Quick Guide to Data Journalism

Quick Guide to Data Journalism

Quick Guide to Data Journalism
With a renewed focus on data storytelling in the data science industry, the approach to data science as a team sport, and big investigations carried out and published by data journalists, such as the Panama Papers, the 2016 U.S. Election Forecast or the Airbnb effect, the interest in data journalism is on the rise.

But what is data journalism exactly and how do you become one?

Today’s blog post will try to give more insights and answers to these questions.

There are many definitions of data journalism out there and it’s hard to see the forest for the trees. Some say it’s the same as data-driven journalism (DDJ), others insist in the two being different disciplines. You’ll find quite some definitions out there.

In this article, we consider data-driven journalism and data journalism as the same discipline.

When it then comes to ‘data journalism’, you might think it’s an easy concept and that coming to a definition isn’t so hard at all. After all, data journalism is journalism done with data. But what does journalism exactly mean and what is data? According to The Data Journalism Handbook, data journalism “is the new possibilities that open up when you combine the traditional ‘nose for news’ and ability to tell a compelling story, with the sheer scale and range of digital information now available”.

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However, this definition perhaps obscures the fact that data journalism is a workflow: in that sense, Mirko Lorenz’ definition, where data journalism is a “workflow where data is the basis for analysis, visualization and –most importantly- storytelling”, could be more accurate. 

You’ll often see the term CAR or Computer-Assisted Reporting passing by on your journey and it’s pretty much equal to what we nowadays call data journalism. It was the “first organized, systematic approach to using computers to collect and analyze data to improve the news”, according to The Data Journalism Handbook. 

Now that the context of data journalism is clear, you can start thinking about it takes to become a data journalist. The following section will give you more insight into what you need to do to become one and you will also find the outline of a step-by-step plan that you can follow to get into data journalism, including the best resources.

You may have read some quotes on this, such as “To become a good data journalist, it helps to begin by becoming a good journalist” (Meredith Broussard) or “Computers don’t make a bad reporter into a good reporter. What they do is make a good reporter better” (Elliott Jaspin), but what in the end do you need to become a data journalist?

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According to Scott Klein, Deputy Managing Editor at ProPublica, and Co-Founder of DocumentCloud candidates should possess 1. Journalism skills, 2. Design talent, 3. Coding acumen. That seems fairly simple, but what about the educational background, and what is exactly meant with ‘journalism skills’, ‘design talent’ or ‘coding acumen’?

For what concerns the first aspect, you might think that you need a journalism degree. Scott Klein confirms that most people on his team have degrees in journalism, but it’s certainly not a prerequisite. There are examples of data journalists that have math or computer sciences background.

And it works well, also because, according to Klein, “journalism is a natural fit for mathletes who want to make the world a better place”. However, what Klein’s looking for in candidates also gives away that the educational background doesn’t necessarily play a big part, as long as you possess the three things he’s looking for.  

And, going from the other side, it’s certainly possible to become a data science journalist if you haven’t got any technical background.

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Whatever your background is, you’ll need to consider it in your quest to acquiring the three skills you need to become a data journalist!

And these three skills don’t come easy.

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