Engaging figures

Some visualizations resonate while others are forgotten. Why that is can be understood with the principles of creating ‘proximity’.

Scientific figures are often presented as neutral displays of evidence that accurately and truthfully report numbers. But influential visualizations are memorable not for their accuracy, but because they make information feel relevant1. Darwin’s sketch of the tree of life, Snow’s cholera map and, more recently, Ed Hawkins’ climate stripes use different ways to make data significant to their readers: Darwin connected humans with direct lines to animals, making the relatedness of all species immediately apparent; Snow mapped individual cholera deaths to houses in Soho, connecting an epidemic to a known neighborhood; and Hawkins’ climate stripe tool allows people to visualize climate change where they live. Each example reduces the distance between the data and its audience. How this is achieved can be described by the theory of proximity: a framework from human-centered computing2,3 that distinguishes seven dimensions of proximity in data visualizations. Below, we discuss how these principles of proximity are used and useful in biological figures.