JOURNAL ARTICLE

User Selection Strategies of Interactive Data Visualization Format

Wenhong Luo

Year: 2022 Journal:   Journal of Computer Information Systems Vol: 63 (1)Pages: 81-93   Publisher: Taylor & Francis

Abstract

A key feature of interactive data visualization is the ability for users to choose the visualization formats and chart types. Some users may rely on their experience and gut feelings in selecting a visualization format while other users may evaluate the task characteristics and select a visualization format that fits better with task requirements. In this study, we examine the conditions under which users employ the experience or analytical strategies in selecting visualization format and the effects of the two strategies on decision accuracy and confidence. A laboratory study has been conducted to test the hypotheses. Our results show that more users employ the analytical strategy when confronted with incongruent cognitive style and task difficulty conditions and they were more confident about their decisions following the analytical strategy. The study helps us understand how interactive data visualizations can be utilized and identify areas for data visualization education and training.

Keywords:
Computer science Selection (genetic algorithm) Visualization Visual analytics Data visualization Human–computer interaction Interactive visualization Information visualization Information retrieval Data mining Artificial intelligence

Metrics

5
Cited By
0.62
FWCI (Field Weighted Citation Impact)
33
Refs
0.62
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Data Visualization and Analytics
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Spatial Cognition and Navigation
Physical Sciences →  Engineering →  Automotive Engineering

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