The last 2 months of 2014 saw a return to regular blogging after some quiet periods earlier in the year
2014 was the 10th anniversary of the Online Journalism Blog, so I thought I’d better begin keeping track of what each year’s most-read posts were.
In 2014 the overriding themes for this blog were programming for journalists, web security, and social media optimisation. Here are the most-read posts of the year, plus one surprisingly popular new page with some background and updates. Continue reading →
Yesterday I spoke at the BBC Data Day: an event bringing together people at the BBC interested in data-related issues, techniques and tools. During the question and answer session following my talk one person mentioned a common reason why he wasn’t using data journalism techniques:
“I haven’t got the time.”
For some reason this time the phrase bristled. And later I realised why.
A journalist wouldn’t get away with saying they “hadn’t got the time” to get a response quote.
A journalist wouldn’t get away with saying they “hadn’t got the time” to get the background to a story.
A journalist wouldn’t get away with saying they “hadn’t got the time” to check a key fact. Continue reading →
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.
When you’ve converted data from a PDF to a spreadsheet it’s not uncommon for text to end up being split across multiple rows, like this: In this post I’ll explain how you can use Open Refine to quickly clean the data up so that the text is put back together and you have a single row for each entry. Continue reading →
My latest ebook – Finding Stories in Spreadsheets – is now live on Leanpub.
As with Scraping for Journalists, I’m publishing the book week-by-week so the book can be updated based on reader feedback, user suggestions and topical developments.
Each week you can download a new chapter covering a different technique for finding stories, from calculating proportions and changes, to combining data, cleaning it up, testing it, and extracting specific details.
There’s also a downloadable spreadsheet at the end of each chapter with a series of exercises to practise that chapter’s technique and find particular stories.
Along the way I tackle some other considerations in telling the story, such as context and background, and the importance of being specific in the language that you use.
Recently it has felt like data journalism might finally be taking a step forward after years spent treading water. I’ve long said that the term ‘data journalism’ was too generic for work that includes practices as diverse as scraping, data visualisation, web interactives, and FOI. But now, in 2014, it feels like different practitioners are starting to find their own identity.