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However, data\u2010driven evidence about how historians actually use visualization remains scarce. We present a corpus\u2010driven, mixed\u2010methods 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\u2010automatic labeling pipeline. We construct a corpus of 14,021 images, classify 4,831 visualization instances using a hierarchical, domain\u2010informed 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 Hi\u2010FigAtlas system as a boundary object to support joint inspection of the corpus. We identify distinct roles for visualizations in historical research: primary\u2010source, evidence\u2010synthesis, 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\u2010specific needs.<\/jats:p>","DOI":"10.1111\/cgf.70468","type":"journal-article","created":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T10:53:23Z","timestamp":1781175203000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["How Historians Use Visualization: A Corpus\u2010Driven Mixed\u2010Methods Study"],"prefix":"10.1111","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-0700-4575","authenticated-orcid":false,"given":"X.","family":"Chen","sequence":"first","affiliation":[{"name":"National Key Laboratory of General Artificial Intelligence, School of Intelligence Science and Technology Peking University  China"},{"name":"PKU\u2010WUHAN Institute for Artificial Intelligence  China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9035-0463","authenticated-orcid":false,"given":"Y.","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Computer Science University of Oxford  UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-4209-9094","authenticated-orcid":false,"given":"W.","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Data Science Fudan University  China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-8612-2492","authenticated-orcid":false,"given":"C.","family":"Ma","sequence":"additional","affiliation":[{"name":"National Key Laboratory of General Artificial Intelligence, School of Intelligence Science and Technology Peking University  China"},{"name":"PKU\u2010WUHAN Institute for Artificial Intelligence  China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7233-980X","authenticated-orcid":false,"given":"X.","family":"Yuan","sequence":"additional","affiliation":[{"name":"National Key Laboratory of General Artificial Intelligence, School of Intelligence Science and Technology Peking University  China"},{"name":"PKU\u2010WUHAN Institute for Artificial Intelligence  China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,6,11]]},"reference":[{"key":"e_1_2_12_2_2","doi-asserted-by":"publisher","DOI":"10.1080\/01615440.2025.2527132"},{"key":"e_1_2_12_3_2","doi-asserted-by":"publisher","DOI":"10.1145\/3544548.3581168"},{"key":"e_1_2_12_4_2","volume-title":"Thematic Analysis: A Practical Guide","author":"Braun V.","year":"2021"},{"key":"e_1_2_12_5_2","unstructured":"BaiS. 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