Visualization as Design

Lesson 5: Design Principles

Briefly exploring historical context and foundations.

Objective

Trace the historical evolution of data visualization through pioneering figures and introduce foundational design principles while examining their value and limitations.

Outline

This lecture examines key historical figures in data visualization and introduces Edward Tufte's influential design principles. We explore how these early ideas shaped modern practice while recognizing the need for empirical validation, setting the stage for cognitive and perception science approaches.

Historical pioneers

A rapid overview covering one influential figure per century to understand how we arrived at modern data visualization.

• Michael Florent van Langren (1600s): Earliest known statistical graphic showing uncertainty in measurements
• William Playfair (1700s): Created and popularized fundamental chart types including pie charts and area charts
• Florence Nightingale (1800s): Pioneered data visualization for advocacy and policy change
• W.E.B. Du Bois (1900s): Transformed data visualization into a tool for social justice messaging
• Donald Bitzer (Today): Early innovator in interactive media and explorable explanations through PLATO system

Note: It is important to acknowledge who is remembered and who is left out of traditional historical narratives and how that fits into existing power structures.

Tufte's design principles

Edward Tufte brought many people into information design through touring workshops and popular books, fundamentally shaping modern data visualization.

• Lie Factor: Visual representation should accurately reflect magnitude of change in data
• Chartjunk: Remove visual elements that don't convey data or assist comprehension
• Data-Ink Ratio: Maximize proportion of graphic's ink devoted to displaying data
• Data Density: Increase amount of data displayed per unit area within reason

Context:

• These are guidelines many follow as standard advice, not absolute rules
• His ideas are readily applicable even with basic tools like Google Sheets

Problematic visualizations

Group activity: analysis of "darts" or problematic graphics catalogued by Michael Friendly that demonstrate Tufte's work.

• Common visualization mistakes and design choices that create confusion
• Application of Tufte's principles to real-world examples
• Development of critical eye for evaluating visualizations
• Understanding why certain design choices fail

Moving beyond Tufte

Recognition that these principles alone are sometimes insufficient for effective data visualization.

• Many design principles were based on aesthetic judgment rather than controlled studies
• Some principles lack empirical validation
• Context, audience, and purpose require different approaches
• Sometimes "inefficient" designs create stronger emotional impact
• Need for scientific understanding of cognitive and perception principles

Next lectures will explore empirical approaches to encoding devices and channel effectiveness before questioning when even those rules aren't complete.

Take Aways

Historical context provides foundation for understanding design principles, but effective visualization requires empirical validation.

• Data visualization has evolved over centuries with each pioneer contributing unique perspectives
• Tufte provided actionable guidelines that remain influential today
• Design principles should be understood as guidelines, not absolute rules
• Understanding both value and limitations of traditional design wisdom is essential
• Modern visualization must be grounded in scientific understanding of human perception
• Who is remembered in history reflects systemic biases we must acknowledge

Citations

[1] B. Adhikari, "Marey's train schedule," University of Missouri Saint Louis, 2021. Available: https://badriadhikari.github.io/data-viz-workshop-2021/minards/

[2] M. van Langren, "Grados de la Longitud," 1644. Available: https://commons.wikimedia.org/wiki/File:Grados_de_la_Longitud.jpg

[3] J. Norman, "Michael Florent van Langren issues the Earliest Known Graph of Statistical Data," History of Information, 2013. Available: https://www.historyofinformation.com/detail.php?id=3415

[4] W. Playfair, "Time Series of Exports and Imports of Denmark and Norway," Commercial and Political Atlas, 2011. Available: https://en.wikipedia.org/wiki/William_Playfair#/media/File:Playfair_TimeSeries-2.png

[5] D. Bellhouse, "The Flawed Genius of William Playfair: The Story of the Father of Statistical Graphics," University of Toronto Press, 2023. Available: https://www.jstor.org/stable/10.3138/jj.6167271

[6] M. Callejon, "Masters series: William Playfair, the father of statistical graphics," Flourish, 2023. Available: https://flourish.studio/blog/masters-william-playfair-father-of-statistical-graphics/

[7] H. Hering, "Florence Nightingale Portrait," 1860. Available: https://en.wikipedia.org/wiki/Florence_Nightingale#/media/File:Florence_Nightingale_(H_Hering_NPG_x82368).jpg

[8] J. Mansky, "W.E.B. Du Bois' Visionary Infographics Come Together for the First Time in Full Color," Smithsonian Magazine, 2018. Available: https://www.smithsonianmag.com/history/first-time-together-and-color-book-displays-web-du-bois-visionary-infographics-180970826/

[9] University of Illinois, "Faculty portrait photograph of Professor of Electrical Engineering Donald Bitzer," University of Illinois, 1971. Available: https://archon.library.illinois.edu/archives/index.php?p=digitallibrary%2Fdigitalcontent&id=7887

[10] J. Scott, "5.08 of BBS: The Documentary," Textfiles, 2005. Available: https://en.wikipedia.org/wiki/PLATO_%28computer_system%29#/media/File:PLATO_chem_exp.jpg

[11] B. Leroy, "Review of Tufte's The Visual Display of Quantitative Information," Carnegie Mellon University, 2018. Available: https://benjaminleroy.github.io/pages/blog/public/post/2018/05/16/review-of-tufte-s-the-visual-display-of-quantitative-information/

[12] M. Friendly, "Darts," York University, 2025. Available: https://www.datavis.ca/gallery/lie-factor.php

[13] Princeton University, "Public Lectures: Edward Tufte (Photo)," Princeton University. Available: https://lectures.princeton.edu/lectures/2013/edward-tufte

[14] Union of Concerned Scientists, "Brief History of US Fuel Efficiency Standards," Union of Concerned Scientists, 2017. Available: https://www.ucsusa.org/resources/brief-history-us-fuel-efficiency

[15] N. Vega, "A gallon of gas was 65 cents in 1978—here's how much it cost every year since," CNBC, 2022. Available: https://www.cnbc.com/2022/04/13/how-much-gas-cost-every-year-since-1978.html

[16] M. Dunnigan, "Why Tufte is Wrong," Medium, 2014. Available: https://medium.com/@MattDuignan/why-tuftes-wrong-a9bd6a14ff8e

[17] B. Adhikari, "Data Density," University of Missouri Saint Louis, 2021. Available: https://badriadhikari.github.io/data-viz-workshop-2021/Tufte/Chapter_8/

License

This lesson is part of Interactive Data Science and Visualization and is released under a CC-BY-NC 4.0 license.