Interactive data visualizations allow you to display complex data in interesting ways and allow viewers to be active participants in exploring the data. Check out some of these some great examples of interactive data visualizations for inspiration.
Flowing Data allows you to visualize a day in the life of Americans.
Interactive Data Visualization with Tableau
I wanted to experiment with visualization of Nebraska On-Farm Research data. After experimenting with several tools, I decided to work with Tableau software, developed by a company whose sole mission is to help people see and understand their data. You can learn more at http://www.tableau.com/. The data was collected by participants in the Nebraska On-Farm Research Network. The crop producers involved compared yields where no starter fertilizer was used to yields where 10-34-0 starter fertilizer was applied at planting. Phosphorus levels for the fields were recorded.
The data visualization has two parts. The first part is a scatter plot showing soil P versus the yield increase for starter fertilizer use. Hovering over each point brings up a tool tip that shows the study location, year, starter product tested and rate, yield of the control and starter treatments, statistical significance, and soil phosphorus level. The tool also allows farmers or agronomists to explore data by adjusting a slider to a range of soil phosphorus that is representative for their fields. The visual then displays the average yield increase for these sites.
The second part allows users to calculate economic impact by putting in their own soil phosphorus, starter fertilizer cost and expected corn price. The tool calculates the expected yield increase and expected return on investment based on the regression line that fits through the data.
Getting Started with Interactive Visualizations
A number of tools are available to enable you to create interactive and animated data visualizations. This article[vi] lists some design tools to look into and is a great place to get started exploring options. Some require more coding, but others can be done completely through a graphical user interface.
Tableau, the tool I used, has a great resource of instructional videos[vii] to help you get started. I recommend working with a simpler dataset, such as the one I used when learning the tool. You also may find it helpful, as I did, to sketch out a plan for the visualization prior to beginning work in Tableau.
Do you have ideas for how interactive data visualizations could be used in Extension or in your work? Share your ideas in the comments.