Annogram: An Annotative Grammar Of Graphics Extension

Annogram: An Annotative Grammar Of Graphics Extension
Md Dilshadur Rahman, Md Rahat-uz- Zaman, Andrew M McNutt, and Paul Rosen
IEEE VIS Short Papers, 2025

Abstract

Annotations are central to effective data communication, yet most visualization tools treat them as secondary constructs — manually defined, difficult to reuse, and loosely coupled to the underlying visualization grammar. We propose a declarative extension to Wilkinson’s Grammar of Graphics that reifies annotations as first-class design elements, enabling structured specification of annotation targets, types, and positioning strategies. To demonstrate the utility of our approach, we develop a prototype extension called Vega-Lite Annotation. Through comparison with eight existing tools, we show that our approach enhances expressiveness, reduces authoring effort, and enables portable, semantically integrated annotation workflows.

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Citation

Md Dilshadur Rahman, Md Rahat-uz- Zaman, Andrew M McNutt, and Paul Rosen. Annogram: An Annotative Grammar Of Graphics Extension. IEEE VIS Short Papers, 2025.

Bibtex


@article{rahman2025annogram,
  title = {AnnoGram: An Annotative Grammar of Graphics Extension},
  author = {Rahman, Md Dilshadur and Zaman, Md Rahat-uz- and McNutt, Andrew M and Rosen,
    Paul},
  journal = {IEEE VIS Short Papers},
  year = {2025},
  abstract = {Annotations are central to effective data communication, yet most
    visualization tools treat them as secondary constructs -- manually defined, difficult to
    reuse, and loosely coupled to the underlying visualization grammar. We propose a
    declarative extension to Wilkinson's Grammar of Graphics that reifies annotations as
    first-class design elements, enabling structured specification of annotation targets,
    types, and positioning strategies. To demonstrate the utility of our approach, we
    develop a prototype extension called Vega-Lite Annotation. Through comparison with eight
    existing tools, we show that our approach enhances expressiveness, reduces authoring
    effort, and enables portable, semantically integrated annotation workflows.}
}