Algorithms & Theories for the
Analysis of Event Data 2016

The workshop Algorithms & Theories for the Analysis of Event Data (ATAED 2016) is a satellite event of both the 37th International Conference on Application and Theory of Petri Nets and Concurrency and the 16th International Conference on Application of Concurrency to System Design (PN 2016 and ACSD 2016). The workshop aims to attract papers related to process mining, region theory and other synthesis techniques. These techniques have in common that "lower level" behavioral descriptions (event logs, sets of partial orders, transition systems, etc.) are used to create "higher level" process models (e.g., various classes of Petri nets, BPMN, or UML activity diagrams).

ATAED 2016 solicits papers related to process mining and region theory. However, the scope is not limited to this. The program committee invites submission of full papers (up to 15 pages) and of short papers (up to 5 pages). Papers should be submitted as pdf-files using the Springer LNCS-format. Papers need to be submitted via Easychair.

Process mining makes it possible to analyze event data, thereby focusing on behavior rather than correlations and simplistic performance indicators. For example, event logs can be used to automatically learn end-to-end process models based on recorded event data. Next to the automated discovery of the real underlying process, there are process mining techniques to analyze bottlenecks, to uncover hidden inefficiencies, to check compliance, to explain deviations, to predict performance, and to guide users towards "better" processes.

Region theory makes it possible to synthesize a process model from a behavioral description. Applying the theory of regions guarantees the behavioral description and the language of the synthesized model to be equivalent. In recent years, various forms of region-based ideas (language-based and state-based variants) have been applied in the context of process mining. Here, there is only example behavior and classical techniques need to be improved. Hence, there are many theoretical challenges with a high practical relevance.

Wil van der Aalst,TU Eindhoven, The Netherlands (co-chair)
Eric Badouel, INRIA Rennes, France
Robin Bergenthum, FernUni Hagen, Germany (co-chair)
Luca Bernardinello, Università degli studi di Milano-Bicocca, Italy
Seppe vanden Broucke, KU Leuven, Belgium
Andrea Burattin, University of Innsbruck, Austria
Toon Calders, Université Libre de Bruxelles, Belgium
Josep Carmona, UPC Barcelona, Spain (co-chair)
Paolo Ceravolo, University of Milan, Italy
Claudio Di Ciccio, Vienna University of Economics and Business, Austria
Manuel Mucientes, University of Santiago de Compostela, Spain
Benoît Depaire, Hasselt University, Belgium
Jörg Desel, FernUni Hagen, Germany

Dirk Fahland , TU Eindhoven, The Netherlands
Diogo Ferreira , Universidade de Lisboa, Portugal
Luciano García-Bañuelos, University of Tartu, Estonia
Stefan Haar, LSV CNRS & ENS de Cachan, France
Gabriel Juhás, Slovak University of Technology, Slovak Republic
Anna Kalenkova, Higher School of Economics NRU, Russia
Jetty Kleijn, Leiden University, The Netherlands
Robert Lorenz, Uni Augsburg, Germany
Hernán Ponce de León, Aalto University, Finland
Marta Pietkiewicz-Koutny, Newcastle University, GB
Marcos Sepúlveda, Universidad Catolica de Chile, Chile
Jochen De Weerdt, KU Leuven, Belgium
Alex Yakovlev, Newcastle University, GB

Abstract: In this talk, I will explore some of the most fascinating possibilities emerging from the challenging, but in my opinion necessary, marriage between data and processes, and their corresponding fields of study. I will in particular range from the design-time analysis of process models to the a-posteriori analysis of their event data. At design time, I will discuss how recent advancements coming from database theory and artificial intelligence can be fruitfully applied to the analysis of models that reflect real process management systems. In particular, I will overview how conventional planning and model checking techniques can be lifted, in principle, to handle verification of infinite-state systems arising from workflow nets ehnanced with CRUD operations over full-fledged relational databases. As for the analysis of event data, I will focus on the crucial, typically neglected problem of data preparation for process mining. Process mining techniques can be suitably applied only when the event data are rigidly structured according to a well-defined schema (such as an XML file complying to the XES format). However, in an enterprise setting such event data are usually not explicitly represented, but are instead hidden inside legacy information systems. Borrowing techniques and tools from conceptual modeling and intelligent data management, such two levels of abstraction will be reconciled. Specifically, I will introduce an operational framework for extracting event data from legacy databases, starting from assertions expressed at the conceptual level.

Marco Montali is an Assistant Professor (in a tenure-track position for Associate Professor) at the KRDB Research Centre for Knowledge and Data, Free University of Bozen-Bolzano (Italy). His research activity focuses on foundational, methodological and experimental aspects of knowledge representation and automated reasoning for the intelligent, holistic management of processes and data, encompassing the formal specification, verification, monitoring and mining of data-aware business processes, clinical guidelines, service-oriented and multiagent systems. On these topics, he authored a Springer monograph and more than 90 papers, published in top-level international journals and conferences, such as ACM TWEB, ACM TIST, JAIR, JAAMAS, PODS, IJCAI, KR, AAAI, AAMAS, BPM, ICSOC. His PhD dissertation was honored with the 2007-2009 “Marco Cadoli” Distinguished Dissertation Award, given by the Italian Association for Logic Programming to the most outstanding italian thesis focused on computational logic. In 2015, he was honored with the Artificial Intelligence “Marco Somalvico” 2015 Prize, given by the Italian Association for Artificial Intelligence to an italian researcher under 35 years who autonomously contributed to advance the state-of-the-art in Artificial Intelligence. He is recipient of three best paper awards.

Monday, June 20

Tuesday, June 21