Direkt zum Inhalt

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 und 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.

Veröffentlichungsdatum dieses Volltextes: 22 Dez 2025 06:53
Konferenz- oder Workshop-Beitrag
DOI zum Zitieren dieses Dokuments: 10.5283/epub.78370


Zusammenfassung

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.



Beteiligte Einrichtungen


Details

DokumentenartKonferenz- oder Workshop-Beitrag (Paper)
Verlag:CEUR-WS
Datum10 Dezember 2025
InstitutionenInformatik und Data Science > Allgemeine Informatik > Lehrstuhl für Programmierung und Software Engineering (Prof. Dr. Judith Michael)
Stichwörter / KeywordsPublic Processes, Model-Driven Engineering, Artificial Intelligence, Large Language Model, AI4SE, Human-centric systems
Dewey-Dezimal-Klassifikation000 Informatik, Informationswissenschaft, allgemeine Werke > 004 Informatik
StatusVeröffentlicht
BegutachtetJa, diese Version wurde begutachtet
An der Universität Regensburg entstandenZum Teil
URN der UB Regensburgurn:nbn:de:bvb:355-epub-783700
Dokumenten-ID78370

Bibliographische Daten exportieren

Nur für Besitzer und Autoren: Kontrollseite des Eintrags

nach oben