nbbaier Tufte Visualization Ideation
Apply Edward Tufte's principles to design clear, honest, high-density data visualizations.
Workflow
For new visualizations:
Clarify the data story
- What comparisons matter?
- What's the key insight to communicate?
- Who's the audience?
Select approach using Tufte principles:
- High comparison need → Small multiples
- Dense data → Consider data tables, sparklines
- Time-series → Line charts with minimal grid
- Part-to-whole → Avoid pie charts; prefer bar/table
Design with data-ink in mind
- Start minimal, add only what's necessary
- Every element must earn its ink
- Default to grayscale; use color purposefully
Apply the Tufte test (see references/tufte-principles.md)
For critiquing visualizations:
Check graphical integrity
- Calculate lie factor if proportions seem off
- Verify baselines and scales
- Look for 3D distortion
Identify chartjunk
- Decorative elements
- Heavy grids
- Unnecessary 3D effects
- Moiré patterns
Evaluate data-ink ratio
- What can be erased?
- What's redundant?
Suggest improvements with specific before/after recommendations
Key Principles Reference
references/tufte-principles.md— core principles from Visual Display of Quantitative Information: lie factor, data-ink, chartjunk, small multiples, integrity.references/analytical-design.md— extensions from Envisioning Information, Visual Explanations, and Beautiful Evidence: the 6 principles of analytical design, sparklines, layering & separation, micro/macro, range-frames, causality, confections. Load when designing dashboards, dense displays, sparklines, or explanatory graphics.
Quick checklist:
- Lie Factor ≈ 1.0 (no visual distortion)
- Maximum data-ink ratio
- Zero chartjunk
- Clear labeling
- Answers "compared to what?"
- Shows causality or mechanism where relevant
- Multivariate (not over-reduced)
- Words, numbers, images integrated — not segregated
- Reveals multiple levels of detail (micro + macro)
- Layering: primary data dominates, secondary recedes
- Appropriate data density