The surge of big data, on the backs of the Facebook, Gmail,
and Instagram generations, has led to an explosion of information available
from every corner of your life. It’s here, it’s most certainly going to stay,
and it’s something journalists have been quick to catch on to. Learn it. Use
it. Love it.
But not all data journalism is created equal.
Take this
article from The New York Times. It provides a good example of how data
journalism can help tell a story; in this instance by overlaying drab
statistics against a map. But if you are at all interested in the primary
elections or in New York, you'd probably be interested in the article and
statistics even if it were presented as a spreadsheet rather than splashed onto
a map. It is content that helps tell a story, allowing readers to better visualize
that stupid sod from five blocks down electing that idiot of a candidate
guaranteed to run this country into the ground! compare how voters in a
particular area made an informed political choice.
However, data journalism truly shines in telling stories
that would otherwise be impossible if told through another medium. This Bloomberg
article on the correlation between marriage and careers provides a good counterexample: it combines an interactive
chart with an interesting premise (it's essentially a horoscope grounded in
statistics), inviting readers to explore a side of statistics that would
otherwise be ignored. Can you imagine reading through a boring table of figures
and facts discussing marriage statistics? In this instance, the content is the story.
The ultimate purpose is to inform and engage the reader. (After
all, what is the point of journalism?) The most successful data journalism provides
a simple reference for a complex subject and is inherently interactive, engaging
the reader and by extension, “sticking” in his head. But perhaps most
importantly, data journalism should be used to present information that would
otherwise be unpalatable or incomprehensible without the aid of a visual.
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