When to use it
- Visualize patterns across two dimensions (e.g., time vs category).
- Highlight intensity using color gradients.
- Identify clusters, correlations, or anomalies.
- Display dense datasets in a compact way.
- Compare relative differences rather than exact values.
When NOT to use
- When precise values must be read.
- For small datasets (low value vs complexity).
- When users are not familiar with color scales.
Categories
- Chart Type: Matrix
- Data Type: Continuous or discrete numeric values (aggregated)
- Chart Family: Heatmap-based
- Purpose: Reveal patterns, trends, and anomalies
Data requirements
- 2 categorical or continuous dimensions (X + Y)
- 1 numeric value (mapped to color)
- Often requires aggregation
Use cases
BSPM
BSPM is a user centered ex-post monitoring tool that enables fast and well-founded analysis of both the awarded capacity and the actually delivered performance of balancing service providers, using meaningful KPIs and visualizations. It provides reliable, settlement-relevant data while establishing a scalable foundation for future extensions and modules.
Accessibility
Do
- Use a color palette with sufficient contrast and ensure color-blind accessibility.
- Include a clearly visible legend with numeric ranges or scale.
- Use intuitive color gradients (low → high).
- Provide alt text or summaries explaining patterns and key insights.
- Keep the grid readable and avoid excessive density.
Don't
- Use red/green or other problematic combinations without alternatives.
- Omit the legend or make it too small to read.
- Rely on color alone without contextual explanation.
- Change color scales between charts (inconsistent interpretation).
- Use misleading gradients that distort magnitude perception.
- Embed heatmaps as images without accessible descriptions.
Related data visualizations
-
Scatter Plot
Shows detailed relationships between two variables; useful when exact values and distribution matter more than aggregated patterns. -
Line Chart
Better suited for showing trends over time when continuity and progression are key. -
Bar Chart
Useful for comparing exact values across categories when precision is more important than pattern recognition.