The global initiative supporting open government data (OGD) has witnessed significant strides in the last decade. This study delves into the prospective integration of Artificial Intelligence (AI) with Hippolyta, a framework meticulously crafted to amplify the interpretability of government data. The aim is to scrutinize the viability of this integration, conducting a technical investigation in the realms of open government data and artificial intelligence. In contributing to the expansive field of OGD, this research focuses on elucidating the interpretability of data originating from governmental sources. Through an exploration of the technical feasibility surrounding the fusion of AI with Hippolyta, we aim to pave the path for advancements, fostering heightened interpretability and overarching enhancements in the understanding of government data.

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As AI technology becomes more powerful, the impact on governance and the governance of AI becomes more important. The purpose of this panel is to bring together experts on Trustworthy AI and E-Governance to discuss the lessons learned so far and the challenges ahead. The goal is to provide a comprehensive review of challenges and potential solutions related to the future acceptance and beneficial application of AI-based solutions - including using AI for public benefit and applying AI for the common good.@en

Open government data initiatives have been rising quickly in recent times. They are encouraged by a wish to democratize data access and knowledge production and enhance cities socially and economically. The hardship of interpreting data can be considered an obstacle to using open government data and more prominent citizen engagement. Technology is crucial to enhance data interpretability and the practical construction of an open government. Nevertheless, the literature needed an instrument to support open government data's interpretability. In this work, our primary goal is to present the definition, implementation, and evaluation of a framework named Hippolyta, which is qualified to help citizens to interpret open government data. Hippolyta first identifies the citizen's necessities using a semantic enrichment module. After this step, the framework conducts the data collection through the same data retrieval module. Finally, Hippolyta creates a graphic visualization through a data visualization module. This study is relevant since it furnishes comprehensive insights into what the open data interpretability concept is composed of and which framework modules can sustain open data interpretation.@en