Lessons From China’s COVID-19 Visualizations
By: Kevin Maher
Tags: Design, China, Covid 19, Programming, Data Visualization

Lessons From China’s COVID-19 Visualizations

And interview with three data viz practitioners who have responded to the urgent need for communicating information about the coronavirus pandemic in China

The threat of the coronavirus has frightened people around the world. Disentangling the real and imagined from the threat can be especially difficult. In late February the general director of the WHO warned “it is impossible to predict which direction this epidemic will take.” Getting information to people about the state of the epidemic is especially important, yet often poorly done. We face what the WHO has termed an “infodemic,” where rumors and misinformation confuse citizens. People looking to understand real threats are often faced with inadequate visualizations.

Responding to this need in China, visualizers in traditional media and academia responded. Three different approaches to this challenge can be seen in the works of the following three visualization practitioners, who I interviewed for this story.

Xiaoru Yuan (XR) is a professor at Peking University and leads the Peking University Visual Analytics group, which created many COVID-19 visualizations.

Huang Zhiming (HZ) is the CEO of Data-viz.cn whose coronavirus visualizations in mass media have received over 1 billion views.

Xiang Fan (XF) is a designer, digital media researcher, and professor at Tsinghua University. Her COVID-19 work gained a strong following.

Kevin Maher (KM): How did each of you begin to get involved with visualizing the coronavirus for the public? What was a challenge you faced?

XR: Our team has over 10 years of experience in visualization, and since I started the visualization research at Peking University in 2008, we have often worked on socially relevant problems. Much of our visualization for the epidemic was for an expert audience. For example, we developed visualization for experts that study patient medical records in order to find out what medical treatment or prevention methods are most effective. In our work made for civilians, we put scientific insights into our visualizations in an understandable way.

Fig 1 The novel coronavirus compared with other historical viruses. Interactive

While talking to professors of public health and medical science, we learned that the current epidemic has several special characteristics, which are unlike other infectious diseases. We decided we wanted to do further comparison. In medical literature we saw COVID-19 compared to other diseases in static graphics, but they compared using R0 [basic reproduction number], which is difficult to obtain an accurate measure of because the information needed to calculate it is quite incomplete. After attempting different metrics, we found a dynamic case fatality rate to be more appropriate. This visual (Fig 1) can give an overall picture for people to be more aware of the nature of the virus in comparison to other viruses, as well as it’s dynamic fatality rate, infection number and mortality number.

Fig 2 A detail of the Tencent News Pandemic Dashboard, one of the most popular mobile dashboards in China. Mobile version

HZ: My media company has worked on designing and developing visualizations for the largest media outlets. At the beginning of the crisis we worked on the visualizations for Tencent News, Baidu, and central governmental news providers.

Toward the beginning of the crisis, when people were most concerned, our visualizations received the largest amount of attention. Our dashboard for Tencent news (Fig 2) received over 100 million views per day during this time.

One of the most difficult challenges in our work was to fact-check the data sources against each other, which required an immense amount of effort toward the beginning of the crisis, but the reliability of the data was most critical.

Fig 3 View of the coronavirus data with circle packing. Interactive version

XF: Nobody was aware of a mysterious virus spreading across the country when the Chinese New Year was approaching. When human-to-human transmission was confirmed, all of us quarantined ourselves at home and eagerly searched for more information about the epidemic.

We knew that, given the unknown and unpredictable nature of the virus, we weren’t the only ones stuck in this bind. However, as visualizers, we could be the earliest info providers using data. One challenge to our work was that at first there were no unified databases for us to use, so we had to pool data from various sources such as the reports by provinces.

FlowCases is a data visualization platform for people dealing with the coronavirus epidemic. It provides two rare perspectives, different from the mainstream media. One focuses on space and hierarchy of the data (fig 3) and another on the time distribution of confirmed cases (fig 4).

KM: There was a kind of “infodemic” where misinformation and rumors in social media confused citizens. How do you see the role of your visualizations for the coronavirus?

HZ: Traditional news media had a great impact by finding ways of communicating accurate information to counteract rumor. There were so many different kinds of information sent out by social media, some true, some false. Our job was to spread the most authoritative and reliable information available.

As far as the visualizations, our work is different from the works of academics or small market visualizers. My analysis of why you can see in the figure below. When doing visualization the highest cost and most difficult visualizations are complex and cool.

Fig 5 Analysis by Huang Zhimin as to why mass media have simple graphics.

For our work in mass media, the ability of a visualization to spread is important. The more complex visualizations have trouble spreading because they are more difficult to understand. The more cool visualizations are more attractive, and spreadable (fig 3). So when we take both cost and the ease of spread into consideration, our team focuses on simple yet cool visuals.

For example, Xiang Fan usually creates much more complex and cool visualizations that are difficult to create. Our work is more simple since it is commercial and needs to prioritize costs and spreadability, so it is either cool and simple or simple and artless.

XF: Like the medical science community, the visualization community was faced with an unknown, rapidly developing severe contagion, that nobody, no matter whether they are part of the mainstream media or civic media, had any experience in communicating. At the beginning of the epidemic we saw our role as presenting information in an effective way that was not tried by the mainstream media. In much of the mainstream media we saw a restriction of design possibilities to only basic charts and maps (fig 6). These graphics left important questions unanswered, for example, the ability to see trends in how new cases are developing in provinces.

Fig 6 A survey of existing coronavirus visualization platforms and works in China. Many of the large scale platforms have similar designs (clustered on the left). Source: Fei Luo, Beijing Institute of Technology.

Our project aimed to allow people to closely observe the cities where they and their loved ones were. We keep checking reactions to our work to see if they can clearly communicate information to the public. Our coronavirus works have gotten more than 1.5 millions views from mobile users.

However, no mainstream media source used or promoted our visualization. Both the mainstream media and the civic visualizers clearly understand different visualization approaches can lead to different cognitive outcomes about the epidemic. Before any institution can decide if a novel kind of visualization is “safe” to the mainstream media, rejection of the project is the most safe thing to do. We try to show a different perspective of the data people don’t see in mainstream platforms.

XR: We want people to look at our visualization and find out the answers to the questions they are asking themselves.

In the research community, goals of visualization are to be effective, and also be novel. Our method of accomplishing this is to first check the “design requirements.” We check literature and interview experts to find and define tasks that are critically important. We then try to tell a story that delivers the information to the receiver.

Fig 7 COVID-19 Barometer showing the new cases in China. Interactive version

For the coronavirus, we needed to identify what information the users want to understand, what they are searching for. One characteristic of the data on the coronavirus is that the overall confirmed cases were highly concentrated in the region of Wuhan at the beginning. However, for most people who see the visualization, they may also want to know how the data applies to regions closer to them. For the COVID-19 Barometer (fig 7) we researched users to find they were interested not only in the overall accumulated infections, but also how their region was affected. They also want to know how the infections are changing over time, especially closer to the present. They want to know at what critical moment the situation will get better. Our visual encoding method and interaction design supports these tasks. With color encoding the trend of new confirmed cases of each region everyday comparing with that of the previous day, viewer can clearly find out how the situation developing.

While in the research community we look for novel visualizations, sometimes the beginnings of effective solutions can be found in previous work. Our team has experience in visualization for many years. We can adapt to new circumstances when something critical needs to be visualized rapidly.

Fig 8 Visualization showing radiation levels within a fictitious city.

Last year we developed a visualization for an expert audience regarding radiation levels in a city (fig 8). The work won an outstanding award in IEEE VAST Challenge 2019. Some aspects of the design requirements were similar to the situation we were facing now. We decided there were aspects of the layout that could successfully deliver information to the audience.

KM: What would you like to tell the visualization community outside of China?

XR: We would welcome talented visualizers to work with our team. We have over 30 faculty members and 150 students who have participated in our work. They are from a variety of backgrounds inside China and outside China. We work with people with a variety of different expertise, including people in data management, data mining, subject matter experts, visualization research, and art and design. We also have worked with top news agencies and journalists so that our work can reach a wider audience. We have worked on developing COVID-19 visualizations for specific audiences and applications, such for the African public (Fig 9). A sample of our work can be seen here.

Fig 9 COVID-19 in Africa. Interactive version

This COVID-19 epidemic is a war between all human beings and the virus. In our role as visualizers, we can harness complex information and

equip people with better situation awareness. We have an open call for professionals to work with us, welcome to join.

With our expertise and by working together we can help society.

HZ：My advice to visualizers is to consider several fundamental issues before you begin visualizing. Is the most important goal of the visualization to spread, or to give people the ability to analyze data? How much expert knowledge does the user have? What device would be best for the visualization, desktop or mobile? Once these considerations are made we can better create more appropriate visualizations.

XF: People around the world have endless questions related to the epidemic, and many of them can be answered though data. Visualization not only has a role in explaining data, but also in answering people’s questions by allowing them to explore the data themselves.

No one knows the extent of how the epidemic will spread or the full impact of its spread. Certainly, no one knows the most effective approach to visualizing the many aspects of the data. As visualizers, let’s try our best to think through the many ways we can give correct answers to the many questions people have.

Final thoughts

There is a phrase by Confucius, 三人行，必有我师, which translates as “if three of us walk together, at least one of the other two is good enough to be my teacher.” In modern times it is used to mean we can learn those with different perspectives.

Outside of strong ties in academia, much of the Chinese data visualization community lives apart from the rest of the world. Only seven of the first 3,500 DVS members were from the Chinese mainland. In my experience at the Chinese Academy of Sciences and in starting the Student’s Data Visualization Society at Tsinghua University, I often see coworkers and classmates sharing insightful Chinese articles and Chinese visualization projects that are not published in English. Conversely, many resources from abroad are not available in China. It seems like there is something that the communities could learn from each other.

In late January Xiaoru Yuan, Xiang Fan, and Huang Zhimin used data visualization to respond to the urgent need for communicating information about the epidemic to the public. I find their three different approaches to visualization each to have its own strengths and undeniable impact. Outside of the visualization community, I saw their works shared on social media as people spread early news of the epidemic situation.

For me, the most important lesson from the China’s epidemic visualization is the opportunity for visualizers to learn from each other. The importance of learning from China’s visualization community is amplified since China has already passed through much of what the rest of the world is now experiencing. We have the opportunity to learn from what worked and what didn’t. In these times of living apart we can be better connected and learn from each other.

This interview was conducted by Kevin Maher, a freelance visualizer pursuing graduate study at Tsinghua University and assisting research at the Chinese Academy of Sciences.

You can read more of Nightingale’s coverage of the coronavirus pandemic here.