When we think about pioneers in science and medicine, the usual suspects are often “fathers of” something: the father of microbiology, the father of modern surgery, and so on. But Florence Nightingale, a 19th-century nurse, statistician, and public health advocate, was a pioneer in her own right — earning her place as the mother of data visualization and public health statistics.
Best known for her tireless work during the Crimean War, Nightingale revolutionized healthcare practices and significantly reduced mortality rates in military hospitals. But her legacy wasn’t just in nursing, it was her ability to communicate the urgency of sanitary reforms through the power of visual data.
The Crimean War: A Battlefield for Better Sanitation
During the Crimean War (1853–1856), Nightingale and her team of nurses witnessed appalling conditions in British field hospitals. Soldiers were dying not from battlefield injuries but from preventable diseases like cholera, dysentery, and typhus. At one point, the mortality rate in some hospitals
Nightingale understood that improving sanitation—ventilation, clean water, and better waste management—could drastically reduce these deaths. But convincing politicians and military officials to invest in sanitary reforms required more than anecdotal evidence. It required data.
Enter the coxcomb diagram, or as it’s more commonly known today, the Rose Diagram. Designed in 1858, this circular chart visually represented monthly mortality rates in military hospitals, differentiating between deaths caused by preventable diseases (blue), battle wounds (orange), and other causes (black).
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As social historian and political economist , what made Nightingale’s Rose Diagram revolutionary wasn’t just its aesthetic appeal — it was its ability to tell a story:
- Before-and-After Comparison: Nightingale didn’t simply plot the data linearly. Instead, she created two distinct “roses”—one for the year before sanitary reforms were implemented (right) and another for the year after (left). This separation, using the same scale, made the dramatic decline in mortality rates impossible to ignore.
- Seasonal Patterns: The circular design highlighted seasonal variations in mortality, with larger wedges representing months where deaths were higher. This made it clear that preventable diseases spiked during certain times of the year, emphasizing the need for ongoing improvements in sanitation.
- Scaling for Clarity: Nightingale scaled her data by using a square root transformation, meaning the area of each wedge represented mortality rates. This is in contrast to a typical method of representing data by the height of a bar or location on a scatterplot, which tends to emphasize larger differences in values. Using square root transformation de-emphasized extreme outliers, such as one month’s exceptionally high death toll, and instead drew attention to overarching trends.
Notes on Nightingale
Nightingale’s Rose Diagram wasn’t just about science—it was a political tool. By presenting data in a visually compelling way, she cut through bureaucratic resistance and made an undeniable case for reforms. Her work helped persuade the British government to overhaul military hospital sanitation, contributing to a dramatic decline in deaths from preventable diseases.
Today, Nightingale’s Rose Diagram serves as a reminder that data isn’t just for analysis—it’s a tool for action. Whether you’re presenting to policymakers, advocating for public health reforms, or just trying to make sense of complex information, her example reminds us that how you present data can be as important as the data itself. It’s also a reminder to view data visualizations with a critical eye. If the creator of a data visualization has a personal or political objective, they can easily manipulate the data in ways that are not immediately obvious. There are dozens of approaches to , such as a truncated (incomplete) axis, inverted (reversed) axis, or a misleading colour scheme. Nightingale’s Rose was impactful precisely because it translated complex data into a compelling visual narrative, creating understanding among non-scientific audiences. With modern access to design tools and graphics today, readers should be aware that the striking nature of data visualization design can be used for both harm and good.
The next time you see an infographic or a dashboard, remember that sometimes a picture isn’t just worth a thousand words—it’s worth a thousand lives.
Note: This article was inspired by the authors’ coursework in PPHS602 at Ď㽶ĘÓƵ, the and .
