OpenGlobe - Open data, open maps.


Learn how to visualize health data and turn it into meaningful, attractive maps, charts and graphs. This course will cover the basics of visualizing health data and introduce students to a variety of tools and techniques for visualizing their own data. This course will include lectures and hands-on tutorials for developing your own data visualizations. By the end of the course students should feel comfortable working with the tools used with their own datasets.

No previous experience is necessary, but a familiarity with data and basic computer literacy is recommended.

Hello All,

In preparation for the course, I encourage you do do the following (if you don’t before tomorrow it’s ok - this will just save you a bit of time):

  1. Ensure you have an active Google account. If you do not, please go to, click on Sign in in the upper right-hand corner, then click on Create an Account on the proceeding page.

  2. Sign up for an Esri account. Please visit, click Sign In in the upper right hand corner, then select Create a Public Account.

  3. Sign up for a CartoDB account. Please visit, click Sign In in the upper right hand corner, then select Create an account.

I would also suggest bringing a flash drive with you if you’d like to take some of the datasets (and perhaps some of your work) home with you. In most cases these data will be available after class as we’ll be working primarily with Internet-based technologies, but it’s always nice to have a drive with you just in case.

Finally, if you’re looking for a little inspiration prior to the course, check out the following:

Geospatial Revolution: Episode One

Geospatial Revolution: Episode Two, Chapter 3

Feel free to contact me before / after the course with any questions.



Classic data visualization research

Hotmap: Looking at Geographic Attention

Smooth and efficient zooming and panning

VisDB: Database Exploration Using Multidimensional Visualization

Polaris: A System for Query, Analysis, and Visualization of Multidimensional Relational Databases

Cluster and Calendar based Visualization of Time Series Data

How NOT to Lie with Visualization

Automating the Design of Graphical Presentations of Relational Information

High-Speed Visual Estimation Using Preattentive Processing

Visual Information Seeking: Tight Coupling of Dynamic Query Filters with Starfield Displays

The Structure of the Information Visualization Design Space

Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods