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  • 标题:Enhancing Core Public Service Vocabulary to Enable Public Service Personalization
  • 本地全文:下载
  • 作者:Alexandros Gerontas ; Dimitris Zeginis ; Rafail Promikyridis
  • 期刊名称:Information
  • 电子版ISSN:2078-2489
  • 出版年度:2022
  • 卷号:13
  • 期号:5
  • 页码:225
  • DOI:10.3390/info13050225
  • 语种:English
  • 出版社:MDPI Publishing
  • 摘要: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.
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