As is the case with people, data journalism and journalism share more commonalities than differences. Although data-driven reporting builds on different types of sources which require other skills to interrogate, the thought process is much the same. Actually, if you zoom out enough, you’ll find that the processes are almost indistinguishable.

Known Unknowns

At its core, journalism is the business of making known unknowns into known knowns. The concept of knowns and unknowns was popularized by the US Secretary of Defense Donald Rumsfeld in 2002. At the time there was a lack of evidence that the Iraqi government had supplied weapons of mass destruction to terrorist groups. During a press briefing over the matter, Rumsfeld said:

Every journalistic process comes down to moving pawns over the matrix of knowns and unknowns. All journalism starts with a question—or, to follow the said matrix, with a known unknown. (You know there is something you don't know, hence the question.) When bootstrapping to move from question or hunch to publication-ready story, the ideal route is to “simply” move all pawns from known unknowns to known knowns. But as every journalist will tell you, reality tends to differ. While researching—either by interviewing people or examining documents or data sets—you are likely to find things you were not aware that you didn't know (unknown unknowns), that require answers, too.