The way we present data to others has evolved from simple pie charts/bar graphs to sophisticated interactive visualizations. These interactive visualizations are built using techs like Augmented Reality or Virtual Reality. There are many leading companies adopting these techs for data exploration, presentation and storytelling. One such example is  IBM Immersive Data, which is an augmented reality visualization tool that helps the data scientists and business executives to quickly explore and understand data. There are also many startups that have started adopting AR/VR for presenting and exploring data visualization.

This post talks about the prototype that is built in Imaginea Labs to visualize the Covid19 data in the AR platform. We will be discussing the design choices that are made to suit the use case. And some trade offs that we shall be aware of. These trade-offs are influenced by technology.

AR Core

Though there are a number of AR tools available, ARCore is the best in handling motion tracking, environmental understanding and light estimation (There are also many exciting features that will be released in future like depth api and dynamic occlusion). These features are suitable for the use case that is being developed here for example, motion tracking allows the users to walk around the data. In this prototype Covind19 data is used for creating the visualization and deriving some meaningful insights.

Evolving design thoughts

These data contain latitude, longitude, state/province, country, day by day counts on number of case confirmed/death/recovered, age groups affected, sex and symptoms.

As latitude and longitude are available in data, they can be plotted over a map or globe. Though an option can be provided to choose a map or globe in our tool, we wanted to try out how these data work on the globe. Because there are lots of examples like InformationIsBeautiful, CVID1O9 Infodemics Observatory etc uses map for visualization and we are very much familiar with how it works in deriving the insights. This also helps us to determine if the globe visualization has any positive impact on user experience during the exploration in AR space.

To convey that the people of the respective state or province are affected by Covid19, all these data are plotted on the globe and each data point is represented by a bug image. Though this gives a geographic overview of infected areas, to fastly grasp the severity level, the bugs are colored with interpolation. The bugs with green color are less infected, whereas the yellow are more infected.

As each of these data points have meaningful information, these data are made interactive. When the users zoom in to a particular region of the globe, these data points belonging to that region pop out a label showing the info like name, No of cases confirmed/death/recovered. As the user will be interested in knowing more about the insights, these bugs are made clickable. On clicking the bug, a graph is displayed, which has the plotting of No of cases confirmed/dead/recovered vs time. To distinguish the curves, the color codes are used. As a whole in this tool, the orange color signifies the confirmed, red signifies death and green signifies recovered cases. As the user might be keen to know the day by day growth of these numbers rather than seeing the latest values, a play option is provided. The user will see an animation in the graph, where the “red” line indicating the current date moves forward and the respective number of cases are displayed accordingly.

By consolidating the data of all the states/provinces, we can generate the data for the whole country. Each country is represented by a bar and its length is proportional to the number of cases confirmed. There are some situations where the visualization might look cluttered. Hence these state/province wise data is made invisible and they are accessed by clicking on the respective country bars.

The user can also interact with the globe as whole to move, rotate and scale according to his convenience.