How Historians Use Visualization: A Corpus-Backed Taxonomy and Analysis for Cross-Disciplinary Practice
This work provides the first large-scale, data-driven account of how historians use visualization, offering a taxonomy and analysis that can guide tool design and cross-disciplinary collaboration.
The authors analyzed 14,021 images from 4,142 research articles to create a taxonomy of visualization use in history, identifying five distinct roles (primary-source, evidence-synthesis, communicative, confirmative, exploratory) and finding that epistemological and practical barriers impede adoption.
Visualization in historical research is shifting from isolated attempts to systematic practices. However, data-driven evidence about how historians actually use visualization remains scarce. We present a corpus-driven, mixed-methods study that combines analysis of images from 4,142 research articles across history and digital humanities journals with a collaboratively developed visualization taxonomy and a semi-automatic labeling pipeline. We construct a corpus of 14,021 images, classify 4,831 visualization instances using a hierarchical, domain-informed taxonomy, and analyze patterns of visualization adoption across venues, history subfields, and time. To interpret these patterns, we conduct interviews with 11 historians and use HiFigAtlas system as a boundary object to support joint inspection of the corpus. We identify distinct roles for visualizations in historical research: primary-source, evidence-synthesis, communicative, confirmative, and exploratory. We further find that while historians pursue diverse goals with figures, persistent epistemological and practical barriers, such as uncertainty, provenance, justification burden, and publication constraints, impede the adoption of visualization. This work contributes a grounded account of visualization use in historical scholarship and points to opportunities to better support domain-specific needs.