Safety In Numbers by Heather Cox

I sourced my data from the South Australian Government open data repository, focusing on everyday passenger vehicles (cars, station wagons, and utilities) and excluding motorcycles, scooters, and heavy commercial vehicles. I honed in on drivers because South Australian Police only record passenger details if they’re injured, making those data incomplete. With driver data always available, I had a consistent basis to compare injury rates for male and female drivers.

Data preparation was done in KNIME, which helped me manage and clean the dataset. One unique challenge was converting crash location coordinates from Lambert Conformal Conic Projection to the Mercator Projection that Tableau (via Mapbox) requires. To solve this, I learned QGIS and successfully transformed the spatial data.

Inspired by Caroline Criado Perez’s Invisible Women, I wanted to test whether the documented bias in vehicle safety applied to my own backyard in South Australia. I visualized the data in Tableau, crafting a hex map where each hexagon is split to display both accident rates and injury rates by gender. Applying the cyan/aqua colour to the hex map made it resemble shattered glass, which inspired other graphics in the viz helped me convey the stark reality of vehicular accidents while avoiding stereotypical gender colours.

The result is a data-driven story that clearly shows female drivers are at higher risk of injury. The underlying reason is that standard crash-test dummies are designed around male dimensions, or are simply “scaled-down” versions of a male model. By highlighting this gender data gap, I’m hoping viewers will be inspired to talk about it, share what they learn, and push for testing protocols that accurately reflect the risks to female bodies, so that vehicle designers can start working on the problem.