Data Visualization Principles Skill

Purpose

Establishes principles for creating effective, accessible, and honest data visualizations for political intelligence data.

Chart Selection Guide

Data Type Recommended Chart

Comparison Bar chart, grouped bar

Trend over time Line chart, area chart

Part-to-whole Pie/donut, stacked bar

Distribution Histogram, box plot

Correlation Scatter plot

Relationships Network diagram, force graph

Geographic Choropleth map

Hierarchical Treemap, sunburst

Design Principles

• Data-ink ratio — Maximize data, minimize decoration

• Clarity — Clear labels, legends, and titles

• Honesty — No misleading scales or truncated axes

• Accessibility — WCAG 2.1 AA compliant colors and patterns

• Responsiveness — Adapt to screen sizes

• Interactivity — Tooltips, zoom, filter where appropriate

Color Guidelines

• Use colorblind-safe palettes

• Maintain 4.5:1 contrast ratio for text

• Use patterns/textures as secondary encoding

• Follow cyberpunk theme variables

• Limit to 7±2 colors per chart

Political Data Considerations

• Show confidence intervals for predictions

• Include data source attribution

• Indicate data freshness/staleness

• Support party-specific color coding

• Handle missing data transparently

Performance

• Canvas for large datasets (>1000 points)

• SVG for interactive/accessible charts

• Lazy load charts below the fold

• Optimize re-renders on data updates

Related Policies

• Secure Development Policy