Many-to-Many Geographically-Embedded Flow Visualisation: An Evaluation
August 06, 2019 ยท Declared Dead ยท ๐ IEEE Transactions on Visualization and Computer Graphics
"No code URL or promise found in abstract"
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Authors
Yalong Yang, Tim Dwyer, Sarah Goodwin, Kim Marriott
arXiv ID
1908.02052
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.GR,
cs.MM
Citations
92
Venue
IEEE Transactions on Visualization and Computer Graphics
Last Checked
2 months ago
Abstract
Showing flows of people and resources between multiple geographic locations is a challenging visualisation problem. We conducted two quantitative user studies to evaluate different visual representations for such dense many-to-many flows. In our first study we compared a bundled node-link flow map representation and OD Maps [37] with a new visualisation we call MapTrix. Like OD Maps, MapTrix overcomes the clutter associated with a traditional flow map while providing geographic embedding that is missing in standard OD matrix representations. We found that OD Maps and MapTrix had similar performance while bundled node-link flow map representations did not scale at all well. Our second study compared participant performance with OD Maps and MapTrix on larger data sets. Again performance was remarkably similar.
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