What is data journalism?
It is no longer possible to communicate with people in the language of statisticians and financiers. Studies have shown that only 5% of people remember bare numbers, while the vast majority (65%) focuses on stories.
The New Black is data-driven stories or data storytelling. The authors build such texts around key numbers and frame them with the story of a real character or phenomenon. And readers can easily retell the story to their friends during a break over a cup of coffee.
How to find a story in data?
Okay, let’s say you have a dataset open in front of you. What do you do next? How do we figure out what the numbers are telling us?
The most effective way to figure out what the data are telling us is not from the data itself, but from assumptions about what the data can tell us. These assumptions are called hypotheses.
Let’s look at the example of a study about the shortage of cancer drugs in Russia, for which I received the Redkollegia award for independent journalists.
The dataset included information about how the regions procure drugs for the treatment of blood cancer in children (date, contract amount, region customer, executor, trade name of the drug and its quantity).
So what questions can be asked about this data?
The first logical question is: how many packs were purchased by each region. But after sorting out the regions by the number of such purchases, I found that half of them did not take place because no one submitted an application.
The question arose: why is this happening?
I turned to the experts. It turned out that the prices for drugs are so low that it is simply unprofitable for companies to produce them. That is, pediatric oncology turned out to be a commercially unprofitable industry.
How do you write a data story?
Sounds good, but how do you write a story like this anyway? Here are four tips:
- Find the story you want to tell. It can be anything from how the U.S. uses its land to why the pockets on women’s jeans are made smaller than those on men’s jeans.
- Think about what data would work for this story and where you could get it: from public sources or requesting it from someone.
- Okay, the data is there. What’s interesting about them? Look for anomalies, like in the cancer story.
- Think of the reader. Show what the numbers say in different ways: with visuals, with words, or with vivid conclusions.
Don’t be afraid to improvise, and your story definitely won’t go unnoticed.