Some Misconceptions about Data Journalism

Some Misconceptions about Data Journalism

Some Misconceptions about Data Journalism

In the past few years, a new discipline in journalism is slowly getting more and more followers — a discipline commonly known as ‘data journalism’. These so-called ‘data journalists’ are usually envisioned as the younger, tech savvy journalists, ones that are not afraid to analyse data, understand how computer code works and simply love these colourful and detailed visualisations.

On the other end of the scale are the non-data-journalists . We usually imagine them, still using a phone and Rolodex as they simply don’t get email — and the last technological leap they made was when the mechanical typewriters were replaced by computerised word processors.

Moving away from these simplistic (even stereotypical) dichotomies into a better understanding of what a data journalist actually looks like, will do justice to the actual hard-working data-journalists out there as well as take this movement forward and make it more open and inclusive.

Let’s begin with the ground truth about the journalism trade: Journalism is all about telling a story, and the best stories are ones that revolve around humans, not numbers.

This basic fact was true a hundred years ago, and is not about to change — even if technology does. For this reason, the best journalists will always be the masters of words; those who have the best understanding of people and what makes them tick. It is the unfortunate truth that the benefit of knowing how to work with data will always come after that.

Read Also:
How Machine Learning and Big Data Drive the Bottom Line

Don’t get me wrong, there’s certainly a place for all the ‘visualisation-oriented journalists’ (or “visi-journalists”). That’s because sometimes the dataisthe story. Sometimes, the fact that some new data is available to the public is newsworthy. Sometimes, some hard-to-find, hidden links in a large dataset are the scoop. Sometimes, a subject is too technical and complex that only a super-interactive visualisation is the only way to actually explain it. But most times, this is not the case.

So we have on one end of the spectrum, that old school journalist with her Rolodex, holding a precious network of high-ranking sources. On the other extreme, a journalist that also codes and wrangles data, trying to find a corruption case by sifting through publicly available data using a custom made Python script. But in between these two extremes, lies a vast range of hard-working journalists, reporting on the day to day happenings in politics, economy, foreign affairs and domestic issues. These journalists don’t have any sources in any high places, and have never heard of Python.

Read Also:
Health Catalyst launches free open source machine learning and artificial intelligence tool

Yet, this majority of journalists is mostly ignored by the data journalism movement — which is a shame, as these are the ones most likely to benefit from it and advance it the most.

Flashback to five years ago — I’m one of the few founding-volunteers of an open-data NGO in Israel, “The Public Knowledge Workshop”. One of our first projects was called “The Open Budget” — a website who took the publicly available (but hard-to-understand) national budget data and presented it in a feature-rich, user friendly website.

At that time, we tried to meet with as many journalists as we could to tell them about the new budget website — and not many would spare an hour of their busy schedules for some geeks from an unknown NGO. We would show them how easy it was to find information and visualise it in an instant. Then we would ask them whether they might consider using our website by themselves for their work.

Read Also:
Five Questions Publishing Leaders Need to Ask About Metadata

A common answer that took me by quite a surprise always went along the lines of “That is very nice indeed but I don’t need your website as I have my sources in the Ministry of Finance and they get me any data I need”. The fact that the data was lying there, within a mouse-click’s reach, and they still wouldn’t use it — simply baffled me. It took me some time to understand why it made perfect sense.


Chief Data Officer Europe
20 Feb

15% off with code CDO7W17

Read Also:
Open data on Australian companies could be the best response to tax avoidance
Predictive Analytics Innovation summit San Diego
22 Feb

$200 off with code DATA200

Read Also:
Mobile is still the safest place for your data
Read Also:
Will financial analysts lose their jobs to intelligent trading machines?
Big Data Paris 2017
6 Mar
Big Data Paris 2017

15% off with code BDP17-7WDATA

Read Also:
Open Data Dashboard Helps Track Sustainability in Austin

Leave a Reply

Your email address will not be published. Required fields are marked *