{"id":19621,"date":"2025-09-05T20:53:12","date_gmt":"2025-09-05T20:53:12","guid":{"rendered":"https:\/\/www.anychart.com\/blog\/?p=19621"},"modified":"2025-09-13T10:08:34","modified_gmt":"2025-09-13T10:08:34","slug":"fresh-data-visualization-practices","status":"publish","type":"post","link":"https:\/\/www.anychart.com\/blog\/2025\/09\/05\/fresh-data-visualization-practices\/","title":{"rendered":"Fresh Data Visualization Practices to Explore \u2014 DataViz Weekly"},"content":{"rendered":"<p><a href=\"https:\/\/www.anychart.com\/blog\/2025\/09\/05\/fresh-data-visualization-practices\/\" target=\"_blank\"><img decoding=\"async\" class=\"alignnone size-full wp-image-19626\" src=\"https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2025\/09\/fresh-data-visualization-practices.png\" alt=\"Four screenshots of fresh data visualization practices to explore in this edition of DataViz Weekly\" width=\"100%\" srcset=\"https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2025\/09\/fresh-data-visualization-practices.png 1366w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2025\/09\/fresh-data-visualization-practices-300x169.png 300w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2025\/09\/fresh-data-visualization-practices-768x432.png 768w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2025\/09\/fresh-data-visualization-practices-1024x576.png 1024w\" sizes=\"(max-width: 1366px) 100vw, 1366px\" \/><\/a>One of the best ways to understand the practice of <a href=\"https:\/\/www.anychart.com\/blog\/2018\/11\/20\/data-visualization-definition-history-examples\/\" target=\"_blank\">data visualization<\/a> is to look at how others put it to use. Every week, new projects come out that apply <a href=\"https:\/\/www.anychart.com\/chartopedia\/chart-type\/\" target=\"_blank\">charts<\/a> or <a href=\"https:\/\/www.anychart.com\/chartopedia\/usage-type\/chart-to-show-location\/\" target=\"_blank\">maps<\/a> to real issues in different ways. We keep an eye on this flow and bring together a few examples worth a look in <a href=\"https:\/\/www.anychart.com\/blog\/category\/data-visualization-weekly\/\" target=\"_blank\">DataViz Weekly<\/a>. Here&#8217;s what we invite you to explore with us this time:<\/p>\n<ul>\n<li>Xi&#8217;s military purge \u2014 The Big Take<\/li>\n<li>Workplace harassment in Mexican hospitals \u2014 Serendipia<\/li>\n<li>Bias in AI models about Ukraine \u2014 Texty.org.ua<\/li>\n<li>Health risks from methane emissions in the U.S. \u2014\u00a0PSE Healthy Energy<\/li>\n<\/ul>\n<p><!--more--><\/p>\n<h2>Data Visualization Weekly: August 29, 2025 \u2013 September 5, 2025<\/h2>\n<h3>Xi&#8217;s Military Purge<\/h3>\n<p><a href=\"https:\/\/www.bloomberg.com\/graphics\/2025-xi-china-military-officials-purge\/\" target=\"_blank\" rel=\"nofollow\"><img decoding=\"async\" class=\"alignnone size-full wp-image-19631\" src=\"https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2025\/09\/china-military-purge-data-visualization.png\" alt=\"China Military Purge Data Visualization\" width=\"100%\" srcset=\"https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2025\/09\/china-military-purge-data-visualization.png 1200w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2025\/09\/china-military-purge-data-visualization-300x194.png 300w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2025\/09\/china-military-purge-data-visualization-768x497.png 768w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2025\/09\/china-military-purge-data-visualization-1024x662.png 1024w\" sizes=\"(max-width: 1200px) 100vw, 1200px\" \/><\/a><br \/>\nPresident Xi Jinping has overseen the biggest shake-up of China&#8217;s armed forces since Mao. In recent years, nearly a fifth of the generals he personally promoted have been dismissed or investigated, leaving the Central Military Commission (CMC) at its smallest size in the post-Mao era. The consequences extend beyond Beijing, raising questions about both China&#8217;s military readiness and Xi&#8217;s grip on power.<\/p>\n<p>Bloomberg&#8217;s The Big Take explores the scale of the purge, providing visualizations that clarify the scope. The central chart, titled All of Xi&#8217;s Men, depicts the tenure of every general appointed since 2012. As readers scroll, Xi&#8217;s three terms are highlighted, showing when investigations began and how the trend has accelerated. Notes along the way mark pivotal events, such as the rise and fall of He Weidong. Additional context in the narrative explains how the purges unfolded and what they mean for China&#8217;s leadership.<\/p>\n<p>See the story on <a href=\"https:\/\/www.bloomberg.com\/graphics\/2025-xi-china-military-officials-purge\/\" target=\"_blank\" rel=\"nofollow\">The Big Take<\/a>.<\/p>\n<h3>Workplace Harassment in Mexican Hospitals<\/h3>\n<p><a href=\"https:\/\/serendipia.digital\/investigacion\/acoso-laboral-en-hospitales\/\" target=\"_blank\" rel=\"nofollow\"><img decoding=\"async\" class=\"alignnone size-full wp-image-19630\" src=\"https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2025\/09\/mexican-hospital-harrassment-data-visualization.png\" alt=\"Workplace Harassment in Mexican Hospitals Data Visualization\" width=\"100%\" srcset=\"https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2025\/09\/mexican-hospital-harrassment-data-visualization.png 1200w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2025\/09\/mexican-hospital-harrassment-data-visualization-300x197.png 300w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2025\/09\/mexican-hospital-harrassment-data-visualization-768x504.png 768w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2025\/09\/mexican-hospital-harrassment-data-visualization-1024x672.png 1024w\" sizes=\"(max-width: 1200px) 100vw, 1200px\" \/><\/a><br \/>\nMedical trainees and residents in Mexico face exhausting 36-hour shifts and frequent harassment, a culture that continues despite regulations meant to prevent such practices. Surveys suggest that most doctors in training experience some form of abuse, whether verbal, physical, or even sexual \u2014 conditions that affect both their well-being and patient safety.<\/p>\n<p>Serendipia investigates the issue with data obtained through information requests to major public health institutions. A <a href=\"https:\/\/www.anychart.com\/chartopedia\/chart-type\/sankey-diagram\/\" target=\"_blank\">Sankey diagram<\/a>, pictured above, shows how complaints are distributed by type of abuse, the sex of the complainant, and their relationship to the aggressor. Additional visualizations, including <a href=\"https:\/\/www.anychart.com\/chartopedia\/chart-type\/line-chart\/\" target=\"_blank\">line<\/a> and <a href=\"https:\/\/www.anychart.com\/chartopedia\/chart-type\/stacked-column-chart\/\" target=\"_blank\">stacked column charts<\/a>, track the steady rise in workplace and sexual harassment reports since 2016, break them down by institution, and highlight differences across categories. The story combines these graphics with testimonies and case studies, highlighting the systemic nature of the problem faced by medical residents across Mexico.<\/p>\n<p>Check out the article on <a href=\"https:\/\/serendipia.digital\/investigacion\/acoso-laboral-en-hospitales\/\" target=\"_blank\" rel=\"nofollow\">Serendipia<\/a> by Fernanda Iz\u00facar and Hugo Osorio.<\/p>\n<h3>Bias in AI Models About Ukraine<\/h3>\n<p><a href=\"https:\/\/texty.org.ua\/projects\/115751\/what-does-ai-think-about-ukraine-exploring-the-biases-of-large-language-models\/\" target=\"_blank\" rel=\"nofollow\"><img decoding=\"async\" class=\"alignnone size-full wp-image-19628\" src=\"https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2025\/09\/ai-bias-ukraine-data-visualization.png\" alt=\"Bias in AI Models About Ukraine Data Visualization\" width=\"100%\" srcset=\"https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2025\/09\/ai-bias-ukraine-data-visualization.png 1200w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2025\/09\/ai-bias-ukraine-data-visualization-300x139.png 300w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2025\/09\/ai-bias-ukraine-data-visualization-768x355.png 768w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2025\/09\/ai-bias-ukraine-data-visualization-1024x473.png 1024w\" sizes=\"(max-width: 1200px) 100vw, 1200px\" \/><\/a><br \/>\nLarge language models (LLMs) shape much of today&#8217;s information ecosystem, from search engines to translation services. Their built-in biases can therefore affect how millions of people perceive global issues \u2014 including Ukraine.<\/p>\n<p>Texty.org.ua, in collaboration with OpenBabylon, tested 27 open-source AI models by asking them over 2,800 questions about Ukraine. Responses were evaluated across ten thematic areas, from geopolitics and national identity to public administration. A series of <a href=\"https:\/\/www.anychart.com\/chartopedia\/chart-type\/stacked-bar-chart\/\" target=\"_blank\">stacked bar charts<\/a> shows how models aligned with categories such as \u201cpro-Ukrainian,\u201d \u201cRussian propaganda,\u201d \u201cWestern neutrality,\u201d or \u201cignorant.\u201d The graphics highlight striking differences: some models consistently called Russia the aggressor, while others echoed Kremlin narratives or avoided clear answers. The study also reveals systematic patterns \u2014 with Canadian and French models giving more Ukraine-friendly responses, while Chinese ones leaned more heavily toward pro-Russian positions.<\/p>\n<p>Explore the investigation on <a href=\"https:\/\/texty.org.ua\/projects\/115751\/what-does-ai-think-about-ukraine-exploring-the-biases-of-large-language-models\/\" target=\"_blank\" rel=\"nofollow\">Texty.org.ua<\/a> by Anton Polishko, Artur K\u00fcllian, Inna Hadzynska, Mykola Khandoha, Nataliia Romanyshyn, Serhii Mikhalkov, Yevhen Kostiuk, and Yurii Filipchuk.<\/p>\n<h3>Health Risks from Methane Emissions in U.S.<\/h3>\n<p><a href=\"https:\/\/mrm.psehealthyenergy.org\/tool\" target=\"_blank\" rel=\"nofollow\"><img decoding=\"async\" class=\"alignnone size-full wp-image-19629\" src=\"https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2025\/09\/methan-risk-data-visualization.png\" alt=\"Health Risks from Methane Emissions Data Visualization\" width=\"100%\" srcset=\"https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2025\/09\/methan-risk-data-visualization.png 1200w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2025\/09\/methan-risk-data-visualization-300x170.png 300w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2025\/09\/methan-risk-data-visualization-768x435.png 768w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2025\/09\/methan-risk-data-visualization-1024x579.png 1024w\" sizes=\"(max-width: 1200px) 100vw, 1200px\" \/><\/a><br \/>\nMethane leaks are often seen mainly as a climate issue, but they also release other hazardous pollutants that can endanger human health. Compounds like benzene, toluene, and xylene are emitted alongside methane during oil and gas operations, posing risks to the respiratory, reproductive, and nervous systems.<\/p>\n<p>The nonprofit research institute PSE Healthy Energy, through its Methane + Health Initiative, has developed the Methane Risk Map. This interactive data visualization tool combines methane emissions records with regulatory-grade air quality modeling, mapping more than 1,300 methane leaks in the United States since 2016. It shows where pollutants released alongside methane may have reached harmful concentrations, helping to connect energy infrastructure with public health impacts. Users can explore locations, see modeled health risks, and understand how these emissions affect nearby communities. The tool is expected to be continually updated as new data becomes available, offering a unique way to connect methane events with public health concerns.<\/p>\n<p>Take a look at the project on the <a href=\"https:\/\/mrm.psehealthyenergy.org\/tool\" target=\"_blank\" rel=\"nofollow\">Methane Risk Map<\/a>.<\/p>\n<h2>Wrapping Up<\/h2>\n<p>Charting shifts in China&#8217;s military leadership, exposing workplace abuse in hospitals, revealing how AI models portray Ukraine, and mapping health risks from methane leaks\u200a-\u200aeach of these projects demonstrates how data visualization can help make sense of complex realities.<\/p>\n<p>Stay tuned for more data viz practices to explore in the next <a href=\"https:\/\/www.anychart.com\/blog\/category\/data-visualization-weekly\/\" target=\"_blank\">Data Visualization Weekly<\/a>.<\/p>\n<!-- AddThis Advanced Settings generic via filter on the_content --><!-- AddThis Share Buttons generic via filter on the_content -->","protected":false},"excerpt":{"rendered":"<p>One of the best ways to understand the practice of data visualization is to look at how others put it to use. Every week, new projects come out that apply charts or maps to real issues in different ways. We keep an eye on this flow and bring together a few examples worth a look [&hellip;]<!-- AddThis Advanced Settings generic via filter on get_the_excerpt --><!-- AddThis Share Buttons generic via filter on get_the_excerpt --><\/p>\n","protected":false},"author":9,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[175],"tags":[260,284,620,1389,256,1111,1370,774,1498,4106,4393,3099,3100],"class_list":["post-19621","post","type-post","status-publish","format-standard","hentry","category-data-visualization-weekly","tag-best-data-visualization-examples","tag-chart-examples","tag-data-analytics-examples","tag-data-visualization-best-pracices","tag-data-visualization-examples","tag-data-visualization-practice","tag-data-viz-examples","tag-dataviz-examples","tag-example","tag-examples","tag-practice","tag-storytelling-examples","tag-visual-storytelling-examples","wpautop"],"yoast_head":"<!-- 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