A Qualitative Analysis of Common Practices in Annotations: A Taxonomy and Design Space
June 09, 2023 ยท The Cartographer ยท ๐ IEEE Transactions on Visualization and Computer Graphics
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"Title-pattern auto-detect: A Qualitative Analysis of Common Practices in Annotations: A Taxonomy and Design Space"
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Authors
Md Dilshadur Rahman, Ghulam Jilani Quadri, Bhavana Doppalapudi, Danielle Albers Szafir, Paul Rosen
arXiv ID
2306.06043
Category
cs.HC: Human-Computer Interaction
Citations
19
Venue
IEEE Transactions on Visualization and Computer Graphics
Last Checked
2 days ago
Abstract
Annotations play a vital role in highlighting critical aspects of visualizations, aiding in data externalization and exploration, collaborative sensemaking, and visual storytelling. However, despite their widespread use, we identified a lack of a design space for common practices for annotations. In this paper, we evaluated over 1,800 static annotated charts to understand how people annotate visualizations in practice. Through qualitative coding of these diverse real-world annotated charts, we explored three primary aspects of annotation usage patterns: analytic purposes for chart annotations (e.g., present, identify, summarize, or compare data features), mechanisms for chart annotations (e.g., types and combinations of annotations used, frequency of different annotation types across chart types, etc.), and the data source used to generate the annotations. We then synthesized our findings into a design space of annotations, highlighting key design choices for chart annotations. We presented three case studies illustrating our design space as a practical framework for chart annotations to enhance the communication of visualization insights. All supplemental materials are available at {https://shorturl.at/bAGM1}.
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