One thing that has impressed me the most is the vast amount of high-quality, organized data around COVID-19. One of the leaders since the early days of COVID-19 has been John Hopkins' Center for Systems Science and Engineering. As part of making an incredible visual map of the outbreak, they open-sourced all of their data collection on GitHub.
While exploring this dataset, I wanted to find what others have created. There were a lot of maps similar to John Hopkins that displayed the number of active cases as a "heat map". This is informative, but they did not provide any direct insight on how the situation was evolving right now.
The visualization that inspired me the most was one I found created by John Burn-Murdoch that overlapped the number of cases in various countries based on the day when each country had the their 100th person infected. I love it!
With this first 91-DIVOC project, my goal is to create my own version of the overlapping countries visualization. I used the dataset linked above, along with a visualization library called d3.js, to create an interactive visualization that allows a user to mouseover any point to explore the data, change the scale for logarithmic (better at showing exponentially increasing data) to linear (better at showing the human impact), and change what country is highlighted. Here's what I created: