Accompanying the report on a railway feasibility study for the Irish Railway Commissioners in 1837 was an atlas which contained maps "drawn to a new design" by Lieutenant Henry D. Harness of the Royal Engineers. The maps showed lines whose widths were proportional to the figures being represented, in this case the average number of people travelling each week between two points (with the data being supplied mostly by the local police).
Harness presented 3 maps which have the following salient features:
1. Map showing the relative number of passengers in different directions by regular public conveyances,
2. Map showing the relative quantities of traffic in different directions,
3. Map showing by varieties of shading the comparative density of the population,
Harness's maps featured in a presentation on the advancement of science prepared for the Statistical Society of London in 1838 by W.R. Rawson. They were referred to as "beautiful maps, which place before the eye a picture of the country representing the traffic of its population".
Sankey diagrams, named after an Irish engineer, Matthew Sankey, who published a diagram in 1898 showing the energy flows in a steam engine is considered to be the first of its kind of the diagrams which make it easy to see the dominant flows within a system and essentially help us to visualize the data.
From the above post, it appears that first representation of data in this way was even earlier than Minard's diagram from 1869. Harness diagrams are evidently first of its kind, which illustrates the flow map of the passengers in the Ireland railways.
Well, that is the example from the history of data visualization, which is one of the milestones helped in setting the trend of visualizing complex data patterns and flow of data.
Following is an interactive data visualization example, which visualizes world sex ratio for total population and also several age categories.
Try the above chart, by hovering the mouse over different countries, and also select the various options in the dropdown box, to change the age category. There is also a "key" given to interpret the color coding.
I think its an excellent example of data visualization. It is amazing how so much amount of data, is elegantly organized, such that users can find what they want, by just hovering the mouse on the country they are interested in. Not only that, the above chart also gives a quick perspective of the distribution of sex ratio across the world by making use of color coding.
References:
- Economist Data Visualization, http://www.economist.com/blogs/dailychart/2011/07/data-visualisation
- Robinson, A. H. (1955). The 1837 maps of Henry Drury Harness. Geographical Journal, 121:440-450
- InfoVisualization Wiki, http://www.infovis.info/
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