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		<title>Visual Vocabulary &#8211; Designing with data</title>
		<link>https://fountn.design/resource/visual-vocabulary/</link>
		
		<dc:creator><![CDATA[Ozan Öztaskiran]]></dc:creator>
		<pubDate>Fri, 14 Feb 2025 11:34:33 +0000</pubDate>
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					<description><![CDATA[Visual Vocabulary, created by FT Interactive, helps users choose the best chart types for data visualization. It offers a clear and structured framework, guiding users—such as data journalists, analysts, and designers—through selecting the right visual representation based on the type of data and the story they want to convey. The resource categorizes charts according to [&#8230;]]]></description>
		
		
		
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		<title>Data Visualization Style Guide</title>
		<link>https://fountn.design/resource/data-visualization-style-guide/</link>
		
		<dc:creator><![CDATA[Ozan Öztaskiran]]></dc:creator>
		<pubDate>Sun, 09 Feb 2025 12:42:13 +0000</pubDate>
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					<description><![CDATA[The BigCommerce Data Visualization Style Guide is a Figma resource that helps designers and developers create clear, consistent, and brand-aligned data visualizations. It sets detailed standards for formatting, chart styles, color schemes, typography, and interactive behaviors to ensure that data is presented in a way that enhances clarity and usability.]]></description>
		
		
		
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		<title>Flowingdata &#8211; Data Visualization and Statistics</title>
		<link>https://fountn.design/resource/flowingdata-data-visualization-and-statistics/</link>
		
		<dc:creator><![CDATA[Ozan Öztaskiran]]></dc:creator>
		<pubDate>Sun, 09 Feb 2025 12:39:24 +0000</pubDate>
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					<description><![CDATA[FlowingData, created by Nathan Yau, explores how data visualization and analysis shape how we understand the world. The platform showcases a blend of personal projects, curated works, and practical guides, offering insights into making data more accessible and meaningful. It also features tutorials and case studies that break down complex visualization techniques into approachable steps. [&#8230;]]]></description>
		
		
		
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		<title>Designing experiences through data stories</title>
		<link>https://fountn.design/resource/designing-experiences-through-data-stories/</link>
		
		<dc:creator><![CDATA[Ozan Öztaskiran]]></dc:creator>
		<pubDate>Sun, 09 Feb 2025 12:23:51 +0000</pubDate>
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					<description><![CDATA[Marion Hekeler discusses how structuring data as narratives can make complex information more accessible and engaging for users. She emphasizes that designers can help users better understand and act upon insights by integrating data into compelling stories. Hekeler also highlights the role of data stories in providing a comprehensive view of information, which allows data [&#8230;]]]></description>
		
		
		
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		<title>Semiotic &#8211; Data visualization framework for React</title>
		<link>https://fountn.design/resource/semiotic-data-visualization-framework-for-react/</link>
		
		<dc:creator><![CDATA[Ozan Öztaskiran]]></dc:creator>
		<pubDate>Sat, 08 Feb 2025 11:55:06 +0000</pubDate>
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					<description><![CDATA[Semiotic is a data visualization framework built for React applications, designed to help developers create interactive charts and graphs with ease. It offers a variety of visualization types, including line charts, area charts, scatterplots, bar charts, and pie charts, enabling the effective representation of complex datasets. The framework is highly customizable, allowing users to adjust [&#8230;]]]></description>
		
		
		
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		<title>A Guide To Getting Data Visualization Right</title>
		<link>https://fountn.design/resource/a-guide-to-getting-data-visualization-right/</link>
		
		<dc:creator><![CDATA[Ozan Öztaskiran]]></dc:creator>
		<pubDate>Sat, 08 Feb 2025 11:53:43 +0000</pubDate>
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					<description><![CDATA[Sara Dholakia’s article offers clear guidance on creating effective data visualizations. It explores essential questions that help determine the right approach, such as the message the data should communicate, the target audience, and which chart types work best with different datasets. She explains how to avoid common pitfalls in visualization design and provides practical advice [&#8230;]]]></description>
		
		
		
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		<title>Fundamentals of Data Visualization</title>
		<link>https://fountn.design/resource/fundamentals-of-data-visualization/</link>
		
		<dc:creator><![CDATA[Ozan Öztaskiran]]></dc:creator>
		<pubDate>Fri, 07 Feb 2025 10:57:43 +0000</pubDate>
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					<description><![CDATA[Fundamentals of Data Visualization by Claus Wilke explains how to design accurate and accessible data visualizations. It focuses on chart selection, accessibility, and avoiding common design mistakes. The resource includes examples and illustrations to make key concepts easier to understand and apply. The book addresses topics like color theory, layout design, and storytelling with data. [&#8230;]]]></description>
		
		
		
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		<title>Dataviz Inspiration</title>
		<link>https://fountn.design/resource/dataviz-inspiration/</link>
		
		<dc:creator><![CDATA[Ozan Öztaskiran]]></dc:creator>
		<pubDate>Tue, 04 Feb 2025 07:26:52 +0000</pubDate>
				<guid isPermaLink="false">https://fountn.design/?post_type=resource&#038;p=7971</guid>

					<description><![CDATA[Dataviz Inspiration is a platform offering a curated collection of over 195 data visualization projects categorized by chart type and design. Its purpose is to provide designers, analysts, and data enthusiasts with a centralized resource for exploring various visualization styles, including line charts, scatterplots, area charts, and maps. TDataviz Inspiration features a robust search function, [&#8230;]]]></description>
		
		
		
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		<title>WHO Data Design Language</title>
		<link>https://fountn.design/resource/who-data-design-language/</link>
		
		<dc:creator><![CDATA[Ozan Öztaskiran]]></dc:creator>
		<pubDate>Tue, 04 Feb 2025 07:22:32 +0000</pubDate>
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					<description><![CDATA[The WHO Data Design Language (DDL) is a framework for consistently presenting global health data. It provides detailed guidelines and tools to ensure data visualizations, charts, and other visual materials are accessible and effective for diverse audiences. Key components of the DDL include a library of chart templates, typography and color specifications, and design principles [&#8230;]]]></description>
		
		
		
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		<title>Data Visualization Style Guidelines</title>
		<link>https://fountn.design/resource/data-visualization-style-guidelines/</link>
		
		<dc:creator><![CDATA[Ozan Öztaskiran]]></dc:creator>
		<pubDate>Mon, 03 Feb 2025 07:18:43 +0000</pubDate>
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					<description><![CDATA[Data Viz Style Guide provides a comprehensive framework for crafting clear, consistent, and accessible data visualizations. It offers guidance on selecting appropriate chart types, using effective color palettes, and ensuring readability through typography and formatting. The guide is structured to help users design visualizations that prioritize clarity and accommodate diverse audiences, including those with accessibility [&#8230;]]]></description>
		
		
		
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