We are particularly interested in issues that prevent process management systems from being enacted broadly. Therefore, we concentrate our research on agile process management what deals with processes that show a high amount of variability. On the following web pages we show how we approach the issue of agile process management with declarative process management technology.
Data Science as the field that “makes the most out of Big Data” is one of the fastest growing fields in computer science. We focus on two major aspects of Data Science: the conceptual design of large data sets and business intelligence as technique for transforming raw data into meaningful information. We explore these techniques specifically from the perspective of process mining and process analysis. Most of our laboratories and student projects address these research areas.
Modeling and Infrastructure
Two more domains of interest must be mentioned to complete the research portfolio of our chair. First, meta modeling and especially domain specific modeling serve as an underlying conceptual basis for our research. Particularly, many projects in the realm of process science are leveraging on the outcomes of these two research areas. Second, we consider process and data science as enabling technology for many infrastructure projects. The application of research results from these domains also approves their applicability and usability, which is one of the main goals of our chair.