Summary
Highlights
The presentation shifts focus to storytelling with data, explaining that it's a fundamental part of the human experience and activates different parts of the brain than data alone. Emotions, driven by stories, change behavior, unlike raw data. The speaker emphasizes how stories increase trust and capture attention, impacting information retention.
The essential elements of a story are described: characters, context, conflict, plot, climax, and closure. These translate to setting the scene, identifying impacted communities, presenting the problem (climax/personal transformation), and offering a resolution or life lesson, especially in the context of public health issues like obesity or heart health.
This part focuses on finding the story within the data, considering the audience, and using plain language. It emphasizes analyzing data for insights, choosing effective data visualizations, providing context, and structuring the story to be clear, concise, and captivating for short attention spans. The goal is to use data-informed stories to drive positive change and better-informed decisions.
A narrative example about diabetes in Washington D.C. is presented to illustrate how data can be woven into a compelling story. It highlights the disproportionate impact on minority communities and those with lower socioeconomic status, the economic burden, and potential solutions like preventative care and education. The story aims to inspire understanding and advocacy.
The presentation concludes by addressing challenges, particularly health misinformation, which became prominent during the pandemic. It defines misinformation as false, inaccurate, or misleading information and stresses the importance of sharing accurate, clear, and easy-to-find information from trusted sources like CDC and NIH to combat dangerous decision-making. Engaging with the community and using trusted 'storytellers' are key strategies.
Katie Bueno from Health Data viz introduces the session on creating successful data visualizations, highlighting that these best practices are rooted in extensive research on how the brain processes visual information. She mentions the company's book 'Visualizing Health and Healthcare Data' as a resource.
The presentation explains that 70% of information is taken through the eyes, but only 5% is processed by the brain. An exercise demonstrates how preattentive attributes (like color highlighting) drastically improve the speed and ease of information processing, making data more understandable. It discusses iconic memory and preattentive attributes such as form, color, and position.
A crucial aspect of data visualization is the thoughtful use of color. The speaker addresses colorblindness, noting that 1 in 12 males and 1 in 200 females are colorblind, particularly red/green. It's recommended to use colorblind-friendly palettes (like blues and oranges) and ensure colors impart meaning rather than just being decorative. Examples show how monochromatic charts or highlighting key data points with color are more effective than using many arbitrary colors.
The section discusses common errors in data visualization, such as having too many bars in a chart, using pie charts with too many slices, or complex stacked bar charts. Redesigns demonstrate how changing chart orientation, using direct labeling instead of color legends, and opting for bar charts over pie charts can significantly improve clarity and quick comprehension. The speaker emphasizes that answers should be 'quick and easy to understand' due to short attention spans.
Participants are asked to identify issues in several examples of 'chart junk,' including 3D bar charts, overly colorful designs, pie charts not representing a whole, and visualizations with dark backgrounds and poor color contrast that hinder readability. The importance of ADA compliance for text and background colors is highlighted, ensuring accessibility for all users.
The speaker differentiates infographics from info posters and provides tips for creating effective infographics. These include using graphic organizers, defining a clear outcome (awareness, teaching, persuasion, action), identifying the problem/story, researching data from reputable sources, and including a summary or call to action. Examples of infographics on location-based health disparities and mental health are shown.
Key development tips include empathizing with end-users, defining the problem or objective, ideating diverse solutions through brainstorming and sketching, prototyping ideas (even with pen and paper), and testing visualizations with internal staff before public release. These steps aim to ensure visualizations are impactful and meet user needs.