Efficient and identity-enhancing law enforcement in the municipality of a mid-sized town ("Law enforcement")

• Applicant: Dr. Hendrik Scholta
• Subject Area: Data Management, Data-Intensive Systems, Computer Science Methods in Business Informatics ; Management and Marketing
• Term: since 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 462287308

Public services are specified by legal regulations. Legislators enact legal norms to define services that are subsequently provided by municipalities. Many of the implementing authorities individually analyze legal texts in order to derive implications for their actions, for instance, to determine required form fields and to design internal processes. This results in redundant efforts, which mid-sized towns in particular can afford less than large cities due to their limited financial resources. In addition, mid-sized towns have to implement the central requirements on the one hand, while on the other hand they want to preserve and emphasize their identity, individuality and independence. Mid-sized towns have a strong local patriotism, but often do not have the financial means to strengthen their own identity through marketing activities. This is where a town's agency is called upon to position itself as a regional player, i.e. to demonstrate its capabilities. The resource-saving accentuation of the local identity is of essential importance, especially for mid-sized towns. Therefore, this subproject develops a semi-automatic method that supports and simplifies law enforcement with the help of reference models in such a way that redundant workloads are reduced and at the same time the local identity and logic of a mid-sized town are strengthened. This subproject uses a design-oriented approach that goes through the phases of analysis, design (concept and demonstrator), evaluation, and diffusion, as it is common in information systems research.

• DFG Programme: Research Units
• Subproject of: FOR 5393: The future smart town
• Co-Investigators: Professor Dr. Matthias Grundmann; Professor Dr. Norbert Kersting