Stacked Graphs – Geometry & Aesthetics

By Lee Byron, Martin Wattenberg. IEEE Transactions on Visualization and Computer Graphics, 2008

423 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Human-Computer Interaction, Signal Processing

View Paper: https://www.semanticscholar.org/paper/29a1b10bae922ccb6a2d3f40958bcc1b70c5fbc1

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

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In Signal Processing

Citations in the corpus

EvoRiver: Visual Analysis of Topic Coopetition on Social Media (2014, background): “Stacked graphs can simultaneously visualize time series individually and collectively [9].”
Ambient affiliation: A linguistic perspective on Twitter (2011, background): “StreamGraphs are an example of a text visualization technique that does not efface logogenesis, the unfolding of text over time (Zappavigna, forthcoming).”
Crowd sensing of traffic anomalies based on human mobility and social media (2013, methodology): “Our design is informed by work on stacked graphs [1], flow maps [10], and road network visualization [12].”
Hierarchical Aggregation for Information Visualization: Overview, Techniques, and Design Guidelines (2010, neutral): “Wattenberg [16] also studied esthetics and layout techni-”
Interactive Visual Profiling of Musicians (2016, background): “Often, streams express a temporal evolution of events [9, 16].”
Context preserving dynamic word cloud visualization (2010, neutral): “Other related work includes stacked graphs, which are useful visualization techniques for visual analysis of quantitative variations of a set of items over time [3, 11].”
Design Considerations for Optimizing Storyline Visualizations (2012, neutral): “Smoothing is a conventional and effective technique applied to many visualization systems [4, 14], and several researchers have also applied smoothing to improve the legibility of parallel coordinates.”
D³ Data-Driven Documents (2011, neutral): “The stack layout computes the y 0 baseline for stacked graphs [11, 4], while the squariﬁed treemap layout [31, 3] computes another spatial partition well-suited for animation (see § 5.1).”
An Efficient Framework for Generating Storyline Visualizations from Streaming Data (2015, neutral): “In summary, this experiment demonstrates our framework’s excellent capability to create legible storyline visualizations.”
Sizing the horizon: the effects of chart size and layering on the graphical perception of time series visualizations (2009, background): “Byron and Wattenberg [ 3 ] suggest sorting the stacks to mitigate this problem.”
Visual Analysis of Topic Competition on Social Media (2013, methodology): “, the bottom of the lowest layer) in the ThemeRiver is computed by minimizing the wiggles [7].”
Fluid interaction for information visualization (2011, background): “The data is represented as a set of stacked graphs [10], where the horizontal axis represents the time, and the vertical axis the amount of children that were given a certain name in the corresponding period.”
Protovis: A Graphical Toolkit for Visualization (2009, methodology): “We now present a pair of in-depth comparisons: a simple pie chart specification and the Job Voyager, an interactive stream graph [5].”
LineUp: Visual Analysis of Multi-Attribute Rankings (2013, methodology): “[30] uses stacked graphs [4] with augmented color bars and glyphs to compare rankings over time.”
VizLinter: A Linter and Fixer Framework for Data Visualization (2021, methodology): “Byron and Wattenberg present a wiggle-minimizing method to optimize the overall shapes of stacked graphs [12].”