Summary and Schedule
This is a new lesson built with The Carpentries Workbench.
| Setup Instructions | Download files required for the lesson | |
| Duration: 00h 00m | 1. Why Visualize Data: Readings | |
| Duration: 00h 12m | 2. Why Visualize Data: Lecture | How do you write a lesson using Markdown and sandpaper? |
| Duration: 00h 24m | 3. Reading and Interpreting STEM Charts |
How can data visualization and creativity help answer important
scientific questions? Why did data visualization become predominant in the social sciences earlier than for physical and natural sciences? How did Du Bubois use data visualization to challenge false biological theories of racial inequality? How did team science help Du Bois’ team to create impactful visualizations for the 1900 Paris exposition? |
| Duration: 00h 44m | 4. R coding interactives | |
| Duration: 00h 56m | 5. Python interactives | |
| Duration: 01h 08m | 6. Stata activity | |
| Duration: 01h 20m | 7. Learning Evaluation | |
| Duration: 01h 32m | 8. Our Team | |
| Duration: 01h 44m | Finish |
The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.
Our modules are designed for learning modern programming tools for data visualization through the recreation and adaption of scientific charts created by W.E.B. Du Bois and his collaborators for the 1900 Paris World Expo.
This site includes coding interactives in R and Python that you open and use with any web browser without any software installations on your own computer. These activities provide code blocks, often with prompts for users to fill in the blank or edit code before clicking execute. These activities are ideal for beginners who do not yet want to install and learn to use a code editor and graphical user interface (GUI) on your own computer.
If you already use a code editor and GUI like R Studio, Sublime, or Jupyter Lab, we recommend that you instead use our language specific Lesson sites that use live coding exercises:
- STEM Data Visualization with Du Bois in R
- STEM Data Visualization with Du Bois in Python
Prior to the interactive coding activities, we present “Episodes” on:
- Why Visualize Data: This covers how visualization can be a tool for creative problem solving in STEM research. The lesson examines how Du Bois turned to visualization as a tool for scientific analysis and communication to challenge false theories of racial inequality.
- Reading and Interpreting Charts: This introduces the four major chart types employed by Du Bois that are still in use today. It covers why we use particular chart types for specific types of data.