The first treemap was created around 1990, for a reason that seems laughable today: 14 people in a University of Maryland computer lab shared an 80-megabyte disk drive, and one of them – professor Ben Shneiderman – wanted to know which individuals, and which files, took up the most space. After considering circular, triangular, and rectangular representations, Prof. Shneiderman came up with the nested, colored rectangle format we use today. (His history of treemaps is fun reading if you want to learn more.) Of course, treemaps have proven valuable for much more than determining who’s hogging the hard drive, as evidenced by the examples below.
Leaves of Green: The venerable line chart was the most common representation of Monday morning’s precipitous drop in the U.S. stock market, but we gravitated toward the treemap above, published by finviz. This visualization represents the stocks in the S&P 500, categorized by sector and sized by market cap; color represents performance. (This screenshot was taken at 9:45 a.m. PDT on Monday; look at all that red.) You can hover over any individual stock to get details, including a comparison against other stocks in its sector; simply double click to get a detailed report. You can also change the time horizon and other metrics the chart displays. It’s endlessly interactive and interesting to use.
Repping Fragmentation: Though app developer OpenSignal is best known for its wireless coverage maps, the company also does a great job of collecting non-geographic data from its apps. The treemap above is from an OpenSignal report about device fragmentation in the Android market published earlier this month. The treemap catalogs the 24,093 different types of Android devices that downloaded the OpenSignal app over just a few months in 2015. (No wonder your mobile app-developer friends look tired all the time.) The various colors represent device brands; hover over any square to see the make and model of the device. The segments of the treemap sort from large to small – upper left to lower right – but another visualization later in the report presents the same data sorted by brand. You can also see how much the market has changed from August 2014 to August 2015 with the click of a button.
All Wet: The Food and Agriculture Organization of the United Nations collects copious data in its mission to eliminate hunger, fight poverty, and support sustainability. A recent report on global irrigation uses treemaps very effectively to visualize Big Data about water use in agriculture: what irrigation technologies are in use, what sources of water are tapped, and how much geographic area is under irrigation worldwide. (The unit for determining rectangle size in the treemap is hectares, not water volume.) A click anywhere on a treemap brings up the data underlying the chart, including links to download the data for your own analysis.
Getting cultured (bonus item): Pantheon, a website created by MIT Media Lab in 2014, shows how a treemap can support the study of history. Pantheon visualizes “historical cultural production” – you choose a country, a date range, and other parameters, and the site creates a treemap showing well-known people from that country, grouped by domain. (Domains include historian, religious figure, and pirate. Yes, pirate.) Or you can flip this around: start with the domain, choose a timeframe, and discover which countries that have produced the most prominent people. In all cases, more details are a click away. The concept of Pantheon is easier to understand than to explain, so if you don’t get it from this write-up, click through and play with it.
By the way, the Custom Visualizations capability in OpenText Actuate Information Hub (iHub) enables you to create treemaps from your own data in iHub using either D3.js or Highcharts. Check out my friend Jesse Freeman’s post about using Custom Visualizations. It doesn’t specifically discuss treemaps, but it will get you started; if you have questions, please leave a comment.