Z: Why vis?

Node: Visualizations show visual patterns

Descriptor VisualPatterns
Argumentative standpoint Interplay
Description

Visualization unveils structures. Usually very fuzzy concept that describes how viewers see structures emerging from the compilation of objects in a visualization. Often Gestalt-psychology is used as a low level theory to explain the perception of visual pattern.

Last updated 3 years ago (June 22, 2018) by Streeb, Dirk

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Publications (44)

F. J. Anscombe 1973 Graphs in Statistical Analysis 0 0 1 5 0
W. S. Cleveland and R. McGill 1984 Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods 0 0 1 5 0
W. S. Cleveland and R. McGill 1985 Graphical Perception and Graphical Methods for Analyzing Scientific Data 0 0 1 5 0
J. H. Larkin and H. A. Simon 1987 Why a Diagram is (Sometimes) Worth Ten Thousand Words 0 0 1 11 0
S. M. Kosslyn 1989 Understanding Charts and Graphs 0 1 0 13 0
S. M. Kosslyn 1994 Elements of Graph Design 0 1 0 8 2
S. K. Card, J. D. Mackinlay and B. Shneiderman 1999 Readings in Information Visualization – Using Vision to Think 0 1 1 18 4
S. Bertschi and N. Bubenhofer 2005 Linguistic Learning: A New Conceptual Focus in Knowledge Visualization 0 0 1 18 0
J. J. van Wijk 2005 The Value of Visualization 0 0 1 6 0
S. M. Kosslyn 2006 Graph Design for the Eye and Mind 0 1 0 11 0
A. C. Telea 2008 Data visualization - principles and practice 0 1 0 9 2
Z. Liu, N. J. Nersessian and J. T. Stasko 2008 Distributed Cognition as a Theoretical Framework for Information Visualization 0 0 1 8 0
H. C. Purchase et al. 2008 Theoretical Foundations of Information Visualization 0 0 1 9 0
J. Fekete et al. 2008 The Value of Information Visualization 0 0 1 12 0
P. Hanrahan 2009 Systems of Thought 0 0 1 9 0
C. Ziemkiewicz and R. Kosara 2010 Beyond Bertin: Seeing the Forest despite the Trees 0 0 1 6 0
S. I. Fabrikant, S. R. Hespanha and M. Hegarty 2010 Cognitively Inspired and Perceptually Salient Graphic Displays for Efficient Spatial Inference Making 0 0 1 8 0
H. Wickham et al. 2010 Graphical Inference for Infovis 0 0 1 1 0
D. A. Keim et al. 2010 Mastering the Information Age Solving Problems with Visual Analytics 0 1 0 17 2
Z. Liu and J. T. Stasko 2010 Mental Models, Visual Reasoning and Interaction in Information Visualization: A Top-down Perspective 0 0 1 5 0
D. C. Gooding 2010 Visualizing Scientific Inference 0 0 1 21 0
M. Hegarty 2011 The Cognitive Science of Visual-Spatial Displays: Implications for Design 0 0 1 25 4
B. Tversky 2011 Visualizing Thought 0 0 1 36 0
D. J. Spiegelhalter, M. Pearson and I. Short 2011 Visualizing Uncertainty About the Future 0 0 1 8 0
J. Walny et al. 2011 Visual Thinking in Action: Visualizations as Used on Whiteboards 0 0 1 10 0
R. E. Patterson 2012 Cognitive Engineering, Cognitive Augmentation, and Information Display 0 0 1 9 2
A. Gelman and A. Unwin 2013 Infovis and Statistical Graphics: Different Goals, Different Looks 0 0 1 21 2
L. J. Trevena et al. 2013 Presenting Quantitative Information about Decision Outcomes: A Risk Communication Primer for Patient Decision Aid Developers 0 0 1 13 0
R. E. Patterson et al. 2014 A Human Cognition Framework for Information Visualization 0 0 1 18 0
G. L. Kindlmann and C. E. Scheidegger 2014 An Algebraic Process for Visualization Design 0 0 2 13 0
T. Verbeiren, R. Sakai and J. Aerts 2014 A Pragmatic Approach to Biases in Visual Data Analysis 0 0 1 2 0
J. T. Stasko 2014 Value-Driven Evaluation of Visualizations 0 0 1 13 0
T. Munzner 2014 Visualization Analysis & Design 0 0 1 15 0
M. Chen, L. Floridi and R. Borgo 2014 What is Visualization Really for? 0 0 1 8 0
A. Abrahamsen and W. Bechtel 2015 Diagrams as Tools for Scientific Reasoning 0 0 1 9 0
K. Cook et al. 2015 Mixed-Initiative Visual Analytics Using Task-Driven Recommendations 0 0 1 9 0
M. O. Ward, G. G. Grinstein and D. A. Keim 2015[2010] Interactive Data Visualization: Foundations, Techniques, and Applications 0 1 0 6 0
L. Byrne, D. Angus and J. Wiles 2016 Acquired Codes of Meaning in Data Visualization and Infographics: Beyond Perceptual Primitives 0 0 1 8 0
D. A. Szafir et al. 2016 Four Types of Ensemble Coding in Data Visualizations 0 0 1 10 0
P. C. Cheng 2016 What Constitutes an Effective Representation? 0 0 1 14 0
X. Chen et al. 2017 A Cognitive Model of How People Make Decisions Through Interaction with Visual Displays 0 0 1 10 0
A. Dasgupta et al. 2017 Empirical Analysis of the Subjective Impressions and Objective Measures of Domain Scientists’ Visual Analytic Judgments 0 0 1 9 0
N. Kijmongkolchai, A. Abdul-Rahman and M. Chen 2017 Empirically Measuring Soft Knowledge in Visualization 0 0 1 9 0
E. Dimara, A. Bezerianos and P. Dragicevic 2017 The Attraction Effect in Information Visualization 0 0 1 10 0
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Codings (46)

Streeb, Dirk: S. M. Kosslyn [1989]: Understanding Charts and Graphs doi:10.1002/acp.2350030302 - 09.07.20 06:59 (+) Positive One or more sentences p. 195 In addition, good displays should make use of easily seen patterns, exploiting our ability to apprehend changes in slope, groupings and the like.
Streeb, Dirk: J. T. Stasko [2014]: Value-Driven Evaluation of Visualizations doi:10.1145/2669557.2669579 - 19.03.18 10:16 (+) Positive Less than a sentence sec. 2 …engaging people’s strong pattern matching abilities…
Streeb, Dirk: L. J. Trevena et al. [2013]: Presenting Quantitative Information about Decision Outcomes: A Risk Communication Primer for Patient Decision Aid Developers doi:10.1186/1472-6947-13-S2-S7 - 19.03.18 07:22 (+-) Ambivalent One or more sentences p. 6 Thus, a potential weakness of visual displays is that people may focus more on the pattern of data rather than the precise values, unless that is the main objective.
Streeb, Dirk: W. S. Cleveland and R. McGill [1985]: Graphical Perception and Graphical Methods for Analyzing Scientific Data doi:10.1126/science.229.4716.828 - 18.03.18 11:39 (+) Positive One or more sentences p. 828 …much of the power of graphs—and what distinguishes them from tables—comes from the ability of our preattentive visual system to detect geometric patterns and assess magnitudes.
Streeb, Dirk: C. Ziemkiewicz and R. Kosara [2010]: Beyond Bertin: Seeing the Forest despite the Trees doi:doi.ieeecomputersociety.org/10.1109/MCG.2010.83 - 18.03.18 10:26 (+) Positive One or more sentences p. 7 They all arise instead from combinations of visual objects or from the viewer’s impression of the visualization’s overall structure.
Streeb, Dirk: H. C. Purchase et al. [2008]: Theoretical Foundations of Information Visualization doi:10.1007/978-3-540-70956-5_3 - 12.03.18 10:35 (+) Positive One or more paragraphs p. 48 Such an abstraction is based on a holistic grasp of characteristic features embracing multiple data items. We shall use the term “pattern” to refer to such features.
Streeb, Dirk: D. A. Keim et al. [2010]: Mastering the Information Age Solving Problems with Visual Analytics isbn:978-3-905673-77-7 - 10.03.18 14:06 (+) Positive One or more sentences p. 114 Ware describes this as visual queries - the search for patterns in the outside world. This capacity of human information processing is very flexible and adaptive.
Streeb, Dirk: H. Wickham et al. [2010]: Graphical Inference for Infovis doi:10.1109/TVCG.2010.161 - 10.03.18 13:22 (+-) Ambivalent Basically all of the publication p. 973 It allows us to uncover new findings, while controlling for apophenia, the innate human ability to see pattern in noise.
Streeb, Dirk: S. M. Kosslyn [2006]: Graph Design for the Eye and Mind isbn:978-0-19-531184-6 - 03.03.18 13:12 (+) Positive One or more sentences p. 18 Although we can consider only about four groups at a time, we can absorb much more information if it is translated into visual patterns.
Streeb, Dirk: S. M. Kosslyn [2006]: Graph Design for the Eye and Mind isbn:978-0-19-531184-6 - 03.03.18 13:12 (+) Positive One or more sentences p. 10
Streeb, Dirk: M. O. Ward, G. G. Grinstein and D. A. Keim [2015[2010]]: Interactive Data Visualization: Foundations, Techniques, and Applications isbn:978-1-4822-5737-3 - 03.03.18 12:15 (+) Positive Less than a sentence p. 6 …help describe some structure, patterns or anomaly in the data.
Streeb, Dirk: M. Hegarty [2011]: The Cognitive Science of Visual-Spatial Displays: Implications for Design doi:10.1111/j.1756-8765.2011.01150.x - 02.03.18 13:46 (+) Positive One or more sentences p. 447 …have developed around questions of how to best use new information technologies to reveal patterns in complex data sets.
Streeb, Dirk: Z. Liu, N. J. Nersessian and J. T. Stasko [2008]: Distributed Cognition as a Theoretical Framework for Information Visualization doi:10.1109/TVCG.2008.121 - 02.03.18 08:41 (+) Positive One or more sentences sec. 2 Hutchins puts it this way: “tools permit us to transform difficult tasks into ones that can be done by pattern matching, by the manipulation of simple physical systems, or by mental simulations of manipulations of simple physical systems. Tools are useful precisely because the cognitive processes required to manipulate them are not the computational processes accomplished by their manipulation.”
Streeb, Dirk: R. E. Patterson [2012]: Cognitive Engineering, Cognitive Augmentation, and Information Display doi:10.1889/JSID20.4.208 - 28.02.18 12:20 (+) Positive One or more paragraphs p. 210 Pattern recognition refers to the recognition of patterns formed from statistical regularities encountered in the environment (or on artificial displays).
Streeb, Dirk: A. Gelman and A. Unwin [2013]: Infovis and Statistical Graphics: Different Goals, Different Looks doi:10.1080/10618600.2012.761137 - 27.02.18 16:15 (+) Positive One or more sentences p. 7 Giving an overview—a qualitative sense of what is in a dataset, checking assumptions, confirming known results, and looking for distinct patterns.
Streeb, Dirk: J. Fekete et al. [2008]: The Value of Information Visualization doi:10.1007/978-3-540-70956-5_1 - 26.02.18 12:44 (+) Positive One or more sentences p. 4 if vision perceives some pattern, there might be a pattern in the data that reveals a structure.
Streeb, Dirk: J. J. van Wijk [2005]: The Value of Visualization doi:10.1109/VISUAL.2005.1532781 - 25.02.18 13:35 (+) Positive Less than a sentence sec. 1 …thanks to the unique capabilities of the human visual system, which enables us to detect interesting features and patterns in short time.
Streeb, Dirk: K. Cook et al. [2015]: Mixed-Initiative Visual Analytics Using Task-Driven Recommendations doi:10.1109/VAST.2015.7347625 - 25.02.18 12:14 (+) Positive One or more sentences sec. 5.1 These visual thumbnails help draw attention to patterns or anomalies.
Streeb, Dirk: S. K. Card, J. D. Mackinlay and B. Shneiderman [1999]: Readings in Information Visualization – Using Vision to Think isbn:978-1-55860-533-6 - 06.02.18 12:59 (+) Positive One or more sentences p. 1 …automatically assemble thousands of data objects into pictures, revealing hidden patterns.
Streeb, Dirk: A. C. Telea [2008]: Data visualization - principles and practice isbn:978-1-56881-306-6 - 05.02.18 09:46 (+) Positive One or more sentences pp. 5-6 A typical answer to this question would involve the discovery of patterns that have particular characteristics in terms of shape, position. or data values, which a human expert such as a medical doctor would classify as anomalous, based on his previous clinical experience.
Streeb, Dirk: S. M. Kosslyn [1994]: Elements of Graph Design isbn:0-7167-2263-1 - 01.02.18 12:04 (+-) Ambivalent One or more subsections pp. 7-8 Our visual system and memory system tend to make a direct connection between the properties of a pattern and the properties of the entities symbolized by that pattern.
Streeb, Dirk: Z. Liu and J. T. Stasko [2010]: Mental Models, Visual Reasoning and Interaction in Information Visualization: A Top-down Perspective doi:10.1109/TVCG.2010.177 - 26.01.18 09:45 (+) Positive
Streeb, Dirk: S. K. Card, J. D. Mackinlay and B. Shneiderman [1999]: Readings in Information Visualization – Using Vision to Think isbn:978-1-55860-533-6 - 26.01.18 09:43 (+) Positive
Streeb, Dirk: J. Walny et al. [2011]: Visual Thinking in Action: Visualizations as Used on Whiteboards doi:10.1109/TVCG.2011.251 - 26.01.18 09:35 (+) Positive
Streeb, Dirk: J. H. Larkin and H. A. Simon [1987]: Why a Diagram is (Sometimes) Worth Ten Thousand Words doi:10.1111/j.1551-6708.1987.tb00863.x - 26.01.18 09:05 (+) Positive
Streeb, Dirk: A. Abrahamsen and W. Bechtel [2015]: Diagrams as Tools for Scientific Reasoning doi:10.1007/s13164-014-0215-2 - 26.01.18 08:57 (+) Positive
Streeb, Dirk: M. Chen, L. Floridi and R. Borgo [2014]: What is Visualization Really for? doi:10.1007/978-3-319-07121-3_5 - 26.01.18 08:53 (+) Positive
Streeb, Dirk: P. C. Cheng [2016]: What Constitutes an Effective Representation? doi:10.1007/978-3-319-42333-3_2 - 26.01.18 08:39 (+) Positive
Streeb, Dirk: T. Munzner [2014]: Visualization Analysis & Design isbn:978-1-4665-0891-0 - 26.01.18 08:25 (+) Positive
Streeb, Dirk: L. Byrne, D. Angus and J. Wiles [2016]: Acquired Codes of Meaning in Data Visualization and Infographics: Beyond Perceptual Primitives doi:10.1109/TVCG.2015.2467321 - 25.01.18 16:19 (+) Positive
Streeb, Dirk: E. Dimara, A. Bezerianos and P. Dragicevic [2017]: The Attraction Effect in Information Visualization doi:10.1109/TVCG.2016.2598594 - 25.01.18 15:56 (+) Positive
Streeb, Dirk: T. Verbeiren, R. Sakai and J. Aerts [2014]: A Pragmatic Approach to Biases in Visual Data Analysis - 25.01.18 15:54 (+) Positive
Streeb, Dirk: G. L. Kindlmann and C. E. Scheidegger [2014]: An Algebraic Process for Visualization Design doi:10.1109/TVCG.2014.2346325 - 25.01.18 15:44 (+) Positive
Streeb, Dirk: B. Tversky [2011]: Visualizing Thought doi:10.1111/j.1756-8765.2010.01113.x - 25.01.18 15:25 (+) Positive
Streeb, Dirk: W. S. Cleveland and R. McGill [1984]: Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods doi:10.2307/2288400 - 25.01.18 15:21 (+) Positive
Streeb, Dirk: P. Hanrahan [2009]: Systems of Thought - 25.01.18 15:11 (+) Positive
Streeb, Dirk: A. Dasgupta et al. [2017]: Empirical Analysis of the Subjective Impressions and Objective Measures of Domain Scientists’ Visual Analytic Judgments doi:10.1145/3025453.3025882 - 25.01.18 15:09 (+) Positive
Streeb, Dirk: N. Kijmongkolchai, A. Abdul-Rahman and M. Chen [2017]: Empirically Measuring Soft Knowledge in Visualization doi:10.1111/cgf.13169 - 25.01.18 15:04 (+) Positive
Streeb, Dirk: X. Chen et al. [2017]: A Cognitive Model of How People Make Decisions Through Interaction with Visual Displays doi:10.1145/3025453.3025596 - 25.01.18 14:17 (+) Positive
Streeb, Dirk: R. E. Patterson et al. [2014]: A Human Cognition Framework for Information Visualization doi:10.1016/j.cag.2014.03.002 - 25.01.18 14:01 (+) Positive
Streeb, Dirk: D. J. Spiegelhalter, M. Pearson and I. Short [2011]: Visualizing Uncertainty About the Future doi:10.1126/science.1191181 - 25.01.18 13:51 (+) Positive
Streeb, Dirk: F. J. Anscombe [1973]: Graphs in Statistical Analysis doi:10.2307/2682899 - 25.01.18 13:44 (+) Positive
Streeb, Dirk: S. I. Fabrikant, S. R. Hespanha and M. Hegarty [2010]: Cognitively Inspired and Perceptually Salient Graphic Displays for Efficient Spatial Inference Making doi:10.1080/00045600903362378 - 25.01.18 13:41 (+) Positive
Streeb, Dirk: D. C. Gooding [2010]: Visualizing Scientific Inference doi:10.1111/j.1756-8765.2009.01048.x - 25.01.18 09:22 (+) Positive
Streeb, Dirk: S. Bertschi and N. Bubenhofer [2005]: Linguistic Learning: A New Conceptual Focus in Knowledge Visualization doi:10.1109/IV.2005.71 - 24.01.18 13:01 (+-) Ambivalent
Streeb, Dirk: D. A. Szafir et al. [2016]: Four Types of Ensemble Coding in Data Visualizations doi:10.1167/16.5.11 - 24.01.18 12:57 (+) Positive
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