Name of the participant: Daniel Schuster
Description of the IT research project: Process mining aims to improve operational processes—ranging from production to business processes—in a data-driven manner. To this end, process mining provides methods and techniques for systematically analyzing event data. This data is generated during the execution of processes and stored in enterprise information systems. Process discovery, a key discipline of process mining, includes techniques for (automatically) learning a process model from event data. However, existing algorithms typically produce low-quality models from event data due to data quality issues and incompletely captured process behavior. Further, existing algorithms are fully automated, and hence, they function as a black box from the user’s perspective. Automated filtering of event data is valuable to obtain better process models. At the same time, it is often too rigorous, i.e., it also removes valuable and correct data.
In many cases, prior knowledge about the process under investigation can be used for process discovery in addition to event data. The project “Cortado: A Tool for Interactive Process Discovery” is concerned with developing a software tool allowing users to discover a process model from event data interactively. By combining machine and human intelligence—hybrid intelligence—Cortado aims to overcome the drawbacks of conventional, automated process discovery approaches. To this end, this project aims to develop new approaches for interactive process discovery and integrate them into the tool. For the practical evaluation of the research results, operational processes from the industry partner IAV will be analyzed with the tool Cortado.
Software Campus partners: Fraunhofer-Verbund IuK-Technologie, IAV
Implementation period: 01.02. 2022 – 31.01.2021
