This is the second post of the Data Storytelling Examples series. Read the first post to learn more about my hints to effective data storytelling.
Today I review a fantastic #IronViz2020 by Simon Beaumont. I always enjoy exploring Simon’s data stories because they’re very well-structured.
Here are the rules on how to learn data storytelling with my Data Storytelling series:
- Go to the data visualization
- Identify story features in the data viz (character – context – conflict)
- Keep reading my tips! 👇
Data Story Examples: Human Development Index is your Hero
As a starting point, Simon gives a good introduction to the United Nations Human Development Index (HDI). You get enough information to interpret the data accurately.
HDI consists of 3 metrics:
- long and healthy life
- being knowledgable
- living standards
Then you learn more about the HDI. Basically, you get the answer to When- Where- and How-questions. Visuals explain to you:
- the evolution of the HDI in the 21st century
- how it differs in geographical regions
- how political systems and conflicts influence the hero
- what drives the HDI by country. Some countries are more income-driven, others more education-driven.
Data Story – Conflict in Human Development
Many of the graphs evoke emotions and acknowledge inequity around the globe.
Take a look at the graph What is the impact of CONFLICT?
The small multiple line charts explain three civil wars. You can easily compare four threads:
- HDI
- life expectancy
- education
- gross national income
Some of the indicators contain a benchmark on the global level. Comparing the data points brings some drama to your brain. You feel involved in the story, and you want to scroll down further and further learn new chapters of the story.
Data Story Context
Simon explains terms using simple language. Everyone is on the same page once reading the story.
The introduction consists of the text and a graph that illustrates three components of the HDI. Comics and book readers are satisfied 🙂
One picture is worth a thousand words.
Albert Einstein
That is so true when you need to digest a massive dataset.
The data source details in the introduction look untypical. Usually, you see the data source details in a footnote.
Still, I like how Simon includes this information at the beginning of the Tableau viz. It’s sleek, not so eye-catching and gives trust. When I read a data story, a question cross my mind several times “interesting, where does the data come from?”
Data Storytelling Structure
Great design is visible in the colour coding and legend placement. Even though the place for the legend is rebellious. It breaks up the main rule we read in F-shape form. Still, it’s not so distracting thanks to one little visual trick.
Throughout the story, you follow a line with dots that divides each new section. It’s a very clever and unique approach. Why does it work?
- You receive guidance where a new chapter is about to start
- It splits informative guidance (labels, legend) from “the meat” (content, graphs, commentary).
- Finally, you end up with the essence of the visualization. You dive into the exploration phase with lots of yummy parameters and colour-coding!
Each section with a title, commentary and graph suit screen view. That’s very audience-empathetic.
Most importantly, scrolling determines the story flow.
Tableau areas of improvement
This data viz works very slowly on my device. Achieving such a great data visualization doesn’t go hand in hand with application performance.
