Please use this identifier to cite or link to this item: https://ruomo.lib.uom.gr/handle/7000/1506
Title: Enhancing Core Public Service Vocabulary to Enable Public Service Personalization
Authors: Gerontas, Alexandros
Zeginis, Dimitris
Promikyridis, Rafail
Androš, Marin
Tambouris, Efthimios
Cipan, Vibor
Tarabanis, Konstantinos
Type: Article
Subjects: FRASCATI::Social sciences
FRASCATI::Social sciences
Keywords: public service
personalization
knowledge graph
chatbot
CPSV-AP
Issue Date: 2022
Source: Information
Volume: 13
Issue: 5
First Page: 225
Abstract: The provision of public services (PS) is at the heart of public authority operations as it directly affects citizens’ lives and the prosperity of society. Part of PS provision is publishing PS descriptions in an online catalogue to inform citizens and promote transparency. The European Commission has developed Core Public Service Vocabulary Application Profile (CPSV-AP), as a standard European PS data model to facilitate PS catalogue creation and semantic interoperability. However, CPSV-AP is not sufficient to model complex PS with different versions based on rules and citizens’ circumstances (e.g., getting a passport for a child or for an emergency). As a result, citizens cannot obtain personalized information on PS. The aim of this paper is to enhance CPSV-AP in order to support the modeling of complex PS. We illustrate the use of the proposed model in a real-life case study. Specifically, we use the proposed model to develop a knowledge graph and a chatbot that provides personalized information to citizens of the city of Bjelovar (Croatia) regarding the life-event “having a baby”. We believe our research is of interest to researchers on PS data models and public authorities interested in providing personalized PS information to their citizens using chatbots.
URI: https://doi.org/10.3390/info13050225
https://ruomo.lib.uom.gr/handle/7000/1506
ISSN: 2078-2489
Other Identifiers: 10.3390/info13050225
Appears in Collections:Department of Applied Informatics

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