
Sign up to save your podcasts
Or


We all know that data visualization is a great tool to explore and make sense of numbers, and also to communicate those numbers to people. But there is also a long historical tradition in visualization that uses graphs, charts, and maps for persuasion. Think, for instance, of Florence Nightingale, who used data and charts to persuade the English authorities to improve the living conditions of soldiers during war. The persuasive tradition of visualization today continues thanks in part to the work of journalists and designers who work not for the news sides of their companies, but for their opinion sections.
In this episode Alberto and Simon talked to two of them, Stuart Thompson from The New York Times, and Sergio Peçanha, from The Washington Post. How is their work similar to what traditional graphics departments in news organizations do? And how is it different?
The music for this episode is Olympic athletes' weights and heights, from this dataset. The tool we use is TwoTone. Try it out!
By Alberto Cairo, Simon Rogers & Scott Klein4.7
77 ratings
We all know that data visualization is a great tool to explore and make sense of numbers, and also to communicate those numbers to people. But there is also a long historical tradition in visualization that uses graphs, charts, and maps for persuasion. Think, for instance, of Florence Nightingale, who used data and charts to persuade the English authorities to improve the living conditions of soldiers during war. The persuasive tradition of visualization today continues thanks in part to the work of journalists and designers who work not for the news sides of their companies, but for their opinion sections.
In this episode Alberto and Simon talked to two of them, Stuart Thompson from The New York Times, and Sergio Peçanha, from The Washington Post. How is their work similar to what traditional graphics departments in news organizations do? And how is it different?
The music for this episode is Olympic athletes' weights and heights, from this dataset. The tool we use is TwoTone. Try it out!

43,838 Listeners

32,021 Listeners

6,822 Listeners

30,680 Listeners

43,548 Listeners

26,233 Listeners

890 Listeners

3,156 Listeners

99 Listeners

16,357 Listeners

5,160 Listeners

15 Listeners

5,509 Listeners

15,247 Listeners

15,918 Listeners