A plea for data-driven stories to go undercover, and center around the story, not around the data, analysis or technology that keeps the story afloat.
Should you learn Python, R or SQL? Investigative reporter Luuk Sengers discusses the ‘tribal war’ at hand in data journalism.
During the annual DataHarvest+ conference data journalists and developers get together to share tech, tools and data. Here’s an incomplete overview of some of these resources.
Lisa Charlotte Rost explains the psychological, social and technological reasons why none of us will ever fully believe all the facts. And how the kind of facts and the context in which we encounter them makes us believe or ignore them.
How can we all believe more true things? And how can we communicate data so that it convinces somebody? She looks at lots of examples from data communication, especially from data visualisation and data journalism.
Corruption in public spending is a problem in many countries around the world. Elvis, the data platform – not the singer, visualises European pubic spending data also known as procurement data or tender data to help journalists find fishy relationships between governments and companies.
Where to start if you’re new to data journalism? Sure, you should probably start with a story, but then what? Nowadays there are so many tools available, it can be… Read More
At the intersection of data and journalism, lots can go wrong. It’s possible that while your story is true, it’s also wrong. New York Times data journalist Robert Gebeloff shares his tactics to avoid that: how not to publish a true but wrong story ever again.
Referring back to the Five “W”s helps journalists address the fundamental questions that every story should be able to answer. Recent events, however, have shown that traditional journalistic practices might not be working as effectively as they used to. As such, here are a few additions to the Five “W”s that will surely come in handy for today’s journalists.
Personally I consider this a must read for all in the field of data journalism. Andrew Gelman wonders why there were no skeptical, investigative, quantitative journalists decades ago? A growing lists of professionals answers his question: because of the lack of tools; emerging technologies; or better education that leads to more data literacy. The true gold is to be found in the comments – about the new quantitative journalism.
An exhaustive reference to problems seen in real-world data along with suggestions on how to resolve them. As a reporter your world is full of data. And those data are full of problems. This guide presents thorough descriptions and suggested solutions to many of the kinds of problems that you will encounter when working with data.