Temporal Summary Images: An Approach to Narrative Visualization via Interactive Annotation Generation and Placement

Visualization is a powerful technique for analysis and communication of complex, multidimensional, and time-varying data. However, it can be difficult to manually synthesize a coherent narrative in a chart or graph due to the quantity of visualized attributes, a variety of salient features, and the...

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Bibliographic Details
Published in:IEEE transactions on visualization and computer graphics 2017-01, Vol.23 (1), p.511-520
Main Authors: Bryan, Chris, Kwan-Liu Ma, Woodring, Jonathan
Format: Article
Language:English
Subjects:
Additives
Annotations
comic strip visualization
Context
Data analysis
Data visualization
Layout
Narrative visualization
storytelling
Strips
time-varying data
Visualization
Workflow
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Summary:Visualization is a powerful technique for analysis and communication of complex, multidimensional, and time-varying data. However, it can be difficult to manually synthesize a coherent narrative in a chart or graph due to the quantity of visualized attributes, a variety of salient features, and the awareness required to interpret points of interest (POls). We present Temporal Summary Images (TSIs) as an approach for both exploring this data and creating stories from it. As a visualization, a TSI is composed of three common components: (1) a temporal layout, (2) comic strip-style data snapshots, and (3) textual annotations. To augment user analysis and exploration, we have developed a number of interactive techniques that recommend relevant data features and design choices, including an automatic annotations workflow. As the analysis and visual design processes converge, the resultant image becomes appropriate for data storytelling. For validation, we use a prototype implementation for TSIs to conduct two case studies with large-scale, scientific simulation datasets.
ISSN:1077-2626
1941-0506
DOI:10.1109/TVCG.2016.2598876