Telling data stories with maps
Simple visualizations make large amounts of data easy to understand at a glance, allowing readers to engage more directly with the data. Choropleth maps are an iconic example of presenting data using colour intensity to illustrate prevalence rates. For example, blue signifies the high chance a child raised in the bottom fifth rose to the top fifth while red shows low chances.
But the process of making these maps is not straight-forward for non-developers. The journalist needs to evaluate the amount of detail given and whether the designer followed these steps in deciding what data to include in the map.
Here are the main steps to follow on any infographics project
1. Define the focus, the story, the goals
2. Do some preliminary research
3. Choose graphic forms according to 1
4. Sketches and storyboards; structure the information
5. Complete the research and write the copy
6. Create the graphics, maps and diagrams
7. Put it all together
In other words, when looking at health indicators and comparing stats between different regions, the amount of detail should add more depth to the colours of the map. It should compare data for related subjects in the pop-out windows for each region and include a headline that explains what the audience should conclude from the map. The report and the year from which the data has been sourced should be clearly identified as in this example of mapping England’s health data.
Life expectancy by UK health areas: what’s it like near you?
In the above example, UK’s life expectancy is mapped using Google Fusion Tables. Red signifies regions with high rate of life expectancy, while green represents low rate of life expectancy. From the filter provided, the reader is able to see the life expectancy of men and women during the years 2007 to 2009.
Excel is used to analyze raw data before mapping. The first row needs to correspond with artificial or conventional boundaries (countries, regions, counties, etc.) and the data needs to be considered evenly distributed across each one of those enumeration units.
Using map and bar chart the reader can filter to get information interested in. But once the choropleth map has been built it becomes easier to distinguish rates of a certain indicator by region.
Tableau Public or Google Fusion Tables are free programs used to map data. If existing map of the geographical boundaries you are interested in does not exist, it is important to develop a customized map and saved in kml format.
However, there are two things that have to be considered before creating the choropleth map graphics: the number of enumeration units (regions) that need to be displayed and subdivisions (classes) going to be used to divide the data set. Design of good choropleth maps include clear use of legend and visibility between colours, so as to be easily distinguishable by the viewer.
The regions with darker colors shall represent higher rates and vice versa for the lighter regions. Popup menus will be used to show text or graphical detail of the variables.
When using choropleth maps as with the example of mapped England’s health data, it is important to limit the amount of popup menu data. The data needs to be selected carefully to make it easy for the reader to understand the purpose of the information. There is need to narrow down on the key message and data sets that support it.
By using Google Fusion Tables, the reader is able to see data variations by selecting any region on the map and a popup menu will appear to show more information.
As visual journalists, it is important to pay keen interest to details because they make a huge difference in the audience’s understanding.
