Critical Scientific Visualization: Reading and Analyzing Data across Disciplines

Visual representations of data shape how we understand scientific breakthroughs, yet every visualization is a series of active design choices. This course provides a foundational framework to critically analyze how scientific data is visualized, helping you understand the power, limits, and responsibilities of representing complex information. You will transition from a passive viewer of charts and models to an active, critical reader and designer of scientific graphics. What you will learn: Understand the core concepts of visual literacy and how data is translated into visual form; Analyze real-world case studies across scientific, engineering, and medical domains; Evaluate the ethical implications and potential biases in data presentation choices; Learn modern principles of accessible and inclusive data design; Practice identifying misleading visual structures in public and academic research. We begin with key terminology and the foundational history of scientific image-making, then progress to examining modern visualization techniques across diverse disciplines. This text-based course is designed for beginners, researchers, and designers with no prior technical or programming experience. Start developing your critical eye for data representation today.