These are my notes from a data visualisation short course.
The idea is to go beyond the bar chart.
- to express ___ (i.e. beyond pure visualisation)
- as material ... having of a physical sense
Algorithms need to be very explicit. When hand drawn, there's room for more experimentation.
The design/art is in the rules.
Pioneer (in a way): Sol Lewitt and his rule based drawings. He writes the rules, but someone else (the draftsmen) implement them. He's dead now, but his drawings are still being executed nowadays.
Another example: conditional design workbook.
To have in mind: Jacques Bertin's visual variables
Sam Winston's data-based Drawing breath - infographic or art?
Also to have in mind: Gestalt's principles. For clarity, legibility.
Timed / warm up exercises
- Mark making / fearless drawing, 5 minutes
- Creativity within the rules: within a circle (outline) draw 100 non straight lines (A reduced interpretation of Sol Lewitt's Drawing #1099)
- Visual variable brainstorming (by Santiago Ortiz) - come with as many ways to visualise the relation between two values: 37 and 75
- Continue a progression
- Data 'gesture drawing'
How to data visualise
- Find patterns of data and determine data structure. What are the categories? The number of entries in the category? Bands?
- Sketch / experiment. Not being precise, but more about how could it look? Legibility vs aesthetics? Depends on the context: is it for an art gallery? Is it for a newspapers article? Is it for a bank extract?
- Set the rules
- Test data scenarios - will the rules work in all situations?
- Make sure the design system (the rules) work with the largest category first.
- Refine rules with consideration to legibility - use Gestalt principles
- Does the system work from a distance?
- Create final drawing (by hand) or bring into computer. If interactive--how would you let someone filter info?
Comparing different icons of different sizes is bad. A solution can be to put them inside circles, which are easier to compare visually.