EVENT TimeMapper Visualizer

EVENT TimeMapper Visualizer

Dataset: GDELT Event Database

Description: Creates a timecoded Google Earth .KML file that allows you to visualize change over time and space, as well as a .CSV file for importing into GIS software and web mapping services.

Components: PERL, R, Google BigQuery

Acknowledgements: Makes use of Google BigQuery.

Example: Visualization of Nigeria in 2014

The EVENT TimeMapper Visualizer allows you to create unique spatio-temporal visualization that overlays all events matching your search onto a Google Earth display and timecodes each event such that you can use the Google Earth "time slider" feature to scroll through time to see patterns in how the matching events move through space over time. Events are clustered by date and location, so multiple events at the same location on a single day are collapsed into a single point on the visualization. Each location is color-coded according to the average Goldstein Scale of all events at that location on that day, from bright red (high conflict) to bright green (high cooperation), and sized based on the total number of events at that location on that day. Clicking on a location will display a popup with the number of events at that location on that date and a source citation for one of the events drawn at random. A .CSV file is also produced that contains the same information, but is designed for import to time-aware GIS software and/or web mapping services. This is one of the most advanced GDELT visualization tools in that it combines so many different dimensions into a single display that allows you to understand at-a-glance the macro-level patterns of your search.

No programming or technical skills are required to use this timeline visualization - you simply specify a set of criteria for the event type and actors involved, along with an optional date range, and the system will automatically search the entire GDELT Event Database for all matching entries and compile the final timeline. Your results will be emailed to you when complete, usually within 10 minutes, depending on server load and the time it takes to perform the necessary calculations. All GDELT Event Database records are scanned for your search parameters and the average prevalance of matching records is averaged by day. Thus, selecting "Nigeria" as the "Event Location", "Material Conflict" as the "Event Quad Class", and "Civilian" as the "Recipient/Victim (Actor2) Type" will generate a visualization of attacks against civilians and other conflict involving cvilians in Nigeria, with the ability to move the Google Earth timeslider back and forth to watching how violence has transitioned across the country.

Your Email Address

Creating these results can take several minutes depending on server demand - please provide the email address that the results should be sent to.

Email Address

Date Range

Limit the time period of analysis. The earliest allowable date for event data is currently January 1, 1979 and the latest date allowed is the current day.

Start Date
End Date
 

Search Criteria - Actors

Select the specific actors involved in the event. The CAMEO taxonomy used by GDELT codifies an "event" as an action performed by one entity (Actor1) onto another (Actor2). GDELT codifies an array of 58 fields of information about each event. Using the form below you can restrict your search to just those events initiated by a specific country and/or type against another country and/or type. For example, to select all attacks on civilians in Nigeria, you would specify "Civilians" using the "Actor2 Type" dropdown below, "Nigeria" using the "Event Location" dropdown below, and then violence-related event types using the next section. To select all protests in Nigeria, you would leave the Actor section below blank, and select protest-related event types from the following section and "Nigeria" as the "Event Location."

Initiator (Actor1) Country:

Initiator (Actor1) Type:

Recipient/Victim (Actor2) Country:

Recipient/Victim (Actor2) Type:

Search Criteria - Event

Select the specific type and/or location of events you are interested in. The full CAMEO taxonomy defines over 300 specific categories of events, but to simplify things, the search interface below lets you search only for the 20 root categories under which those other event types fall, or you can select by "Quad Class", which groups the 20 root categories into 4 "super categories".

Event Code:
     OR     
Event Quad Class:

Event Location:

Location Weighting

How should the "weight" of each location be calculated?

  • Number Events Each location is weighted by the total number of unique events found at that location, irrespective of how much news coverage each event received. This is useful to look strictly at the overall distribution of events, where all events are considered equal. Using this weighting, an event that is covered by 10,000 different news reports across the world will count the same as one that received just a single news report. This yields the best overall picture of where things are happening, but not necessarily where the "most important" ones are happening.
  • Number Articles Each location is weighted by the total number of news articles covering events found at that location. Using this weighting, an event that is covered by 10,000 different news reports across the world will count as 10,000 times more important as one that received just a single news report. This option uses the volume of media coverage of each event as a proxy for its perceived "importance" and thus offers the best overall picture of where the "most important" events are taking place (as measured by media coverage).

Outputs

The following output files will be generated:

  • Timecoded Google Earth .KML File Generates a timecoded Google Earth .KML file that allows you to visualize change over time and space.
  • .CSV File This outputs a .CSV file containing the same information as the .KML file, but in .CSV format for import to time-aware GIS software and/or web mapping services.