A Dessau Approach to Data Visualization
My MFA fellow, Stephanie Long & I design a data visualization curriculum for DEL (Digital Engaged Learning Conference) participants who come from different disciplines to understand the process of working with data and data visualization using the four of many Bauhaus principles:
1. Process vs. Product
2. Form vs. Function
3. Simplicity vs. Complexity
4. The Workshop Format — Learning by Doing
Objectives
This workshop is a learn-by-doing opportunity. Much like the Dessau students who learned design principles by working with the materials to create every-day objects, participants will learn design principles through working with data to create meaningful visuals. Just as Bauhaus students learned manufacturing techniques, attendees will learn how to manufacture an every-day necessity using data visualization. By applying the same principles of form and function that shaped modern design, this workshop condenses the complex process of data visualization into a simple format. The workshop introduces participants to:
1. Two primary types of data visualization: static vs. interactive
2. Collecting, examining data, and identifying data relationships
3. Building a narrative out of data
4. Creating data visualization using primary design elements (color, shape, line, pattern) & the principle of hierarchy
The Bauhaus Curriculum
Data Visualization Workshop
The Design Element
Form v.s. Function
Only uses primary shapes and colors, with the force connection idea to help the participants create simple but functional data visualization from a small data set with 2–3 categories.
Explanatory v.s. Exploratory
We create a data matrix to anticipate how data can be visualized base on the design elements used.
Data Exercises
After introducing primary design elements, "form and function" matrix, and four mini exercises (visualizing small data with only 2–3 categories), we invite participants to collect their data with a minimum of 5 categories. They then identify the relationships between among categories (we only have one data set), identify themes, and create a static/explanatory hand-drawing data.
Data Workbook
Participants receive a workbook that includes 4 mini exercises (data provided) and 1 big data exercise which they need to collect their personal data.
