Visual Analytics Meets Process Mining
Problem
Visual Analytics integrates the outstanding capabilities of humans in terms of visual information exploration with the enormous processing power of computers to form a powerful knowledge discovery environment. Process Mining aims to extract information and knowledge from event logs to discover, monitor, and improve processes in a variety of application domains. The combination of interactive visual data analyses and exploration with Process Mining algorithms makes complex information structures more comprehensible and facilitates new insights. However, this combination is partly an uncharted territory.
Aim
You should provide a systematic overview of existing approaches in scientific literature that support or could support the combination of Visual Analytics and Process Mining to extract more insights from complex event data and ease the analysis process.
Other information
Starting point(s) for research:
- Process Mining Manifesto
- part of the book: Wil van der Aalst, Process Mining: Data Science in Action, Springer, 2016.
- Anton Yeshchenko, Jan Mendling, A Survey of Approaches for Event Sequence Analysis and Visualization using the ESeVis Framework, 2022. or https://www.sciencedirect.com/science/article/pii/S0306437923001199?via%3Dihub
- Wil van der Aalst
- Silvia Miksch gave a keynote talk entitled "Visual Analytics Meets Process Mining: Challenges and Opportunities" at 3rd International Conference on Process Mining in Eindhoven, The Netherlands (see also https://www.cvast.tuwien.ac.at/bibcite/reference/541)