Web visualization dashboards are popular. We propose a system called RAIV that can capture and archive web visualizations into self-contained objects. RAIV also uses a client-server architecture to host and manage archived objects as online galleries, which users can use a standard web browser to experience without needing to install any additional software. RAIV supports intelligent search as well. When a search target has been found, RAIV can show the interaction path required to reach that target. We demonstrate RAIV’s capability using a genomics web visualization system called KnowEnG from NCSA and publicly available census data visualizations from US Census.
Hunter Price, John Duggan, Robert Sisneros, Tanner Hobson, James Hammer, James Osborne, Jian Huang, "RAIV: Researchable Archives for Interactive Visualizations" in Electronic Imaging, 2024, pp 362-1 - 362-10, https://doi.org/10.2352/EI.2024.36.1.VDA-362