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An Emotional Response to the Value of Visualization
IEEE Computer Graphics and Applications
|August 24, 2019
Summary
Data visualization value traditionally focuses on efficiency and insight. This study argues for including hedonic qualities, like emotion and aesthetics, in assessing visualization value for broader applications.
Area of Science:
- Information Visualization
- Human-Computer Interaction
- Data Science
Background:
- Traditional data visualization research prioritizes efficiency, comprehension, and insight.
- Successful data physicalizations highlight the importance of hedonic (pleasure-based) qualities.
- Emotion plays a significant role in psychology, art, design, marketing, and HCI.
Purpose of the Study:
- To propose an expanded definition of value for data visualization.
- To incorporate hedonic qualities into the assessment of visualization value.
- To provide a framework applicable to all data visualization forms.
Main Methods:
- Literature review across psychology, art, design, marketing, and HCI.
- Analysis of successful data physicalizations.
- Theoretical argument for expanded value metrics.
Main Results:
- Hedonic qualities are crucial for successful data physicalizations.
- Existing value metrics for data visualization are incomplete.
- An expanded definition of value is necessary.
Conclusions:
- Data visualization value should encompass hedonic qualities alongside traditional metrics.
- Considering emotion and aesthetics enhances visualization's impact and engagement.
- This expanded definition offers a more holistic approach to evaluating data visualization effectiveness.
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