A Survey On Annotations In Data Visualization: Empirical Insights And Applications
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A Survey On Annotations In Data Visualization: Empirical Insights And Applications |
Abstract
Annotations are widely used in information visualization to guide attention, clarify patterns, and support interpretation. We present a comprehensive survey of 191 research papers 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. An interactive web resource detailing the surveyed papers is available at https://shape-vis.github.io/annotation star/.
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Citation
Md Dilshadur Rahman, Bhavana Doppalapudi, Ghulam Jilani Quadri, and Paul Rosen. A Survey On Annotations In Data Visualization: Empirical Insights And Applications. To appear in IEEE Transactions on Computer Graphics and Visualization, 2025.
Bibtex
@article{rahman2025survey,
title = {A Survey on Annotations in Data Visualization: Empirical Insights and
Applications},
author = {Rahman, Md Dilshadur and Doppalapudi, Bhavana and Quadri, Ghulam Jilani and
Rosen, Paul},
journal = {To appear in IEEE Transactions on Computer Graphics and Visualization},
year = {2025},
abstract = {Annotations are widely used in information visualization to guide
attention, clarify patterns, and support interpretation. We present a comprehensive
survey of 191 research papers 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. An interactive web resource detailing the surveyed papers
is available at https://shape-vis.github.io/annotation star/.}
}



