A Q&A with our stats journalism data viz award winners

A team of journalists from Zeit Online won this year's 'Data visualisation' category in the 2020 RSS Statistical Excellence in Journalism Awards. Their winning entry, The Millions Who Left , used interactive graphics to show migration between east and west Germany since 1991. It was described as 'superb' by the judges.

We spoke to Elena Erdmann & Julius Tröger from the team about their approach to data journalism.

 

How do statistics help you tell a good story?/ In what ways does data visualisation help better tell a story? 
Every journalist profits from a basic understanding of data and statistics, especially since more and more data is collected and accessible online. Thus, for most journalistic investigations, checking the available data helps us to form an informed opinion about a topic. 
 
Data visualisations provide insight at a glance or breaks down the story to every reader with interactivity. It allows the journalist to address both those who are only superficially interested and the experts, who can use interactivity to dig deeper. 
 
What do you think is the most important thing to bear in mind when reporting on statistics?   
It’s complicated. As data journalists, we are usually not experts in the topic we are researching, even if the data provides interesting insights. While working with data, it is easy to mistake correlation for causation or to form a conclusion based on biases in the measurement process. Even official statistics can contain mistakes. At the same time, data can provide the reader with a false sense of certainty. Therefore, when reporting on data, it is important to consult with experts, to double-check the data and to highlight uncertainties. The challenge is then how to visualise possible uncertainty. 
 
What can statisticians do to help journalists in putting numbers into context for their readers?   
As data journalists, we cooperate and consult with scientists and statisticians on a daily basis. Often, this cooperation is much closer than in traditional reporting. Many of the scientists we spoke to have been extremely helpful and supportive. One thing that could still be improved is the accessibility of scientific data. Scientists sometimes do provide the data to their studies in a machine readable format which makes it easier to process, but this is still not the norm. 
 
Has the Covid-19 pandemic made readers more stats-savvy?   
Yes, most certainly. Never before have data and statistics played such an important and prominent role in the public debate: For months, readers have been checking the infection numbers on a daily basis, they are discussing topics such as the R-value and test sensitivity and specificity. Even charts with a logarithmic scale have been seen by a broad audience. We are confident that the pandemic has increased public data literacy, but at the same time all the numbers might also have led to confusion, at least for some people. 
 
How do you decide which numbers to use and which to leave out – do you have a limit to the amount of stats you use in any given story?  
There is no fixed limit to the amount of stats in any story. However, we always aim to make it as easy to understand as possible. Our readers should not feel like they are tediously studying a statistical analysis—they should get to the main takeaways as soon as possible. Yet, it is important to be clear and transparent in the methodology. Visualisation often helps to give a better understanding of complex topics. If it is just a number in a text, a bar chart or a map with animated edge-bundeled flows like in 'The Millions Who Left'. 
 
The Economic and Social Research Council funds research on the social and economic questions facing us today. If you could choose a question to research, what would it be?  
Climate change. This topic affects all facets of our life and we have to work as closely as possible with scientists to inform the public. 

Read more about the winners of the 2020 Statistical Excellence in Journalism Awards in our announcement.

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