The EdbA workshop aims to provide a forum for discussing and developing analytics for various forms of event data. In its most basic form, such data describes discrete events, which occur instantly – and thus have no duration, are ordered in time and are described by a set of attributes. The analytical potential of event data lies in the fact that it captures the dynamic behavior of people, objects and/or systems at a fine-grained level.

The Fourth International Workshop on Leveraging Machine Learning in Process Mining is a premier event that aims to foster collaboration and innovation in the intersection of machine learning and process mining. Over the past few years, the combination of these two fields has generated a lot of interest, and this workshop provides an excellent opportunity for researchers and practitioners to share their latest findings and explore new directions for future research.

The world’s most valuable resource is no longer oil, but data. The goal of data science techniques is not to collect more data, but to extract knowledge and valuable insights from existing data in various forms. To analyze and improve processes, event data is the main source of information. In recent years, a new discipline has emerged combining traditional process analysis and data-centric analysis: Process-Oriented Data Science (PODS). The interdisciplinary nature of this new research area has resulted in its application to analyze processes in a wide variety of domains. This workshop has an explicit focus on healthcare.

Process Mining has proven to be a powerful interdisciplinary tool for addressing open challenges in several fields such as healthcare or finances … and Education is no exception. The recent Process Mining approaches proposed for learning analytics, curricular analytics, or MOOC analytics are just some examples. But the Education discipline is also contributing to Process Mining, providing best practices, lessons learned, and new artifacts for better teaching and assessing Process Mining.The International Workshop on Education meets Process Mining (EduPM) aims at providing a high-quality forum for the intersection of Education and Process Mining.

The Second Workshop on Collaboration Mining for Distributed Systems (COMINDS 2023) aims to facilitate the sharing of research findings, ideas, and experiences on new process mining techniques and practices for analyzing collaboration processes. Process mining is a powerful tool for the analysis of business processes carried on by one participant. However, it lacks approaches able to deal with the analysis of collaboration processes implemented by many participants in a distributed system e.g., supply chains involving manufacturers, producers, and retailers; healthcare scenarios involving patients, hospitals, and doctors; or even smart systems like multi-robot and IoT systems.

Process mining has been successfully applied in analysing and improving processes based on event logs in all kinds of environments. Responsible process mining is highly relevant to our more and more data-driven society and has received less focus. FACT (Fair, Accurate, Confidential, and Transparent) and similar other principles for data science and machine learning have been proposed (cf. https://redasci.org/) to guide the development and application of data science.