Data visualization has surfaced as an essential journalistic practice for conveying complex quantitative information in print and digital media. While existing scholarship predominantly examines data journalism within digital newsrooms, the long-term evolution of visual data artifacts in traditional newsprint media persists under-researched, particularly in Central Asia. To address this gap, this study examines the quantitative growth, structural typology, and functional transformation of data visualization in Kazakhstani print media through a ten-year diachronic content analysis of the national socio-political weekly newspaper Jas Qazaq (2016–2025). Based on an extensive review of 466 published newspaper issues, an empirical dataset of N = 1,090 visual data artifacts was categorized across four main graphic topographies: frequently appearing stock-market symbols (42.8%), statistical tables, maps, and seismograms (21.7%), prominent numerical snapshots (18.9%), and thematic infographics (16.6%).The evidence indicates 84.7% over time increase in extent of the visual data (expanding from 72 units in 2016 to 133 units in 2025), demonstrating the consistent institutionalization of data visualization as a constant newsprint standard. Qualitatively, the editorial workflow transitioned from basic numerical decoration to complex crisis communication during major national emergencies (e.g., the COVID-19 pandemic, Almaty earthquake, spring floods). The study defines a region-specific print data journalism model, providing a theoretical framework for how print newsrooms structure visual information to reduce potential audience mental strains.
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Abdikhalyk et al. (2026) studied this question.
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