Data is all around us. We can access it with greater ease; hence, the recent boom in “data-driven journalism.” Data is used to structure the story inside and out, as a tool for verification and presentation, and everything in between. Many news organizations around the world are starting to publish stories and cover beats that can be better told through data.
The same goes for our #urbanmobilityCH newsroom, where we will be publishing two stories driven by data. We invited Sylke Gruhnwald, head of the data team at NZZ (Neue Zürcher Zeitung), one of Switzerland’s oldest and most widely circulated newspapers, to a Google hangout with us and asked her how her team works with data and how we can use data in our stories. Here are some key takeaways:
Keep an open mind and follow the data
Fostering an open mind is critical to developing a data-driven story. Since it is quite possible that the data will prove the reporter’s initial thesis wrong, data journalists need to be first and foremost aware of falsification and flexible in their approach to the data. Don’t go in fixated on your opinion. Instead, listen to the data and see where it is heading. It’s a procedure not too distant from interviewing: “Not only can you interview a person, but you can also ‘interview’ a database—for example, running queries,” Gruhnwald said.
Beyond knowing when to admit falsification, a general open-mindedness in outlook encourages inspiration for new stories and provides direction for finding data sets. Gruhnwald recommends that those interested in data journalism keep updated with a network of newspapers, magazines and journals. Or scan existing data sets for possible discoveries. There is plenty of information available and many stories that are not yet told. It’s only a matter of “being out there.”
Be data literate
A data-driven story demands data literacy. A data journalist must know how to read and interpret the data, and how to locate it within the greater picture.
Basic math and statistics are useful to any journalist, no matter how far removed the topic is from the realm of quantitative knowledge. “It doesn’t matter if you cover culture, because you might cover the finances of your local theater, and then you should be able to read a checks and balance sheet, for example,” Gruhnwald said.
And data is not only figures (numbers) but also every format that can be read by a computer, whether that be images, photography or pdf’s. For example, Gruhnwald’s team helps NZZ’s reporters recheck documents and their history by going through their metadata.
Data literacy is very important for #ddj. The stereotype that most journalists were bad in math should not be valid.
— Student Reporter (@oikosReporter) March 25, 2014
The beauty of visualization
Sometimes it makes more sense to keep data within the context of the story, but other times data can be visualized as an effective, additional feature of the story. In the latter case, the data needs to be presented clearly, thoughtfully and accessibly. As important as the story is, the presentation of the data also needs to speak to readers. Having an eye for design helps, as does learning code, so journalists should remember to collaborate with designers and developers and take advantage of their expertise.
When data-driven stories are published on the Web, readers and reporters have a special opportunity to interact within the medium of the data. It is possible that the reader may look at the same data, reformulate it and produce a different angle that is counter to the reporter’s.
Data is Money and Time
Although data can be freely obtained from many places (a statistics bureau, social media APIs, some universities and companies), interesting data is often locked up, either financially or behind legal walls. Sometimes, accessing data can even be a political game. NZZ’s feature on lobbyism (link in German) required data that was tied up in thousands of euros, way beyond the newspaper’s budget for the story. But by reaching out and building relationships, NZZ was given access at a lower rate. “It all started off in our haggling and establishing a good relation with a company that supports it, to open up the commercial registry data,” Gruhnwald said.
After gaining access, working with data also requires time to clean and analyze it. This can take months of poring over numbers and merging different sources to produce a database for one topic. Especially when it comes to dealing with personal, individualized data, data journalists need to be extra-cautious in making sure that they have read the data correctly.
Data journalism, at the very least, provides writers with more material to work with, and at its best, it produces stories with concreteness, a larger context and a sense of authority.
While data analysis can be fun and addictive, it needs a good research question as well as awareness of and sensitivity to the inherent bias in interpretation. Just like people, data can also be biased. “Figures might seem as if [they are] sole facts, but it always depends on who actually released them, how did they come up with that certain figure, how do you as a recipient choose them and so forth. Data doesn’t equal facts,” Gruhnwald said.
Watch the full recording of the google Hangout here.