Monthly Archives: January 2024

Olaya Argüeso: “Data journalism stories, when they are done, are really easy to implement on the local level”

Olaya Argueso Perez: fotocredit: Ivo Mayr, CORRECTIV2
Photo: Ivo Mayr, CORRECTIV.Europe

The CORRECTIV.Europe project, founded by German investigative media outlet Correctiv, aims to help local journalists publish data stories who wouldn’t otherwise have the time or money to do it. Cristina Puerta speaks to its editor-in-chief Olaya Argüeso.

“[CORRECTIV.Europe] is about giving the European citizens a feeling that they are on the same boat together”, editor-in-chief Olaya Argüeso explains.

Local journalism, she says, has been “neglected”, and it is now, when people suffer the consequences of global phenomena — for example, climate change because of flooding and droughts where they live — that they realise how important local journalism is.

News avoidance is at an all-time high, and while Argüeso feels breaking global problems down to a local level cannot be the solution, it can, she says, show citizens what they can do about those problems.

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I’ve updated the Inverted Pyramid of Data Journalism — and brought together resources for every stage

Inverted pyramid of data journalism: conceive, compile, clean, context, combine (with 'question' throughout). Communicate: vis, narrate, humanise, personalise, socialise, utilise

It’s over a decade since I published the Inverted Pyramid of Data Journalism. The model has been translated into multiple languages, taught all over the world, and included in a number of books and research papers. But in that time the model has also developed and changed through discussion and teaching, so here’s a round up of everything I’ve written or recommended on the different stages — along with a revised model in English (shown above; versions have been published before in German, Russian and Ukrainian!).

The most basic change to the Inverted Pyramid of Data Journalism is the recognition of a stage that precedes all others — idea generation — labelled ‘Conceive’ in the diagram above.

This is often a major stumbling block to people starting out with data journalism, and I’ve written a lot about it in recent years (see below for a full list).

The second major change is to make questioning more explicit as a process that (should) take place through all stages — not just in data analysis but in the way we question our sources, our ideas, and the reliability of the data itself.

Alongside the updated pyramid I’ve been using for the past few years I also wanted to round up links to a number of resources that relate to each stage. Here they are…

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