In information visualization and computing, treemapping is a method for displaying hierarchical data by using nested rectangles.
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Treemaps display hierarchical (tree-structured) data as a set of nested rectangles. Each branch of the tree is given a rectangle, which is then tiled with smaller rectangles representing sub-branches. A leaf node's rectangle has an area proportional to a specified dimension on the data. Often the leaf nodes are colored to show a separate dimension of the data.
When the color and size dimensions are correlated in some way with the tree structure, one can often easily see patterns that would be difficult to spot in other ways, for example, if a certain color is particularly relevant. A second advantage of treemaps is that, by construction, they make efficient use of space. As a result, they can legibly display thousands of items on the screen simultaneously.
To create a treemap, one must define a tiling algorithm, that is, a way to divide a rectangle into sub-rectangles of specified areas. Ideally, a treemap algorithm would create rectangles of aspect ratio close to one, would furthermore preserve some sense of the ordering in the input data, and would change to reflect changes in the underlying data. Unfortunately, these properties have an inverse relationship. As the aspect ratio is optimized, the order of placement becomes less predictable. As the order becomes more stable, the aspect ratio is degraded.
To date, six primary rectangular treemap algorithms have been developed:
| Algorithm | Order | Aspect ratios | Stability |
|---|---|---|---|
| BinaryTree | partially ordered | high | stable |
| Mixed Treemaps[2] | ordered | lowest | stable |
| Ordered | partially ordered | medium | medium stability |
| Slice And Dice | ordered | very high | stable |
| Squarified[3] | unordered | lowest | medium stability |
| Strip | ordered | medium | medium stability |
In addition, several algorithms have been proposed that use non-rectangular regions:
Area-based visualizations have existed for decades. Mosaic plots and Marimekko diagrams both use rectangular tilings to show joint distributions, for example. The main distinguishing feature of a treemap, however, is the recursive construction that allows it to be extended to hierarchical data with any number of levels. This idea was invented by University of Maryland, College Park professor Ben Shneiderman in the early 1990s.[1] Shneiderman and his collaborators then deepened the idea by introducing a variety of interactive techniques for filtering and adjusting treemaps.
These early treemaps all used the simple "slice-and-dice" tiling algorithm. Despite many desirable properties (it is stable, preserves ordering, and is easy to implement), the slice-and-dice method often produces tilings with many long, skinny rectangles. In 1994 Hascoet & Beaudouin-Lafon invented a "squarifying" algorithm, later popularized by Jarke van Wijk, that created tilings whose rectangles were closer to square. In 1999 Martin Wattenberg used a variation of the "squarifying" algorithm that he called "pivot and slice" to create the first Web-based treemap, the SmartMoney Map of the Market, which displayed data on hundreds of companies in the U.S. stock market. Following its launch, treemaps enjoyed a surge of interest, especially in financial contexts.
A third wave of treemap innovation came around 2004, after Marcos Weskamp created the Newsmap, a treemap that displayed news headlines. This example of a non-analytical treemap inspired many imitators, and introduced treemaps to a new, broad audience. In recent years, treemaps have made their way into the mainstream media, including usage by the New York Times.[5][6]