Z: Why vis?

Node: Visualizations are augmented with knowledge

Descriptor KnowledgeAugmentation
Argumentative standpoint Cognition
Description

Viewers can augment a visualization with their contextual knowledge.

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

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Outgoing Links (2)

Incoming Links (3)

Publications (14)

F. J. Anscombe 1973 Graphs in Statistical Analysis 0 0 1 5 0
S. M. Kosslyn 1989 Understanding Charts and Graphs 0 1 0 13 0
J. J. van Wijk 2005 The Value of Visualization 0 0 1 6 0
A. C. Telea 2008 Data visualization - principles and practice 0 1 0 9 2
M. Chen and H. Jaenicke 2010 An Information-Theoretic Framework for Visualization 0 0 1 9 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
A. Gelman and A. Unwin 2013 Infovis and Statistical Graphics: Different Goals, Different Looks 0 0 1 21 2
E. Dimara, P. Dragicevic and A. Bezerianos 2014 Accounting for Availability Biases in Information Visualization 0 0 1 5 0
T. Tenbrink 2014 Cognitive Discourse Analysis for Cognitively Supportive Visualisations 0 0 1 8 0
M. T. McCrudden and D. N. Rapp 2015 How Visual Displays Affect Cognitive Processing 0 0 1 19 0
M. Chen and A. Golan 2016 What May Visualization Processes Optimize? 0 0 1 10 0
N. Kijmongkolchai, A. Abdul-Rahman and M. Chen 2017 Empirically Measuring Soft Knowledge in Visualization 0 0 1 9 0
B. Alper et al. 2017 Visualization Literacy at Elementary School 0 0 1 10 0
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Codings (14)

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. 191 Once information in a display is in short-term memory, it can be encoded into long-term memory. That is, it can be compared against previously stored information and categorized. Once categorized, one knows more about the stimulus than is apparent in the input itself. Factors that affect this process affect our ability to extract meaning from the display.
Streeb, Dirk: M. Chen and A. Golan [2016]: What May Visualization Processes Optimize? doi:10.1109/TVCG.2015.2513410 - 04.03.18 10:31 (+) Positive One or more sentences sec. 1 The input to the transformation may also include “soft” information and knowledge, such as known theories, intuition, belief, value judgment, and so on.
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. 454 Understanding a graphic can also include making further inferences based on domain knowledge or visual-spatial processes (comparison, mental rotation, etc.) so that the resulting internal representation comes to contain information that is not presented explicitly in the external display.
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. 8 If they have a lot of background knowledge, they will view the graphic differently than if they rely only on the graphic and its surrounding text.
Streeb, Dirk: J. J. van Wijk [2005]: The Value of Visualization doi:10.1109/VISUAL.2005.1532781 - 25.02.18 13:35 (+-) Ambivalent One or more paragraphs sec. 4.4 This simply means that the increase in knowledge using visualization not only depends on the data itself, but also on the specification (for instance, which hardware has been used, which algorithm has been used and which parameters), the perceptual skills of the observer, and the a priori knowledge of the observer. Hence, the statement that visualization shows that a certain phenomenon occurs is doubtful and subjective.
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: 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: M. T. McCrudden and D. N. Rapp [2015]: How Visual Displays Affect Cognitive Processing doi:10.1007/s10648-015-9342-2 - 25.01.18 14:11 (++) Central positive
Streeb, Dirk: T. Tenbrink [2014]: Cognitive Discourse Analysis for Cognitively Supportive Visualisations - 25.01.18 13:58 (=) Neutral
Streeb, Dirk: B. Alper et al. [2017]: Visualization Literacy at Elementary School doi:10.1145/3025453.3025877 - 25.01.18 13:54 (+) 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
Streeb, Dirk: E. Dimara, P. Dragicevic and A. Bezerianos [2014]: Accounting for Availability Biases in Information Visualization - 25.01.18 13:35 (+) 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
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