Towards an event-centric knowledge graph approach for public administration

Public administrations (PA) around the globe produce and handle a vast amount of data that are mainly the outcome of interactions of end-users. By evaluating the focus of PA one finds that most interactions involve only a few core entities such as the citizen or business. Usually, this information involving the core entities are scattered in numerous siloed databases developed by different departments and divisions, thus hindering PA to provide a comprehensive overview of their core entities and their interactions. Recently, knowledge graphs have been proposed for structuring large collections of data in a meaningful way, however they tend to represent a static state of the world and do not focus on the dynamics and changes over time. To address this, a new approach of event-centric knowledge graphs has been introduced that captures the dynamics of knowledge considering events as first-class entities for knowledge representation. The aim of this paper is to apply an event-centric knowledge graph approach for a holistic data governance of all data repositories in PA which models all interactions of PA related actors. We anticipate that the proposed approach will also facilitate PAs to adopt a data-centic orientation that can facilitate ubiquitous AI and data analytics.