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 over time. 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.

Automated summary

Temporal event sequence alignment is useful for visualizing nuanced changes and interactions over time in various domains. Sequence Braiding is a novel overview visualization method that visually aligns multiple temporal events and attribute groups simultaneously, supporting arbitrary ordering, absence, and duplication of events. Experiment results suggest that users of Sequence Braiding can understand high-level patterns and trends faster and with similar error rates compared to other methods.