Sequence Braiding: Visual Overviews of Temporal Event Sequences and Attributes

Temporal event sequence alignment has been used in many domains to visualize nuanced changes and interactions overtime. Existing approaches align one or two sentinel events. Overview tasks require examining all alignments of interest using interaction and time or juxtaposition of many visualizations...

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Bibliographic Details
Published in:IEEE transactions on visualization and computer graphics 2021-02, Vol.27 (2), p.1353-1363
Main Authors: Bartolomeo, Sara Di, Zhang, Yixuan, Sheng, Fangfang, Dunne, Cody
Format: Article
Language:English
Subjects:
algorithm
Blood
Data visualization
Diabetes
evaluation
Glucose
Insulin
network visualization
Task analysis
Temporal event sequence visualization
Visualization
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Summary:Temporal event sequence alignment has been used in many domains to visualize nuanced changes and interactions overtime. Existing approaches align one or two sentinel events. Overview tasks require examining all alignments of interest using interaction and time or juxtaposition of many visualizations. Furthermore, any event attribute overviews are not closely tied to sequence visualizations. We present SEQUENCE BRAIDING, a novel overview visualization for temporal event sequences and attributes using a layered directed acyclic network. SEQUENCE BRAIDING visually aligns many temporal events and attribute groups simultaneously and supports arbitrary ordering, absence, and duplication of events. In a controlled experiment we compare SEQUENCE BRAIDING and IDMVis on user task completion time, correctness, error, and confidence. Our results provide good evidence that users of SEQUENCE BRAIDING can understand high-level patterns and trends faster and with similar error. A full version of this paper with all appendices; the evaluation stimuli, data, and analysis code; and source code are available at osf.io/mq2wt.
ISSN:1077-2626
1941-0506
DOI:10.1109/TVCG.2020.3030442