In the spirit of the holidays, we decided to look at what Santa’s yearly voyage would look like if he planned his route based on the global population ranking of each country. This way, he could offload as much weight as possible early in his voyage, thus being more fuel efficient on his trip overall. The trip starts off pretty relaxed but then quickly has Santa and his reindeer jumping back and forth across the globe as he goes down the list of countries. What was interesting to see in his trip was that many countries are close in both population and geographical proximity. We found a several country clusters during Santa's trip delivering gifts around the world. Amazing what you can learn from a hypothetical Christmas voyage.

 The New York Times has put together this great timeline visualization, which shows how Michael Jackson’s songs have performed on the Billboard Hot 100 Chart.   What’s interesting is the visual story the chart creates of the pop star’s career broken down by year and album. You can drill-down and see the rise and fall of the popularity of each song on each album. You’ll notice that there are additional timelines which compares Michael Jackson’s career with other artists.  These smaller timelines, despite their reduced scale, are able to show artists’ general trends and how their singles performed on the Billboard Hot 100 as well.  For example, we can see that most of the Beatles’ singles are popular on the charts for a 5 year period.  In contrast, Michael Jackson has spurts of popularity from the mid 1970’s to the mid 1990’s.  In the period 1990 to 2000 Boyz II men and Michael Jackson perform on the charts similarly.

In what other applications could you use this visualization in?  Think about examples of where you would compare entities and the frequency of particular behaviors overtime. 


Click above image to see original graphic. 

Time series data can come from a variety of different sources, from GPS units to census data. Where most GIS applications are great at showing where things are geospatially, the dimension of time can often be difficult for users to easily see. And when you are dealing with time series data, this becomes a pretty big issue. Our approach has been to display time as the vertical axis, allowing features to be displayed in their chronological order. This allows the user to see the sequence of events or data points. This is crucial when dealing with movement data, as the order of these points really dictates the underlying movement.

In this simple example, we look at how a user can take a time series data set of location points from ArcGIS10 and visualize them in a 3D time viewer, which shows a path between the location points over time. Taking it one step further, the time series data can be animated, allowing the user to play back the sequence and see the movements in real-time.

Take a look at the video demonstration: