Reference & Resources

Interesting Data Viz

• Pudding
• Flowing Data
• Information is Beautiful
• Junk Charts

Handy Tools

• RAWGraphs app (browser-based data visualization app)
• Kepler.gl (geospatial tool that can export a static web app)
• Tableau Public (free hosted version of famous business analytics software)
• Florish (data storytelling)
• Datawrapper (embeddable visualizations)
• Google Charts (integrated with Sheets)

Choosing a Visualization Type

• The Data Visualization Catalogue
• Periodic Table of Visualization Methods
• Data to Viz
• Visual Vocabulary
• Data Viz Project

Reference

• Nathan Yau, “How to Spot Visualization Lies”, Flowing Data, 2017.
• Alberto Cairo, How Charts Lie: Getting Smarter about Visual Information, 2019 (at the library).
• Jack Dougherty and Ilya Ilyankou, “How to Lie with Charts”, Hands-On Data Visualization, 2023.
• DataSpire, “5 Tips to Be Aware of How Charts Lie”, 2021.
• DataSpire, “Let’s leverage perception science to our advantage!”, 2020.
• Micah Bowers, “Numbers Shouldn’t Lie: An Overview of Common Data Visualization Mistakes”, Toptal Design.
• Jackie Fleming, “A Librarian’s Tips for Reading Visual Information”, 2021.
• Katy Börner, Andreas Bueckle, and Michael Ginda, “Data visualization literacy: Definitions, conceptual frameworks, exercises, and assessments”, PNAS 2019.

Some Bad Examples

• When Data Visualization Really Isn’t Useful (and When It Is)
• Remove Your Rose Tinted Glasses: Data Visualizations Designed to Mislead
• Military Expenditures: How Do the Top-Spending Nations Compare? (dual axis chart used out of context)
• Mistakes, we’ve drawn a few: Learning from our errors in data visualisation
• 12 Bad Data Visualization Examples Explained