Why do we love to organise knowledge into trees?

Jonathan Keats:

IN THE early 1990s, 14 computer scientists at the University of Maryland were sharing an 80-megabyte hard drive. The drive was often overloaded, with expendable files taking up space in neglected sub-directories. Finding anything was like blindly reaching along all the branches of an overgrown tree.

There had to be a better way, thought departmental professor Ben Shneiderman. So he wrote a six-line algorithm that visualised the drive as a rectangle. Vertical divisions split the rectangle into smaller ones, representing directories, which then subdivided horizontally to show subdirectories. Each of the smallest rectangles corresponded to a megabyte of storage space, so free space was visible at a glance.

He called his invention a “treemap”, and it was adopted by computer labs around the world. It soon found other uses, such as in an interactive chart of stocks and shares, still popular today.

These hierarchical treemaps “epitomize the recent growth of information visualization”, writes Manuel Lima in The Book of Trees: Visualizing branches of knowledge. And as big data engulfs labs and lives, the need for such powerful visualisations will only increase.