scientific-visualization

Overview

Effective scientific visualization communicates data clearly, honestly, and accessibly. Poor chart choices, misleading axes, or inaccessible color palettes can obscure findings or introduce bias. This guide covers the full workflow of scientific figure preparation: from selecting the right chart type for your data structure through color theory, accessibility, and journal submission formatting requirements.

Key Concepts

Chart Type and Data Type Alignment

Every chart type is optimized for a specific data structure. Mismatches (e.g., pie charts for continuous distributions, bar charts for time series) hide structure and distort perception.