Geotime(s)

2012 Olympic Torch Relay Route in CSV

Mon, 14 May 2012 17:47:48 GMT

After an hour searching for raw data on the 2012 Olympics Torch Relay Route, I gave up and did some web scraping on my own. What we came up with is a CSV file that has %95 of the stops that the torch will be making on it's jorney to London. We are still working on the time stamps for these, so stay tuned for updates. Until then, please feel free to download and use the data set.

CSV file of the 2012 Olympic Torch Relay Route

Overview of the 2012 Olympic Torch Relay Route

3D Time View of the 2012 Olympic Torch Relay Route

Only 73 more days to go!

Cheers,
The GeoTime Team

Microsoft's GeoLife Project

Fri, 11 May 2012 17:06:16 GMT

Thanks to Leo for the tip on Microsoft's GeoLife GPS Trajectories Project. It looks like Microsoft has collected GPS locations of 178 project users over a period of 3 years (!!!). That's a gold mine of movement data, which is quite uncommon. We will certainly be downloading the raw data to see what types of patterns we can identify and post our results back here. Check out the project for yourself here:

Microsoft's GeoLife Project Homepage

New Webinar Schedule Posted: 4 Upcoming Presentations Added

Mon, 30 Apr 2012 17:01:27 GMT

We just posted the new schedule for our upcoming webinar presentations. We have some really great talks touching on topics that we discuss quite a lot here in the office; namely, movement and pattern analysis.

First up is a new talk by our Visual Analytics Product Manager, Curtis Garton, on identifying and analyzing communications patterns. Communications take place all the time via all sorts of means: email, phones, Facebook, Twitter, meetings, etc. In his presentation, Curtis will cover off a number of ways to look for patterns within communications data and how to present them in a meaningful manner.

Next up is Dr. Seraphim Alvanides & Godwin Yeboah from Northumbria University in the UK. We have been anxiously awaiting their presentation on cycling data that they have analyzed from Newcaste upon Tyne. Their research work focuses on those who cycle as their primary form of transportation in support of urban planners and policy makers.

Our third presentation was originally presented at the International Association of Law Enforcement Intelligence Analysts (IALEIA) 2012 conference in San Diego. In this talk, Curtis Garton discusses how various sources of location information can be fused to create accurate movement trails for advanced analysis. He looks at data sources that have varying levels of location resolution, such as GPS, cell site locations and automatic license plate reader data.

And finally, we continue our ongoing series with the CrisisMappers Network. This session will be given by John Quinn at Makerere University in Uganda. Topic and date coming soon!

Head over to the webinar registration page and sign up today!

US Geological Survey - Wildlife Tracking Analysis Webinar

Thu, 05 Apr 2012 17:33:48 GMT

We have just posted the recording from the presentation by Andrew Modlin from the US Geological Survey, who presented a talk on wildlife tracking data analysis. Andrew looked at how GPS tracking data recorded in the wild could be analyzed to learn more about different aspects of animal movement.

Our favorite part of the talk was when Andrew used the Meeting Finder to look for potential “mating sessions” between male and female animals. Not something we had envisioned when designing the tools in GeoTime but happy that it was able to help Andrew out!

Check out Andrew’s presentation here:

Cheers, The GeoTime Team

Oculus GeoTime 5.3 - What’s New Overview Webinar Recording is now live

Fri, 09 Mar 2012 17:35:18 GMT

For anyone who missed the GeoTime 5.3 - What’s New Overview Webinar, the recording has been posted on our YouTube channel. You can view it here:

GeoTime 5.3 - What's New Overview Webinar

We had a great turn out for the event and some really good questions at the end from attendees. This was our first webinar that was structured to be 30 minutes vs. the standard hour most webinars run. Feedback after the presentation was that things were a little fast, so we will aim to pace the presentations better for the shorter time spot on our next webinar. You can sign up to the next talk, “Human Movement Analysis” at the webinar registrations page.

We also had some great suggestions for future speakers, so thanks everyone who sent in their ideas. We will be working to contact new speakers and hope to announce our spring webinar schedule soon.
Have a suggestions for a future webinar topic or speaker? Let us know: info@geotime.com

Cheers,
The GeoTime Team

Down hill skiing GPS data now available

Wed, 29 Feb 2012 16:13:49 GMT

A few weeks ago we posted short video on the analysis of GPS data from a downhill skier at Marmot Basin, close to Jasper, Alberta, Canada.

We had a some of you write in to see if you could get your hands on the data we recorded and we are happy to share. You can download the data in three different formats below:

KML

CSV

GPX

We would love to see any analysis work done on the data, so please make sure to send us back a peek at what you are able to work up. And if you have any other requests for data, let us know @ info@geotime.com

Cheers,

The GeoTime Team

Cupid Strikes Again: Time Series + GIS: Together at last.

Tue, 14 Feb 2012 09:26:31 GMT

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

New Webinar Schedule And Registration Page Now Live

Wed, 08 Feb 2012 12:43:51 GMT

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

Analysis of GPS Data From A Downhill Skier - New Feature Sneak Peek

Mon, 30 Jan 2012 16:16:16 GMT

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.

Santa's voyage if he used global population ranking to plan his route

Sat, 24 Dec 2011 00:55:51 GMT

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.

Happy holidays everyone!

The GeoTime Team.

Interactive Timeline: Michael Jackson’s Billboard Rankings

Tue, 06 Dec 2011 12:04:58 GMT

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.

Looking At Time Series Data From ArcGIS 10

Fri, 02 Dec 2011 15:53:05 GMT

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:

Crisis Mappers Webinar Series

Thu, 01 Dec 2011 18:26:56 GMT

Over the past three years we have been working with the International Network of Crisis Mappers in support of the great work they are doing around leveraging technology for crisis mapping. Both Patrick Meier and Jen Ziemke, co-founders of the Crisis Mappers Network, have been bringing together researchers, practitioners, volunteers and industry professionals to share and discuss the many challenges and opportunities around crisis mapping. The GeoTime Team has participated in a number of Crisis Mappers’ activities, including the Crisis Mappers’ Webinar Series. These online presentations and discussions feature a variety of speakers from many different disciplines, relating their experiences and stories around crisis mapping. What’s great about these online sessions is the post-presentation discussions that break out and continue after the webinar has wrapped up.

We have a number of these webinars archived that we hope to start sharing here on the GeoTime(s) blog but if you are interested in checking them out right away, simply head over the Crisis Mappers’ website and register to get access to them.

Today we posted one of the more recent webinars with presenter Helena Puig from the United Nations Development Program's (UNDP) Threat and Risk Mapping Analysis unit in the Sudan, who gave a fabulous presentation on Crisis Mapping Analytics using data from conflicts in Sudan and Libya.

Upstream Data Mining And Data Viz Go Hand In Hand

Fri, 18 Nov 2011 14:05:14 GMT

A worthwhile read by Enrico Bertini on "Why Visualization Cannot Afford Ignoring Data Mining and Vice Versa".

Here are a few notable exerpts that we really enjoyed from his article:

- Data is full of rubbish: I repeated it several times in this blog. Data never comes for free, you have to manipulate it in order to accommodate the needs you have for your project. The most classical things you will need to deal with are: missing values, outliers detection, normalization, aggregation, sampling, etc., but every project comes with its own bag of necessary data wrangling. Each one of these requires robust and solid techniques, it is not something you can improvise. And no matter how skilled a data visualization expert you are, you will need to borrow solid techniques from dataminers, otherwise you are an amateur.

- Humans don’t scale, machines do: There is no way to visualize a billion items. really believe me, there’s no way to do that effectively. If you assign every item to one single pixel (known as pixel-based visualization), which is the maximum scalability available, you will need either a huge screen or very tiny pixels. In both cases our body has limitations. With a huge screen your perception is hampered by the maximum field of view, that is, there’s no way to embrace the whole screen with your eyes. With tiny pixels the human eye is limited by its maximum resolution. On the other hand machines do scale and can crunch monstrous amounts of data. Add a number of machines to your cluster and you have more power.

- You cannot trust black boxes. The issue of trust is very well known among dataminers: the models data mining algorithms build are often arcane and even if something seems to work, there’s no way to really understand why and how it works. Visualization has the power to shorten this gap and help model builders gain better confidence on the babies they build.

- There’s no right answer. Data Mining has a long tradition for providing tools to build models that give clear cut answers automatically: “should I give the loan to this customer or not?“. This is fine and useful and it’s been a very successful model for data mining so far. But many of the modern inquiries on data are not so clear-cut. Data analysis is often exploratory and and there’s no right answer. When mining is used for this purpose it necessarily needs a certain level of flexibility: ask a question, produce some initial results, visualize them, understand better the problem, change the parameters, use another algorithm, compare alternative results etc … and how do you do that without visualization?

Well worth the time for a full reading:

http://fellinlovewithdata.com/reflections/why-visualization-cannot-afford-ignoring-data-mining-and-vice-versa

20 Visualizations to Help You Understand Crime

Thu, 17 Nov 2011 17:02:56 GMT

If you work with crime data chances are you spend a lot of time trying to find crime trends for your self or for those you report to. With a good visualization finding these patterns and sharing this information becomes much easier. Here Flowing Data showcases 20 different ways you can visualize your data to help you understand your data. You'll notice that in this set mapping visualizations and statistical visualizations seem to be quite popular. When selecting a visualization method keep in mind what you would like to show with your data. For example, which of these 20 visualizations are better for finding patterns versus reporting trends? Maybe you're trying to reach a much broader audience and are simply trying to entertain as opposed to inform. Each visualization is has its own purpose. To help you decide which visualization is right for you we will periodically post blog articles about the strengths and weaknesses of differeint visualization methods.

Click on the image to open up the gallery.

Need help in choosing a visualization right now? We would be glad to give you a hand. Please do not hesitate to contact info@geotime.com with any questions you may have.

Investigating Money Laundering Cases: How The Who/Where/When Make All The Difference

Thu, 17 Nov 2011 15:01:16 GMT

A brief overview of the importance of the "Who/Where/When" when investigating money laundering cases. By looking at when someone is moving money around, patterns of illicit activity are clearly visible. It comes down to the face that techniques such as smurfing involve geographically diverse deposit locations and can be spread out over time, all to avoid detection. By seeing these geo-temporal patterns, it is possible to quickly identify new suspects by mapping the time and location of deposits to ATM video survaillance footage.

Money Laundering Investigation Using GeoTime

This short video shows what financial transactions look like over time and geography, which is key to being able to spot patterns. The next step is to show the relationship between the accounts and the associated individuals to understand how the money moves through a network of organized criminals.

Mapping the Mexican Drug War

Thu, 17 Nov 2011 10:24:57 GMT

The LA Times has put together a visualization summarizing the Mexican drug war. You'll notice that they have included information on key players, number of deaths (by week and location), and indicated regional hotspots. There are also some great interactive components within this graphic. You can adjust the timeline, associate each key player with a location, and filter by topic or location. If you were to use this visualization as a tool to summarize the drug war in Mexico, what other information would you want to see?

Click on the image below for the fully interactive graphic.

Choosing Clarity over Style: World Food Prices

Thu, 17 Nov 2011 09:45:27 GMT

One of the most important considerations to make when visualizating data is the complexity of your visualization. We all want the "wow factor" in our data, but there are times when a simpler approach to visualization tells a better story. Your aim should be to inform rather than to entertain. For example, look at the increase in world food prices as visualized in Wolfram Alpha. By using a simple line chart we can clearly see when the price of coffee has increased over the last 20 years. With few visual elements its easy to see the price spikes in lat 1994, 1998 and 2011. Below you will also see a collection of tables which give you the average current world price of different foods. Here a table works just fine becaue we are comparing the price of one food item at one point in time. It is easy to get the relative value of one item to another.

A Periodic Table of Visualization Methods

Thu, 17 Nov 2011 09:16:35 GMT

Visual-Literacy.org has provided this great interactive visualization of visualizations! In its Periodic Table of Visualization, they have categorized a multitude of visualization styles. They've also provided some suggestions on what type of visualizations are best for certain types of information. Roll over each visual element to view an example. Many of these examples would work well when you're trying to convey this information to others in presentations and reports. If you want to analyze data, you may want to consider making parts of these visualizations more dynamic. For example, with a Data Map it would be useful to have a dynamic animation in order to see changes in regional data over time. With a Semantic Network, it would be great to have filters which highlight important nodes within the network.

Click on the image below to open the interactive visualization.

7 Billion: How Did we Get So Big So fast - Dynamic Visualizations and Metaphors

Wed, 16 Nov 2011 15:09:44 GMT

Sometimes a static graphic alone can't tell the complex visual story hidden in your data. NPR has provided a great example in this video of how to using moving and animated elements to tell a story of how the world's population has grown to 7 billion people. Watch as they use the flow of water to indicate births and deaths and color to separate each continent. You'll notice they also shift between different visualization techniques to emphasise different elements of their story. For example, they use an Area Chart in order show the worlds total population grow over time. When you're visualization your data, keep in mind that you may need separate visual representations for the different types of data you wish to share.

Click on the Image below top view the video.

Announcing the new GeoTme(s) Blog

Mon, 14 Nov 2011 15:05:32 GMT

Today we are happy to launch the GeoTime(s) Blog, a new resource for all things related to movement analysis, data presentation and visual analytics. We will be using our new blog as place to share analysis techniques, customer stories, research work and interesting articles. It will be a collaborative effort between the GeoTime Team and our users, who are always coming up with new ways to use visual analysis tools to analyze and present complex data. As we are a company obsessed with all things visual, we will no doubt be sharing a lots of video content with you here on our new blog.