The moving picture
Writing about data visualizations is one thing. Writing about an interactive data visualization is an entirely other, complicated task.
As a general rule, you should focus on your audience and what they stand to learn from the activity.
Think of your visualization as a playground. Before they enter, there should be some rules, expectations, or structure for play. Of course, this isn’t a requirement. But if you want your audience to feel as though their journey is supported, you can take some basic steps to ensure they get valuable information from your viz.
- Explain how the viz was created. What technology did you use? What data did you use?
- Criticize the logic you used when constructing the visualization. In the visualization example below, we use CO2 emission per capita and stop there. It is our job as data narrators to explain to the audience why this is a simplistic view of the larger CO2 emissions situation, and why it’s a valuable first step before diving deeper into the topic. Always explain the constraints of your work.
- Direct usage of the tool. While you want your audience to discover meaning through play, you should explain how the visualization works. Your job is to facilitate learning.
- Develop vocabulary. Remember that every moment of engagement is an opportunity to help your audience learn language that will help them better conceptualize of large data theories.
And now, the VIZ
In the visualization below, we’re using CO2 data from the World Bank to compare total CO2 emissions per capita of each country versus their annual CO2 emissions over time. The main strengths of this visualization is that it allows us to see total CO2, but also which countries have improved overtime. As a first step into data analysis, this will help us understand where common misconceptions come from. For example, Qatar is clearly the larger CO2 emitter. But it’s important to remember that this is per capita (weighted by population). Also, if you click on Qatar and isolate its emissions over time, you’ll see that the country has improved its emissions greatly. Now, we begin to see a fuller picture.
In the visualization below, click on the lines in the bottom viz, or the bubbles in the top viz, and try to find which countries have improved and which countries have worsened their CO2 emissions.
