Ogbonda, Ebube GloryRoberts, Jonathan C.Butcher, Peter W. S.Vangorp, PeterHunter, David2023-09-122023-09-122023978-3-03868-231-8https://doi.org/10.2312/cgvc.20231192https://diglib.eg.org:443/handle/10.2312/cgvc20231192In response to the escalating global refugee crisis, we present a case-study of developing an advanced tool for interpreting high-dimensional refugee data. Developed using Mapbox and D3.js, our interactive visualisation harmonises geographical and temporal dimensions of U.S. refugee data from the State Department's Refugee Processing Center. Our modular approach and robust data preprocessing enable seamless interactions among diverse visual components. The result is a narrative-driven visualisation that reveals broad immigration trends and individual refugee movements, fostering a nuanced and empathetic understanding of refugee dynamics. This work highlights the power of narrative visualisations in shaping policy decisions and promoting global discourse on the refugee crisis, marking a significant leap in data visualisation for refugee and immigration challenges.Attribution 4.0 International LicenseCCS Concepts: Human-centered computing -> Visualization design and evaluation methods; Visualization toolkits; Visual analyticsHuman centered computingVisualization design and evaluation methodsVisualization toolkitsVisual analytics10.2312/cgvc.2023119257-593 pages