Semiology of Graphics - Diagrams, Networks, Maps

By J. Bertin, W. J. Berg. 2010

1,230 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/22be1cebc94d9eedc2cc6c000bee5222a37a9fd0

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Citations in the corpus

Stacking-Based Visualization of Trajectory Attribute Data (2012, methodology): “We rely on color because it is a widely accepted approach, it fits well with the trajectory band design, and it is both selective and associative [9] and therefore can support very well elementary and synoptic tasks.”
VizLinter: A Linter and Fixer Framework for Data Visualization (2021, background): “In the interviews, the experts noted that creating a visualization requires specifying marks and channels, the two primary components of visual encoding [7].”
The “Physics” of Notations: Toward a Scientific Basis for Constructing Visual Notations in Software Engineering (2009, background): “Research in psychophysics has established discrimin-ability thresholds for most visual variables, which can be used to guide choice of values [8], [126], [127].”
Bubble Sets: Revealing Set Relations with Isocontours over Existing Visualizations (2009, background): “…we perceive visualizations indicates that the spatial positioning of data items may be the most salient of the possible visual encodings such as position, colour, shape, etc. [3] [21], it may well be important to preserve positioning of data items while providing set membership visual containers.”
Guidance for representing uncertainty on global temperature change maps (2016, background): “Bertin’s system of visual variables is probably the most widely used, and includes location, size, lightness, grain/texture, colour (primarily hue), orientation, and shape (Bertin, 1983).”
When (ish) is My Bus?: User-centered Visualizations of Uncertainty in Everyday, Mobile Predictive Systems (2016, background): “Many other abstract, static representations encode a predictive distribution's probability density function (PDF) intrinsically as retinal variables (e.g., color, shape, texture) [3].”
Voyager 2: Augmenting Visual Analysis with Partial View Specifications (2017, methodology): “APT then uses a logic program that codiﬁes a set of expressiveness and effectiveness criteria inspired by Bertin [3] and Cleveland [7] to prune and rank visualizations.”
Termite: visualization techniques for assessing textual topic models (2012, background): “Matrix views can surface relationships among a large number of items [2, 14] or between two data dimensions [9] if an appropriate ordering (or seriation) is applied [10, 26].”
Vega-Lite: A Grammar of Interactive Graphics (2018, background): “Voyager leverages perceptual effectiveness criteria [2, 8, 16] to rank candidate visual encodings.”
Visualization Rhetoric: Framing Effects in Narrative Visualization (2011, background): “Researchers seek to better understand " framing effects " , situations where often small changes in the presentation of an issue or an event, such as slight modifications of phrasing, produce measurable changes of opinion [35].”
Visual Semiotics & Uncertainty Visualization: An Empirical Study (2012, background): “The concept of visual variables was originally outlined by Bertin (under the label of " retinal variables " ) in 1967 and made available in an English translation in 1983 [28].”
Voyager: Exploratory Analysis via Faceted Browsing of Visualization Recommendations (2016, unknown): “It then applies a set of expressiveness and effectiveness criteria based on the work of Bertin [4] and Cleveland [8] to prune and rank the set of visualizations.”
Situation Awareness-Based Agent Transparency (2014, unknown): “At the very fundamental, bottom-up level, Bertin (1983) attempted to create a classification structure for the various symbolic elements that result in responses from the visual system, which he denoted as marks.”
VLAT: Development of a Visualization Literacy Assessment Test (2017, background): “They defined graph comprehension as reading and interpreting a graph [24], and they proposed the three levels of graph comprehension framework [7] [13] [49]: (1) the first level is the elementary level in which a graph reader can read a specific value in a graph (e.g., a graph reader is able to…”
The Cognitive Science of Visual-Spatial Displays: Implications for Design (2011, methodology): “…science to display design The design of visual displays is often based on intuitions, approaches that analyze the basic dimensions or ''visual variables'' that make up visual-spatial displays (e.g., Bertin, 1983), or deriving principles from examples of good and poor graphics (e.g., Tufte, 2001).”
Analysis of biomedical data with multilevel glyphs (2014, background): “Berg), provides the foundation for the analysis of visual elements to display qualitative or quantitative data [5].”