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Keynote Lectures

Process Mining as the Superglue between Data and Process Management
Wil van der Aalst, RWTH Aachen University, Germany

From Data to the Press: Data Management for Journalism and Fact-Checking
Ioana Manolescu, Inria, France

 

Process Mining as the Superglue between Data and Process Management

Wil van der Aalst
RWTH Aachen University
Germany
 

Brief Bio
Prof.dr.ir. Wil van der Aalst is a full professor at RWTH Aachen University leading the Process and Data Science (PADS) group. He is also part-time affiliated with the Fraunhofer-Institut für Angewandte Informationstechnik (FIT) where he leads FIT's Process Mining group and the Technische Universiteit Eindhoven (TU/e). Until December 2017, he was the scientific director of the Data Science Center Eindhoven (DSC/e) and led the Architecture of Information Systems group at TU/e. Since 2003, he holds a part-time position at Queensland University of Technology (QUT). Currently, he is also a distinguished fellow of Fondazione Bruno Kessler (FBK) in Trento and a member of the Board of Governors of Tilburg University. His research interests include process mining, Petri nets, business process management, workflow management, process modeling, and process analysis. Wil van der Aalst has published over 220 journal papers, 20 books (as author or editor), 500 refereed conference/workshop publications, and 75 book chapters. Many of his papers are highly cited (he one of the most cited computer scientists in the world; according to Google Scholar, he has an H-index of 145 and has been cited over 97,500 times) and his ideas have influenced researchers, software developers, and standardization committees working on process support. Next to serving on the editorial boards of over ten scientific journals, he is also playing an advisory role for several companies, including Fluxicon, Celonis, Processgold, and Bright Cape. Van der Aalst received honorary degrees from the Moscow Higher School of Economics (Prof. h.c.), Tsinghua University, and Hasselt University (Dr. h.c.). He is also an elected member of the Royal Netherlands Academy of Arts and Sciences, the Royal Holland Society of Sciences and Humanities, and the Academy of Europe. In 2018, he was awarded an Alexander-von-Humboldt Professorship.


Abstract
Process mining is rapidly becoming a standard way to analyze performance and compliance problems based on event data. Currently, there are over 30 commercial process-mining tools based on the research by prof. Van der Aalst and his team. Process mining reveals how processes behave "in the wild". Seemingly simple processes like Order-to-Cash (OTC) and Purchase-to-Pay (P2P), turn out to be much more complex than anticipated. Hand-made models describing behavior (BPMN, UML activity diagrams, EPCs, flow charts, etc.) often fail to capture reality. Process mining connects Business Process Management (BPM) and data-driven approaches such as Data Mining (DM), Machine Learning (ML), Artificial Intelligence (AI), and Business Intelligence (BI) by combining a process-centric view and the evidence hidden in an organization's databases. In his talk, Wil van der Aalst (“the godfather of process mining”) reflects on the capabilities and limitations of today’s process mining tools. He will also discuss the conversion of data from today's information systems into event logs showing different viewpoints.



 

 

From Data to the Press: Data Management for Journalism and Fact-Checking

Ioana Manolescu
Inria
France
 

Brief Bio
Ioana Manolescu is the lead of the CEDAR team, joint between Inria Saclay and the LIX lab (UMR 7161) of Ecole polytechnique, in France. The CEDAR team research focuses on rich data analytics at cloud scale. She is a member of the PVLDB Endowment Board of Trustees, and a co-president of the ACM SIGMOD Jim Gray PhD dissertation committee. Recently, she has been a general chair of the IEEE ICDE 2018 conference, an associate editor for PVLDB 2017 and 2018, and the program chair of SSDBBM 2016. She has co-authored more than 130 articles in international journals and conferences, and contributed to several books. Her main research interests include data models and algorithms for computational fact-checking, performance optimizations for semistructured data and the Semantic Web, and distributed architectures for complex large data. She is also the scientific director of LabIA, a French government initiative for adopting AI tools in the public administration.


Abstract
Modern societies crucially rely on the availability of free media. While any citizen has today access to the necessary tools to publish content and debate, the best standards for reliable, verified reporting and for well-structured debates are still held by professional journalists. Historically confined to newsrooms and performed before publication, verification of claims (aka fact-checking) has now become a very visible part of journalists' activity; the importance of some topics under discussion (e.g., large-scale pollution or the national economy) has also attracted fact-checkers outside the journalism industry, such as scientists, NGOs etc. In this talk, I will outline a vision of Journalistic Dataspaces, as an environment and set of tools that should support journalists and/or fact-checkers by means of digital content management. This draws upon the recent years of collaboration with journalists from French media, notably Le Monde's fact-checking team "Les Décodeurs" and Ouest France, a large regional newspaper, as well as many academic colleagues. I will highlight the common needs of fact-checking and modern ("data") journalism, show how existing tools from the database, information retrieval, knowledge representation and natural language processing can help realize this vision. I will also discuss the main technical and organizational challenges toward realizing this vision. Most of this work is part of the [ http://contentcheck.inria.fr/ | ANR ContentCheck project ] .



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