The Tufte- Feynman Principle

The Feynman diagram is considered the greatest data visualization project ever. Its beauty lies in its utility. Richard Feynman first invented them to organize terms in computations in quantum electrodynamics (QED). The diagrams provided a surprisingly good approximation of sub-atomic behavior. Good enough to be related to three Noble prize-winning accomplishments. Edward Tufte, considered globally as a pioneer in the field of data visualization, regarded the Feynman Diagram as the epitome of all that is good and aspirational of Data visualization. He came up with the Tufte- Feynman principle to codify the lessons that can be learned from the diagram. A guide to not only young data visualizers but to all curious people struggling to understand and explain the increasingly complex world.   

The six steps were “(1) documenting the sources and characteristics of the data, (2) insistently enforcing appropriate comparisons, (3) demonstrating mechanisms of cause and effect, (4) expressing those mechanisms quantitatively, (5) recognizing the inherently multivariate nature of analytic problems, (6) inspecting and evaluating alternative explanations.” In brief, “information displays should be documentary, comparative, causal and explanatory, quantified, multivariate, exploratory, sceptical.”