VisTaxa: Developing a Taxonomy of Historical Visualizations
Historical visualizations are a rich resource for visualization research. While taxonomy is commonly used to structure and understand the design space of visualizations, existing taxonomies primarily focus on contemporary visualizations and largely overlook historical visualizations. To address this gap, we describe an empirical method for taxonomy development. We introduce a coding protocol and the VisTaxa system for taxonomy labeling and comparison. We demonstrate using our method to develop a historical visualization taxonomy by coding 400 images of historical visualizations. We analyze the coding result and reflect on the coding process. Our work is an initial step toward a systematic investigation of the design space of historical visualizations.
Authors
- X. T. Chen (ORCID: https://orcid.org/0009-0006-0700-4575)
- Yuhan Guo (ORCID: https://orcid.org/0009-0004-3857-7486)
- Xiaoru Yuan (ORCID: https://orcid.org/0000-0002-7233-980X)
- Yu Zhang (ORCID: https://orcid.org/0000-0002-9035-0463)
- Guozheng Li (ORCID: https://orcid.org/0000-0001-6663-6712)
- Siming Chen (ORCID: https://orcid.org/0000-0002-2690-3588)
- Weili Zheng (ORCID: https://orcid.org/0009-0000-4209-9094)
Institutions
- Beijing Institute of Technology (CN)
- Fudan University (CN)
- University of Oxford (GB)
- Beijing Academy of Artificial Intelligence (CN)
Publication Details
- Journal
- IEEE Transactions on Visualization and Computer Graphics
- Published
- 2025-05-06
- DOI
- https://doi.org/10.1109/tvcg.2025.3567132
- Citations
- 1
- Primary Topic
- Data Visualization and Analytics
- Type
- article
- Field-Weighted Citation Impact
- 1.28