Z: Why vis?

Node: Visualizations provide context

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Argumentative standpoint Design
Description

Visualizations can put information next to information that is needed for its understanding, both, within the visualization as well as within the scenario where the visualization is used.

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

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Incoming Links (2)

Publications (21)

F. J. Anscombe 1973 Graphs in Statistical Analysis 0 0 1 5 0
H. Wainer 1984 How to Display Data Badly 0 0 1 6 0
J. J. Thomas 2005 Illuminating the Path: The Research and Development Agenda for Visual Analytics 0 1 0 13 0
J. S. Yi et al. 2007 Toward a Deeper Understanding of the Role of Interaction in Information Visualization 0 0 1 3 3
A. C. Telea 2008 Data visualization - principles and practice 0 1 0 9 2
H. C. Purchase et al. 2008 Theoretical Foundations of Information Visualization 0 0 1 9 0
C. Ziemkiewicz and R. Kosara 2008 The Shaping of Information by Visual Metaphors 0 0 1 3 0
M. Chen and H. Jaenicke 2010 An Information-Theoretic Framework for Visualization 0 0 1 9 0
K. Hornbæk and M. Hertzum 2011 The notion of overview in information visualization 0 0 1 5 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
M. Correll and M. Gleicher 2014 Bad for Data, Good for the Brain : Knowledge-First Axioms For Visualization Design 0 0 1 6 0
H. C. Purchase 2014 Twelve Years of Diagrams Research 0 0 1 16 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
K. Cook et al. 2015 Mixed-Initiative Visual Analytics Using Task-Driven Recommendations 0 0 1 9 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
E. Dimara, A. Bezerianos and P. Dragicevic 2017 The Attraction Effect in Information Visualization 0 0 1 10 0
Authors Year Title Codings Coded entities
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Codings (22)

Streeb, Dirk: J. S. Yi et al. [2007]: Toward a Deeper Understanding of the Role of Interaction in Information Visualization doi:10.1109/TVCG.2007.70515 - 20.03.18 09:43 (+) Positive Less than a sentence sec. 4.5 …provide very similar functionality by allowing particular sub-trees in a hierarchy to be examined more closely without losing context of the entire structure.
Streeb, Dirk: J. T. Stasko [2014]: Value-Driven Evaluation of Visualizations doi:10.1145/2669557.2669579 - 19.03.18 10:16 (+) Positive One or more paragraphs sec. 3 An effective visualization should convey information about the totality of data being presented, effectively the “big picture.”
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 (+) Positive One or more sentences p. 7 Finally, it has been shown that visual aids are most effective for comprehension when the entire population at risk is shown rather than only depicting sick people, for instance.
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 (-) Negative One or more sentences p. 8 When web-users were shown survival graphs for a hypothetical disease and treatment, they based their perceptions of treatment effectiveness on visual differences in these graphs. When a longer duration of data was shown, people perceived larger differences in risk even when the magnitude of risk reduction was identical.
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 Less than a sentence p. 56 …though tick marks, labels, and axes are often essential for appropriate identification.
Streeb, Dirk: J. J. Thomas [2005]: Illuminating the Path: The Research and Development Agenda for Visual Analytics isbn:0-7695-2323-4 - 08.03.18 09:07 (+) Positive One or more sentences p. 30 Visual analytics must build upon this research base to create visual representations that instantly convey the important content of information, within context.
Streeb, Dirk: H. Wainer [1984]: How to Display Data Badly doi:10.1080/00031305.1984.10483186 - 02.03.18 12:48 (+) Positive One or more sentences p. 141 The Times' alternative provides the context for a deeper understanding.
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. 209 This conclusion is underscored by a number of studies that have shown that visual identification and visual search are enhanced by the presence of a visual context relative to isolated stimuli, especially visual contexts that have meaning.
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 Less than a sentence p. 4 …provide more contextual information…
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 They are presented to the user on the Canvas in the context of the user’s ongoing analysis
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 p. 6 Moreover, the visual support can provide additional information that may not be explicitly requested by the question but that can open broader perspectives on the studied problem.
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: 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: C. Ziemkiewicz and R. Kosara [2008]: The Shaping of Information by Visual Metaphors doi:10.1109/TVCG.2008.171 - 26.01.18 08:30 (+) 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: K. Hornbæk and M. Hertzum [2011]: The notion of overview in information visualization doi:10.1016/j.ijhcs.2011.02.007 - 25.01.18 16:17 (++) Central positive
Streeb, Dirk: M. Correll and M. Gleicher [2014]: Bad for Data, Good for the Brain : Knowledge-First Axioms For Visualization Design - 25.01.18 16:14 (+) 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: H. C. Purchase [2014]: Twelve Years of Diagrams Research doi:10.1016/j.jvlc.2013.11.004 - 25.01.18 13:46 (+) Positive
Streeb, Dirk: F. J. Anscombe [1973]: Graphs in Statistical Analysis doi:10.2307/2682899 - 25.01.18 13:44 (+) Positive
Streeb, Dirk: M. Chen and H. Jaenicke [2010]: An Information-Theoretic Framework for Visualization doi:10.1109/TVCG.2010.132 - 25.01.18 13:38 (+) Positive
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