Project description

We are a small team of eight people who produce a range of data-driven stories. About half of our output are original ideas that we have conceived and executed. The other half are collaborations with other teams but in all those cases all of the data-crunching, visualisation and storyboarding is done by our team.
The submitted portfolio represents a range of stories and story styles designed for mobile audiences and intended to maximise engagement and shareability. The range from the lighter subject matter (pocket money) to more serious topics (the gulags of Xinjiang).
Some are data visualisations. Others use satellite imaging. Many include reader input.
As we are a publically-funded news organisation, we are not required to consider the monetisation aspect. But we do have to consider engagement and reach. So impact is very important for our team especially as we are only funded year-to-year.

What makes this project innovative?

Our portfolio is at the cutting edge of data journalism in Australia. We have used a variety of tools and techniques - working within the confines of a very inflexible CMS - to tell sometimes complicated stories in a new and engaging way. Our stories have consistently rated well for engagement and the reader feedback has been overwhelmingly positive. We have colleagues in another part of our organisation doing similar work but in Australia, the ABC stands out in sustaining this level of quality and quantity of work.

What was the impact of your project? How did you measure it?

We measure success in terms of reach (unique visitors), engagement minutes and page views. Social class: 4,635,779 (engagement minutes) Property prices: 2,765,543 Xingjiang camps: 1,465,633 Extreme weather: 1,128,204 Education revolution: 1,000,349 Flocking to the fringe: 1,031,155

Source and methodology

We obtain datasets from a variety of government and non-government organisation, sometimes through scraping or freedom of information requests. The data is cleaned, analysed and then checked with statisticians and subject-matter experts to ensure that we are not misinterpreting the data.

Technologies Used

Everything is coded using Javascript, D3 and React library. We use QGIS mapping software. We use the Sentinel Hub for satellite imagery. We also use Google Refine, Tableau and Tableau Prep.

Project members

Stephen Hutcheon, Mark Doman, Inga Ting, Alex Palmer, Jack Fisher, Michael Workman, Ri Lui, Nathanael Scott

Link

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