What is special about getting time together with GIS you ask? Tons! We work a lot on showing the benefits of visual analysis which allows analysts to see changes over both space and time. Movement, for instance, is very difficult to visualize in traditional timeline views. Map viewers typically have no way of showing the dimension of time within your data. Pattern analysis is another area that is difficult to do without seeing both where and when things occurred. We believe that a fused time, space and link viewer is the key to understand movements, patterns and behaviors.   

 

With that in mind, we decided that Valentine’s Day was the perfect opportunity for us to announce the latest release of our visual analysis tool. GeoTime was designed from the ground up for visual analysis of data that has location, time and link information. Think GPS, communications and transactional data. This new release targets three key analysis workflows:

• Automatically find locations of interest
  • Identify locations frequently visited by multiple individuals
  • Detect movement close to locations and areas of interest
• Easy loading of Call Detail Records to show movement and call patterns
  • New Import Wizard for CDR records
  • Supports all major carriers
  • Works on other types of communications data (ex: email, IMs, radio)
• Spot trends and patterns within large data sets
  • From your RMS, CMS and other back end systems
  • Scale up to hundreds of thousands of events

This latest release will also see the first ever 64bit version of GeoTime, giving analysts the ability to import much larger data sets then previous releases. Check out the What’s New Videos to see just how much data we can throw into GeoTime’s 3D viewer.

We will be hosting a webinar of What’s New in GeoTime 5.3 February 22nd, which will cover the new capabilities and enhancements in this release. For those interested in attending the presentation, head on over to the registrations page.


Happy Valentine’s Day everyone!

The GeoTime Team

 

After a quiet winter season, the GeoTime Team is happy to announce a new line up of upcoming webinars. We have been talking with our customers, partners and industry leaders in hopes of providing informative and engaging presentations via our interactive webinar room. We have really enjoyed the interaction and discussion that has taken place in our past webinars and look forward to future discussions with attendees.

Today we are announcing three new webinars. You can register for them all on our registrations page.


On February 23rd, Curtis Garton, Visual Analytics Product Manager @ Oculus will be giving an overview of GeoTime for visual analysis of spatio-temporal data sets. The presentation will go over what types of data are best suited for analysis, how to “look” at your data, doing mark-up and presenting your findings.

On February 29th, Andrew Modlin @ U.S. Geological Survey, Western Ecological Research Centre, presents his work on the analysis of wildlife tracking data collected in Southern Nevada, USA. Deployable GPS data-loggers have the potential to greatly benefit conservation research, but the resulting data-sets can be daunting to analyze. Andrew will discuss the use of Geotime's visual tools to investigate fine scale habitat use, identify proximal encounters, and validate GPS location data.

On March 28th, join the CrisisMappers Network as we continue our ongoing webinar series with them. The CrisisMappers Webinar Series features a variety of speakers from around the world, ranging from researchers to on the ground practitioners. To learn more about the CrisisMappers Network, check out http://www.crisismappers.net.


We really enjoy the interaction that we have with attendees and presenters, which is made possible via our webinar meeting rooms. What has really made discussion and dialogue possible is the dynamic way the presentations are delivered. There are numerous ways in which attendees can interact with presenters, ranging from simple Q&A sessions, live chat sessions and full VoIP voice discussions. Here is a screenshot of one of our webinars in action:

Our webinar meeting room has all the facilities for group chat, Q&A, live broadcasts and more

Check out the list of upcoming webinars and register for as many as you like. We look forward to seeing you in attendance!

Sign up today at the GeoTime Webinar Registrations Page



Cheers,
The GeoTime Team

From time to time, we like to give the world a sneak peek into what the GeoTime Team is working on. These new features and capabilities are things that we are designing, developing or just testing out to see if they fly. And not all of them will make it into a GeoTime release. These previews videos are meant to let users know where we are headed and to get a glimpse of what might be coming up in future releases of the software.

In this video, we will be working with a data set recorded in the Canadian Rockies (Marmot Basin to be exact!). One of our GeoTime Team members used a GPS device to record a portion of their day skiing the slopes. What was great was that the device captured their altitude, which we allowed us to show their movement up and down the slopes over time. For analysis, we wanted to understand where they spent most of their time skiing and show that on the map, in a heatmap type display. To accomplish this, we divided the hill into four areas or regions using map graphics and then summarized the number of events in each one, which in turn determined the color of these regions. The darker the color, the more time the skier spent in that region. What’s great is that you can drive these map graphics with any data that a user imports, which is really useful for doing crime series analysis, fraud reporting and customer visit heatmaps.

 

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: