A Survey on Annotations in Information Visualization: Empirical Studies, Applications and Challenges

Annotations are widely used in information visualization to guide attention, clarify patterns, and support interpretation. We present a comprehensive survey of 191 research articles describing empirical studies, tools, techniques, and systems that incorporate annotations across various visualization contexts. Based on a structured analysis, we characterize annotations by their types, generation methods, and targets, and examine their use across four primary application domains: user engagement, storytelling, collaboration, and exploratory data analysis. We also discuss key trends, practical challenges, and open research directions. These findings offer a foundation for designing more effective annotation systems and advancing future research on annotation in visualization.

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Publication Details

Journal
IEEE Transactions on Visualization and Computer Graphics
Published
2025-08-20
DOI
https://doi.org/10.1109/tvcg.2025.3600957
Citations
4
Primary Topic
Data Visualization and Analytics
Type
article
Field-Weighted Citation Impact
5.10
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article

A Survey on Annotations in Information Visualization: Empirical Studies, Applications and Challenges

Bhavana Doppalapudi, Ghulam Jilani Quadri, Paul Rosen, Md Dilshadur Rahman
4 citations
IEEE Transactions on Visualization and Computer Graphics
Data Visualization and Analytics
5.10
article

A Survey on Annotations in Information Visualization: Empirical Studies, Applications and Challenges

Bhavana Doppalapudi, Ghulam Jilani Quadri, Paul Rosen, Md Dilshadur Rahman
article en
4 citations

Abstract

Annotations are widely used in information visualization to guide attention, clarify patterns, and support interpretation. We present a comprehensive survey of 191 research articles describing empirical studies, tools, techniques, and systems that incorporate annotations across various visualization contexts. Based on a structured analysis, we characterize annotations by their types, generation methods, and targets, and examine their use across four primary application domains: user engagement, storytelling, collaboration, and exploratory data analysis. We also discuss key trends, practical challenges, and open research directions. These findings offer a foundation for designing more effective annotation systems and advancing future research on annotation in visualization.

IEEE Transactions on Visualization and Computer GraphicsVol. 31(12)
University of Utah (US), University of South Florida (US), University of Oklahoma (US)
Openalex Percentile: Top 4%
Data Visualization and Analytics
5.10
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