Research at the Chair of Applied Computer Science IV (Databases and Information Systems) is focusing on generic methods and architectures for modelling and implementing database and/or process-based information systems. The focal point of our research lies in the comprehensive investigation of all aspects of process management. Our underlying thesis is that process management is an ideal means for all sorts of integration efforts within an enterprise. Although, we still see that many pragmatic issues of process management are not matured enough such that process management can become a standard technology that easily can be applied. Our aim is to further investigate the theoretical and conceptual basis of process management and translate these results into pragmatically solutions. According to this agenda, we split our research efforts into these research domains:
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 Process Management and especially on the website of our Competence Center for Practical Process Management (C2P2) we show how we approach the issue of agile process management with declarative process management technology.
This research domain explores the powerful capabilities of modelling. Especially, we are interested in the research domains of meta modelling and domain specific language modelling since we need results from these areas to enact our ideas for process management.
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.
We consider process management technology and data analytics as enabling technology for many infrastructure projects. This research domain is experimentally exploring the potential of process management technology and data analytics in this application domain.