Academic Awards 2024 booklet

73 Linked Data for Smart Neighborhood Cities increasingly contribute to global energy consumption, which leads to a large set of challenges. However, there is only limited integration of (energy) data on an urban level, which limits the capability of integral solutions. This project built upon existing data structures to take the first steps towards a Semantic Digital Twin of Eindhoven, which was named Neo Dash. This Digital Twin allows the end-user to meaningfully explore data from previously unconnected and inaccessible sources to assess pressing challenges. An exploration of energy poverty in Eindhoven shows how this Semantic Digital Twin can provide valuable insights into solving the challenges urban areas face today by finding areas this issue is most pressing, allowing for more efficient problem solving. This project will serve as a foundation for further research and as proof of concept for employing semantic web technologies for solving today’s urban challenges. Hopefully creating a foundation for the Semantic Digital Twins of the future. Figure 1: Example of high level-of-detail in Neo Dash Figure 2: Example of Energy Poverty analysis enabled by Neo Dash data integration. The figure highlights the exact buildings where Energy Poverty might be an issue.