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Semantic Snapping for Guided Multi-View Visualization Design

Yngve S. Kristiansen, Laura Garrison, Stefan Bruckner

View presentation: 2021-10-27T15:00:00Z GMT-0600 Change your timezone on the schedule page
Exemplar figure, described by caption below
Conceptual figure showing the semantic space with relations and operations for our semantic model. Operation 4 displays the homogenize operation which is available as a result of a multiples relation (the two axis scales are different, but should be the same if the underlying data represents the same quantity).
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Visual information displays are typically composed of multiple visualizations that are used to facilitate an understanding of the underlying data. A common example are dashboards, which are frequently used in domains such as finance, process monitoring and business intelligence. However, users may not be aware of existing guidelines and lack expert design knowledge when composing such multi-view visualizations. In this paper, we present semantic snapping, an approach to help non-expert users design effective multi-view visualizations from sets of pre-existing views. When a particular view is placed on a canvas, it is "aligned'' with the remaining views--not with respect to its geometric layout, but based on aspects of the visual encoding itself, such as how data dimensions are mapped to channels. Our method uses an on-the-fly procedure to detect and suggest resolutions for conflicting, misleading, or ambiguous designs, as well as to provide suggestions for alternative presentations. With this approach, users can be guided to avoid common pitfalls encountered when composing visualizations. Our provided examples and case studies demonstrate the usefulness and validity of our approach.