I've been teaching the graduate Information Visualization course since Fall 2011. In this series of posts, I'm highlighting a few of the projects from each course offering. (Previous posts: Fall 2011, Fall 2012, 2013)
https://ws-dl.cs.odu.edu/vis/flunet-vis/ and is best viewed in Chrome.
The Global Influenza Surveillance and Response System (GISRS) has been in operation since 1995 and aggregates data weekly from laboratories and flu centers around the world. The FluNet website was constructed to provide access to this data, but does not include interactive visualizations.
This project presents an interactive visualization of all of the GISRS data available through FluNet as of October 2013. The main visualization is an animated 3D choropleth globe where hue corresponds to virus lineage (influenza type A or type B) and color intensity corresponds to infection level. This shows the propagation of influenza across the globe over time. The globe is also semi-transparent, so that the user can see how influenza infection rates change on the opposite hemisphere. The user may pick a specific time period or press the play button and watch the yearly cycle of infection play itself out on the globe's surface.
The visualization also includes the option to show a 2D version of the globe, using the Natural Earth projection.
There is a stacked area slider located under the globe for navigating through time (example of a "scented widget"). The stacked area chart provides a view of the progression of infection levels over time and is shown on a cubic-root scale to compensate for the peaks during the 2009 flu pandemic.
If the user clicks on a country, a popout chart will be displayed, showing a single year of data for that country, centered on the current point in time. The default view is a stacked area chart, but there are options to show either a streamgraph or an expanded 100% stacked area chart. The popout chart animates with the choropleth.
The video below shows a demo:
Although the data was freely available from the GISRS website, there was still a significant amount of data cleaning involved. Both OpenRefine and Mr. Data Converter were used to clean and format the data into JSON. The D3.js, NVD3, and TopoJSON libraries were used to create the visualization.
Our future work on this project involves turning this into an extensible framework that can be used to show other global datasets over time.