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Data journalism: The good, the bad and the ugly

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Data journalism: The good, the bad and the ugly

Sandra Crucianelli | July 03, 2012

We live in a world where almost everything is expressed in numbers. If you're a journalist who wants to follow the data trail, you have to be able to tell people how this enormous cobweb of numbers affects their lives.

To get started with data journalism, here are some skills you need and challenges you will face.

  • Data journalism requires knowledge of general subjects usually far removed from conventional journalism. You need to know how the public administration works, how to interpret laws, decrees and ordinances. If a journalist doesn't understand how the institutions of his or her country work, the data trail can dead end quickly.

  • Fluency in English. Most of the frequently used tools in data journalism are only available in English. For now, that leaves a large gap between journalists who can access these resources because of their language abilities and those who can't.

  • Online search skills. Using Google the usual way won’t cut it. You need to take advantage of advanced searches by format, by subject and by date, but also, given the lack of national initiatives for open data, know which official sites hold data.

  • Spreadsheet skills. Journalists need to know how to process numbers in Excel or a similar software program.

  • Math and statistics knowledge, both descriptive and inferential. A number-phobic journalist will run into trouble analyzing public budgets, taxes or other topics such as crime and pollution.

  • Data journalism training is mostly DIY. With a few exceptions, most university journalism schools aren't teaching data journalism, so you'll be investing in learning by doing.

  • Projects can be time consuming and costly. You'll have to access dozen, if not hundreds or thousands of forms, texts and graphics. Sometimes you have to fall back on the work of programmers to design applications that can capture data from web pages.

  • Remember the three basic parts of data journalism stories. In addition to the story, the project should provide readers with background documents, explain the methodology so the work can withstand peer review and include an adequate visualization of the data.

  • Remember you won't always find what you're looking for. You'll have to read tons of records, mountains of documents and make phone calls that no one will return in an attempt to open doors that may stay closed. Sometimes there is no story in the data, though it doesn't happen often.

Now that you know the worst of data journalism, you're better prepared to face the challenges ahead. This is a good indicator of success because in data journalism, it's not the people with luck, good connections, or brilliant minds who shine, but those who persevere. There is the difference.

A version of this post originally appeared in Spanish on La Nación Data and is posted on IJNet with permission. It was translated into English by Maite Fernandez.

Sandra Crucianelli is a Knight International Journalism Fellow, an investigative journalist and instructor, specializing in digital resources and data journalism. She is the founder and editor of Sololocal.info, an online magazine that provides hyperlocal news from Bahía Blanca City, Argentina.

@spcrucianelli

Image: Morguefile.