Hans Rosling, the master of data storytelling, once explained that data visualization is like looking at musical notes, but you will not hear music just by looking at them. This great metaphor in a simple way differentiates data visualization from data storytelling.
When I think about how data serve us, they are only a bridge between our imagination or expectations and reality. They need a guide who reveals their shape and meaning to unlock their full potential. Everything depends on how comfortable we feel with numbers. Our main goal when we work with data shouldn’t be presenting numbers but highlighting the situation behind them, problems to address or opportunities we can leverage. Some people don’t have a natural instinct to read between data lines, while some do. Some people need a guide some don’t.
But at the beginning, I would like to dig into concerns about the differences between data visualisations and data storytelling. Many times, both terms are used interchangeably which is misleading. The biggest distinction between those two terms is that the first one focuses on displaying data in readable form, and the second is communicate insights and conclusions.
Data visualisation is simply displaying data. Our intention here is not to communicate information but to show data to receivers and give them the possibility to build their insights and conclusions. Data storytelling, on the other hand, is something totally counterparty. We, as authors, want to sell receivers one of the possible stories around a particular data set. However, that story can be more or less ethical or trustworthy, but I won’t touch that sensitive topic here – to go deeper into ethics in presenting data read this post.
Of course, like in the marketing world, we have some tips and tricks to sell our stories.
Narration is a game changer in communicating data findings. It is the heart of data storytelling. One data set can contain dozens of stories. What we pick up and how we tell about them depends on our goals. Storytelling is a very successful tool in communication or marketing. Humans crave stories from the beginning of our species. This is our natural way of passing messages mainly because it activates many parts of our brain like language processing, movement processing, and emotion processing. Due that engaged processes we can remember things easier.
How we frame the story will affect how this story will be displayed. Yes, displayed. In data storytelling, we use all visual attributes to get a message across to our audience. The main part is to properly link the message with what is presented. We use colours, shapes, positions, and text to focus or guide the audience’s attention.
Let’s get through the basics of visual narration.
In the above picture, the same data set is displayed. However, with a totally different intention. On the left side, data is presented by categories (social interactions) on the timeline (age). Interpretation is on the audience’s side. The audience can craft their own stories based on their feelings, expectations, and experiences.
On the right, the data set is filtered by author lenses. The author focuses only on one of the categories – time spent alone and presents the positive aspect of the fact that when we age, we have more time for ourselves. To promote this thesis, she exposed the category “Alone” with orange colour and combined the rest of the categories into one and painted them with neutral grey colour. Due to this technique, the category “Alone” is pushed out to the foreground for paying the viewers’ attention. Furthermore, the category “Alone” is placed first from the visualization baseline, so we can see the increasing trend over time. A thoughtful title is important as well to influence how we interpret the whole visualisation.
Narration over narration
The author’s thesis presented above is positive. Can we turn it into a negative one? Let’s compare below two examples.
Again, the same data set is used. By implementing various techniques, we can play on people’s emotions to evoke different outlooks of the presented information.
On the left, the bright, optimistic colour orange is used to emphasise the advantages of the situation. However, the example on the right gives us another impression. Blue colour, often joined with sadness, bars falling as streams of rain from the sky upon someone’s head, and the pessimistic title leaves us without a doubt that being alone when you get older is nothing pleasant.
Is it manipulation? I didn’t change here data set or axis scale. I just move viewers’ focus and show another perspective. Nevertheless, I can leave the audience with counter feelings.
So, I’ll repeat here once again, it is your decision how to sell your data storytelling.