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Netz, Lukas ; Michael, Judith ; Rumpe, Bernhard

AI-based and Model-driven Methods to Guide Citizens through Processes in the Public Sector

Netz, Lukas , Michael, Judith and Rumpe, Bernhard (2025) AI-based and Model-driven Methods to Guide Citizens through Processes in the Public Sector. In: Joint Proceedings of the STAF 2025 Workshops: OCL, OOPSLE, LLM4SE, ICMM, AgileMDE, AI4DPS, and TTC co-located with the International Conference on Software Technologies: Applications and Foundations (STAF 2025), 10.-13.6.2025, Koblenz, Germany.

Date of publication of this fulltext: 22 Dec 2025 06:53
Conference or workshop item
DOI to cite this document: 10.5283/epub.78370


Abstract

Digitalization of processes in the public sector is a challenging endeavor for citizens: too long or ambiguous forms and unfamiliar terms make it challenging to participate in these processes. What is needed are methods to guide citizens with IT systems through processes in the public sector in a user-centric way. Within this paper, we investigate how to develop web systems that provide ...

Digitalization of processes in the public sector is a challenging endeavor for citizens: too long or ambiguous forms and unfamiliar terms make it challenging to participate in these processes. What is needed are methods to guide citizens with IT systems through processes in the public sector in a user-centric way. Within this paper, we investigate how to develop web systems that provide citizen-centered guidance in several dimensions: explanatory content, guided navigation, contextual process support, and form completion. Our solution integrates generative AI and model-driven engineering methods to develop web applications for the public sector. This has not only advantages for citizens, but we can also enhance the system maintenance of such systems with these methods. We present the main processes of how to realize such integrated approaches, provide some examples from practice, and discuss open challenges for the approaches.



Involved Institutions


Details

Item typeConference or workshop item (Paper)
Publisher:CEUR-WS
Open Access Type:CC-License
Date10 December 2025
InstitutionsInformatics and Data Science > General computer science > Chair of Programming and Software Engineering (Prof. Dr. Judith Michael)
KeywordsPublic Processes, Model-Driven Engineering, Artificial Intelligence, Large Language Model, AI4SE, Human-centric systems
Dewey Decimal Classification000 Computer science, information & general works > 004 Computer science
StatusPublished
RefereedYes, this version has been refereed
Created at the University of RegensburgPartially
URN of the UB Regensburgurn:nbn:de:bvb:355-epub-783700
Item ID78370

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