Category Archives: databases

FAQ: Do you need new ethics for computational journalism?

This latest post in the FAQ series answers questions posed by a student in Belgium regarding ethics and data journalism.

Q: Do ethical issues in the practice of computational journalism differ from those of “traditional” journalism?

No, I don’t think they do particularly – any more than ethics in journalism differ from ethics in life in general. However, as in journalism versus life, there are areas which attract more attention because they are the places we find the most conflict between different ethical demands.

For example, the tension between public interest and an individual’s right to privacy is a general ethical issue in journalism but which has particular salience in data journalism, when you’re dealing with data which names individuals.

I wrote about this in a book chapter which I’ve published in parts on the blog. Continue reading

That massive open online course on data journalism now has a start date

In case you haven’t seen the tweets and blog posts, that MOOC on data journalism I’m involved in has a start date: May 19.

The launch was delayed a little due to the amount of people who signed up – which I think was a sensible decision.

You can watch the introduction video above, or ‘meet the instructors’ below. Looking forward to this…

Why open data matters – a (very bad) example from Universal Jobmatch

Open Data stickers image by Jonathan Gray

Open Data stickers image by Jonathan Gray

I come upon examples of bad practice in publishing government data on a regular basis, but the Universal Jobmatch tool is an example so bad I just had to write about it. In fact, it’s worse than the old-fashioned data service that preceded it.

That older service was the Office for National Statistics’ labour market service NOMIS, which published data on Jobcentre vacancies and claimants until late 2012, when Jobcentre Plus was given responsibility for publishing the data using their Universal Jobmatch tool.

Despite a number of concerns, more than a year on, Universal Jobmatch‘s reports section has ignored at least half of the public data principles first drafted by the Government’s Public Sector Transparency Board in 2010, and published in 2012. Continue reading

Saving the evidence in Ukraine: collaborate first – or you won’t be able to ask questions later

YanukovychLeaks screengrab

“The reporters then did something remarkable. They made a decision to cooperate among all the news organizations and to save first and report later.

“It wasn’t an easy decision. But it was clear that if they didn’t act, critical records of their own country’s history could be lost. The scene was already filling with other reporters eager to grab what stories they could and leave. In contrast, the group was joined by a handful of other like-minded journalists: Anna Babinets of Slidstvo/TV Hromadske;  Oleksandr Akymenko, formerly of Forbes; Katya Gorchinska and Vlad Lavrov of the Kyiv Post. Radio Free Europe reporter Natalie Sedletska returned from Prague so she could help, and others came, too.

“… In the tense situation that characterizes Ukraine, conspiracies form quickly. To demonstrate their transparency, the organizers quickly moved to get documents up. By early Tuesday, nearly 400 documents, a fraction of the estimated 20,000 to 50,000 documents, had been posted. Dozens more are being added by the hour.”

Drew Sullivan writes about Yanukovych Leaks.

FAQ: Big data and journalism

The latest in the series of Frequently Asked Questions comes from a UK student, who has questions about big data.

How can data journalists make sense of such quantities of data and filter out what’s meaningful?

In the same way they always have. Journalists’ role has always been to make choices about which information to prioritise, what extra information they need, and what information to include in the story they communicate. Continue reading

New ebook now ready! Learn basic spreadsheet skills with Data Journalism Heist

Data journalism book Data Journalism Heist

I’ve written a short ebook for people who are looking to get started with data journalism but need some help.

Data Journalism Heist covers two simple techniques for finding story leads in spreadsheets: pivot tables and advanced filters.

Neither technique requires any formulae, and there are dozens of local datasets (and one international one) to use them on.

In addition the book covers how to follow leads from data, and tell the resulting story, with tips on visualisation and plenty of recommendations for next steps.

You can buy it from Leanpub here. Comments welcome as always.