Data Visualization

Data Visualization

Warming stripes

Alice McGrath | 11 June 2024


  1. Principles and approaches to data
  2. What makes a good data visualization?
  3. The process of visualization
  4. Activity:
  5. Activity: Draw your data


Data Humanism Data Humanism, a visual manifesto, by Giorgia Lupi

Data feminism principles

  1. Examine power
  2. Challenge power
  3. Elevate emotion & embodiment
  4. Rethink binaries and hierarchies
  5. Embrace pluralism
  6. Consider context
  7. Make labor visible
Data Feminism, D’Ignazio, C., & Klein, L. (MIT UP: 2020). Read for free online.

What makes a good data viz?

  • What’s the message of the visualization?
  • What questions does it raise?
  • What makes it effective?

Ex. 1 Warming Stripes

Data viz with red and blue stripes Ed Hawkins, University of Reading, 2018

See also this interactive version here or read more about its growing influence

  • What’s the message of this viz?
  • Why is this effective?

Example 2: Wealth, shown to scale

screengrab of wealth viz Matt Korostoff (2021). Read about it on github: MKorostoff/1-pixel-wealth

Example 3: Dunham’s Data

Interactive Flow of Katherine Dunham’s Dancers, Drummers, and Singers (2019)

See also blog post by Kate Elswit and Harmony Bench

Other cool examples

How do you make a data viz?

Get data

  • Collect it
  • Find a dataset
  • Clean and organize it
  • Get to know the context and effects of the data collection process
  • Basic info: try using wtf csv

Analyze data

  • What types of data do you have?
  • How many variables do you have? How do your variables relate to each other?
  • What questions can your dataset answer? What stories can it tell?

What types of data do you have?

Numeric | categoric | geographic | temporal |relationships

How many variables do you have? How do your variables relate to each other?

quantities/distribution | correlation | part of a whole | change over time | connections

What questions can you answer?

What stories can you tell?

Design visualizations

What will you show?

  • All variables? Relationships between variables?
  • Summaries? Every data point?

What graph types would be most effective?

  • Useful resource: From Data to Viz
  • Use your imagination! Draw your visualization on paper.
  • For inspiration: Dear Data project, Georgia Lupi & Stefanie Posavec; See also the winners of the [Information is Beautiful Awards]


  • What methods can you use to highlight your variables?
  • How can you make the results visually compelling and engaging?
  • How can you make them more accessible?


  • What should viewers take away from your visualization?
  • What kind of contextual information is needed for them to understand it?

Activity: collecting and drawing data


  • How many countries and states have you lived in? For how long?
  • List all the locations, with the approximate number of years you have lived there
  • Add your name, each location, and the number of years to the excel spreadsheet for this workshop: dataviz-workshop-locations-6-11-24.xlsx


  • In groups of 2: draw visual representations of this dataset
  • Design it however you like
  • Aim to create two different versions

Activity: visualizing data with RawGraphs

Creating a data visualization using

  1. Choose one of the data samples and select a recommended visualization
  2. Assign categories and data columns to features
  3. Select colors and labels to customize your data viz
  4. Export it as an .svg file

Next steps

  • Open the .svg in Illustrator for additional customization
  • Find your own dataset to visualize in rawgraphs
  • Embed your visualization in your log


Sources for datasets

Data viz tools

cage pool viz

Remember: correlation is not causation! See other Spurious Correlations, by Tyler Vigen.