On the 8 and 9th of February 2018, we gathered with an international group of process mining researchers to discuss the many challenges in the field of conformance checking. The event was organized by the Flemish Scientific Research Community on Process Mining (htpps://www.srcprocessmining.org), a community that is led by our research group, together with KULeuven and UGent. The brainstorm session was attended by researchers from the Polytechnic University of Catalonia, the Pontifical Catholic University of Chile, RWTH Aachen University, the Technical University of Eindhoven and the Wirtschaftsuniversität Wien.
Organizations are nowadays storing huge amounts of data related to various business processes. Process mining provides different methods and techniques to analyze and improve these processes. This allows companies to gain a competitive advantage. Process mining initiated with the discovery of work-flow models from event data. However, over the past 20 years, the process mining field has evolved into a broad and diverse research discipline.
The world of education is changing more than ever. Since the emergence of the internet, platforms for e-learning are becoming omnipresent. The use of video lectures and other online learning materials are rapidly replacing traditional lectures and textbooks. As learning is occurring more and more online, teachers are facing new challenges. The increasing distance between student and instructor asks for new tools to track and adjust learning activities.
The huge potential of process mining applications is -luckily- already discovered in a variety of business settings. In industry, more and more companies are learning about its potential value. In meanwhile, academic researchers continue their quest to the best algorithm, the most meaningful metrics, the most understandable visualisations, etcetera. Whatever ‘best’, ‘meaningful’, and ‘understandable’ may be… These are food for thought and discussion on their own. But I’d like to address a different mini-research-topic-on-its-own: the event log.
An implicit assumption in process mining (both research and applications), is the existence of an event log.