Cairn Wiki

Insight Grid Experiments

These experiments visualize the Critical Insight framework—showing where we have knowledge versus the vast space of potential insights we haven't yet discovered.

All Experiments

Concept

The core idea: most of the "insight space" is unexplored.

If we imagine all possible questions × topics × granularities as a huge grid, we've only filled in a tiny fraction. These visualizations make that visible:

  1. Sparse Grid: Each cell is a potential insight area. Filled cells (bright) = we have something. Empty (dark) = unknown.

  2. Treemap: Hierarchical view where the filled portion of each rectangle shows knowledge density. Most areas are mostly empty.

  3. Score Matrix: Individual insights rated on Surprising × Important × Compact.

  4. Pixel Map: Ultra-dense view showing thousands of potential insight areas, with ~2% explored.

Individual Components

Sparse Knowledge Grid

A 40×60 grid with ~4% fill rate:

Knowledge Treemap

Nested rectangles showing knowledge density by domain:

Insight Score Matrix

Individual insights rated on the three criteria:

Pixel Density Map

High-resolution view of the insight space:

Research Frontier

3D-style columns showing exploration depth by research area:

Priority Matrix (ITN Framework)

Classic Importance × Tractability × Neglectedness visualization:

Topic × Question Grid

Categorical grid showing which question types we've addressed for each topic:

Design Notes

Color encoding:

  • Brightness = importance (brighter = more important)
  • Saturation/hue = surprising (warmer = more surprising)
  • Opacity = quality/confidence

Interactivity:

  • Hover to see details
  • Toggle color modes
  • Sort by different criteria

The key insight these visualizations convey: We've barely scratched the surface of what's knowable. Most cells are dark. This should motivate:

  1. Systematic exploration of the space
  2. Prioritizing high-importance regions
  3. Seeking surprising findings (they carry more information)