involves multiple entities, objects, and actors to which events can be correlated in various ways. In these situations, a unique explicit process notion does either not exist, is unclear or different processes or dynamics could be recorded in the same dataset.
The workshop aims to further the development of new (or the novel application of existing) techniques, algorithms and data structures for recording, storing, managing, processing, analyzing, and visualizing event data in various forms. The workshop welcomes two types of submissions, i.e. original research papers as well as case study reports on event data and behavioral analytics.
The topics considered in the workshop consist of, but are not limited to:
- Augmentation of fine-grained event data to higher-order activities or behavior
- Storage, integration, and querying of behavioral event data
- Representation and analysis of event data without a unique case identifier (without case identifier or with multiple case identifiers present)
- Monitoring and detection of complex behavior
- Diagnosis of behavior, including root-cause analysis, variance analysis, cluster analysis and many other exploratory analysis techniques
- Visual analytics of (complex) behavior
- Behavior Pattern detection, e.g., in real-time location data or other types of context-rich data
- Outlier Behavior Detection
- Behavior Prediction
- Prescriptive analytics which predicts behavior and prescribes which action could steer behavior in a specific direction
- Calvin Schröder, Jan Niklas van Detten and Sander J. J. Leemans. Locally Optimized Process Tree Discovery. (pdf)
- Viki Peeva, Marvin Porsil and Wil van der Aalst. Object-Centric Local Process Models. (pdf)
- Alfonso Bravo, Cristina Cabanillas, Joaquin Peña and Manuel Resinas. Analyzing the Evolution of Boards in Collaborative Work Management Tools. (pdf)
- Flavio Corradini, Sara Pettinari, Barbara Re, Lorenzo Rossi and Massimiliano Sampaolo. Toward Robotic Event Logs for Process Mining: Feature Identification and Processing.
- Edyta Brzychczy, Tomasz Pełech-Pilichowski and Ziemowit Dworakowski. Case ID detection based on time series data – the mining use case.
- Arvid Lepsien, Marco Pegoraro, Frederik Fonger, Dominic Langhammer, Milda Aleknonytė-Resch and Agnes Koschmider. Ranking the Top-K Realizations of Stochastically Known Event Logs. (pdf)
- Jan Niklas van Detten, Pol Schumacher and Sander J.J. Leemans. A Framework for Advanced Case Notions in Object-Centric Process Mining. (pdf)
- Lukas Liss, Nico Elbert, Christoph Flath and Wil van der Aalst. Framework for Extracting Real-World Object-Centric Event Logs from Game Data. (pdf)
- Maike Basmer, Martin Kabierski, Kristina Sahling, Saimir Bala, Agnieszka Patecka and Jan Mendling. A Classification of Data Quality Issues in Object-Centric Event Data. (pdf)
- Nina Graves, Tobias Brockhoff, István Koren and Wil van der Aalst. Extending Process Intelligence with Quantity-related Process Mining. (pdf)
- Discussion on open problems, issues and trends in event data and behavioral analytics
All accepted papers are published by Springer in the Lecture Notes in Business Information Processing (LNBIP) series.
Organizing Committee
- Depaire Benoît, Hasselt University, Belgium
- Fahland, Dirk, Eindhoven University of Technology, the Netherlands
- Leotta, Francesco, Sapienza University of Rome, Italy
- Senderovich, Arik, York University, Canada
Program Committee
- Simone Agostinelli, Sapienza University of Rome, Italy
- Yannis Bertrand, Katholieke Universiteit Leuven, Belgium
- Ioannis Chatzigiannakis, Sapienza University of Rome, Italy
- Jochen De Weerdt, Katholieke Universiteit Leuven, Belgium
- Claudio Di Ciccio, Utrecht University, the Netherlands
- Massimiliano de Leoni, University of Padua, Italy
- Chiara Di Francescomarino, Fondazione Bruno Kessler-IRST, Italy
- Fabrizio Fornari, University of Camerino, Italy
- Gert Janssenswillen, Hasselt University, Belgium
- Eva Klijn, Eindhoven University of Technology, the Netherlands
- Felix Mannhardt, Eindhoven University of Technology, the Netherlands
- Niels Martin, Hasselt University, Belgium
- Massimo Mecella, Sapienza University of Rome, Italy
- Renata Medeiros de Carvalho, Eindhoven University of Technology, the Netherlands
- Jan Mendling, Humboldt-Universität zu Berlin, Germany
- Barbara Re, University of Camerino, Italy
- Stef van den Elzen, Eindhoven University of Technology, the Netherlands
- Francesca Zerbato, University of St. Gallen, Austria