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

Journal Article · Wed Aug 10 00:00:00 EDT 2016 · IEEE Transactions on Visualization and Computer Graphics

DOI:https://doi.org/10.1109/TVCG.2016.2598876· OSTI ID:1463548

Bryan, Chris ^[1]; Ma, Kwan-Liu ^[1]; Woodring, Jonathan ^[2]

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1. Univ. of California, Davis, CA (United States)
2. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

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 (POIs). 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.

• Research Organization: Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
• Sponsoring Organization: USDOE
• Grant/Contract Number: AC52-06NA25396
• OSTI ID: 1463548
• Report Number(s): LA-UR-17-27532
• Journal Information: IEEE Transactions on Visualization and Computer Graphics, Vol. 23, Issue 1; ISSN 1077-2626
• Publisher: IEEE
• Country of Publication: United States
• Language: English

Related Subjects

97 MATHEMATICS AND COMPUTING