Marjorie: Visualizing Type 1 Diabetes Data to Support Pattern Exploration
Anna Scimone, Klaus Eckelt, Marc Streit, Andreas Hinterreiter
DOI: 10.1109/TVCG.2023.3326936
Room: 105
2023-10-26T04:57:00ZGMT-0600Change your timezone on the schedule page
2023-10-26T04:57:00Z
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Keywords
Design study, task analysis, diabetes, time series data, visual analytics, clustering
Abstract
This work involves joint efforts between visualization and humanities researchers, aiming at building a holistic view of the cultural exchange and integration between China and Japan brought about by the overseas circulation of Chinese classics. Book circulation data consist of uncertain spatiotemporal trajectories, with multiple dimensions, and movement across hierarchical spaces forms a compound network. LiberRoad visualizes the circulation of books collected in the Imperial Household Agency of Japan, and can be generalized to other book movement data. The LiberRoad system enables a smooth transition between three views (Location Graph, map, and timeline) according to the desired perspectives (spatial or temporal), as well as flexible filtering and selection. The Location Graph is a novel uncertainty-aware visualization method that employs improved circle packing to represent spatial hierarchy. The map view intuitively shows the overall circulation by clustering and allows zooming into single book trajectory with lenses magnifying local movements. The timeline view ranks dynamically in response to user interaction to facilitate the discovery of temporal events. The evaluation and feedback from the expert users demonstrate that LiberRoad is helpful in revealing movement patterns and comparing circulation characteristics of different times and spaces.