The Great Wave is a project developed during a year-long data journalism fellowship at the International School for Advanced Studies (SISSA) in Trieste, Italy, a research center that focuses on physics, neuroscience, mathematics and science communication. Its purpose was to think about the pandemic and its effects in a more systematic way, taking a step back from emergency writing to get a broader look at what happened in 2020. We wanted to understand what did we think about the virus, how did we know it, and whether it was the best use of available scientific evidence, especially in the West.
The results of our project were featured in national and local media in Italy, sparking debates around the timing and effectiveness of the country’s pandemic response. Some public health authorities denied our FOIA requests, and the lack of transparency around critical epidemiological data was also one of the most contested issues.
Data visualization was key to our project. We wanted to report the best available evidence we could find sifting through hundreds of papers, and talking to dozens of experts, in a concise and compelling way. At the same time, given the topic we absolutely wanted to avoid compiling a statistical atlas of the pandemic. Working with information designer Federica Fragapane, we designed our visualizations to make numbers as human as possible. Every time we showed individuals, for example, we made them look all different from each other. There are no two identical objects to represent them. For us it was very important to remind readers that we were talking about people and their stories, not abstract figures. This was the principle that led us to design many hand-made visualizations, crafted from scratch instead of using off the shelf tools.
What was the hardest part of this project?
Our goal, especially in the first half of project, was to try to give some dignity and respect to everybody involved. This was a story about people that lost family, friends, loved ones, and we wanted to do all we could to show empathy and compassion, which is especially hard when working with numbers. One such example can be found in the first chapter when we talked about what happened in Bergamo, the most hit Italian area during the first wave. To give readers an idea of the amount of destruction the virus brought, we tracked each of the excess deaths as best as we could, through all available public information. We then built a simulation of their social structure using demographic data to show how many family members were left without their loved ones.
What can others learn from this project?
This project taught us that data driven journalism was invaluable in understanding and reporting this pandemic, but also carried the risk of being cold and heartless. We strived for balance between rigor and humanity. Numbers are great for telling some stories, but – like when we talked about mental health – they also can have large limitations. You can’t really use data to talk about feelings in a meaningful way, for example, and so we didn’t. Sometimes all that’s needed is just a voice. Our hope is that those lessons can be of use to other journalists as well.