One of the problems with living in a world awash with data isn't merely understanding the data, but finding an effective and meaningful way to present and explain the data to others: others who often don't possess the same domain expertise or ability to understand the implications of the data. In a world that increases in complexity daily (since 1970 the branches of "complexity science" have increased from three to 33) the ability to understand and be understood becomes increasingly essential.
With that in mind, Dan Boyarski (Professor of Design and former head of Carnegie Mellon's design school) and I have created a course in "communicating complexity:" a combination lab, project-based course, and research platform.
More than simply a course in data visualization, this is an approach founded upon concepts of design thinking, that will uncover and apply best practices in communincating complexity across all disciplines and audiences.
The course encompasses such areas as:
- Critical thinking & Evidence-Based Presentation;
- Organization & Pattern Languages;
- Design Thinking;
- The Psychology of Communication;
- Information Architecture and Design;
- Visualization;
- Advanced presentation techniques;
- Advanced writing for understanding;
- Presentation of evidence through books, papers, websites, blogs etc;
- Design examples of best practices in visualization and making information understandable, useful, and actionable;
- Real-world policy, IT, security, and technology explanations and examples;
- Student projects;
- Class research.
For a deeper look at the course, please visit the course wiki.