Google Earth Visualization
We have created a KML file for Google Earth of power plant data that you can download and view on your computer using Google Earth. Just start Google Earth, click on "File", "Open", and select the EnipediaPowerPlants.kml you just downloaded. Go to Tools -> Options -> General -> "Show web results in external browser". This will make your webbrowser load any enipedia pages you may want to consult.
We think this way the data on Enipedia is more accessible. Each of the icons displayed indicates the fuel types used by various power plants. Icons with a question mark () mean that we do not yet have information on their fuel type. The size of the circles around each power plant represents the electrical power output (MWh) as of 2007. When you are zoomed out, you will see the largest plants, while zooming in will reveal even the smallest power plants.
For each of the power plants that you see, there is a corresponding page in enipedia that contains more information on it. By clicking on a power plant's icon, a box pops up that contains the enipedia link to this page. Depending on how Google Earth is set up, once you click on this, the web page will either appear in Google Earth, or a separate web browser.
- note: loading enipedia pages WITHIN Google Earth may be very slow. This is a problem in Google Earth, the community has been notified.
- remedy: in Google Earth, go to Tools -> Options -> General -> "Show web results in external browser".
 Update/Synchonization Schedule
The data in the Google Earth Visualization is regenerated from the latest data in the wiki early in the morning every day (3 am Central European Time). Any updates that you make to coordinates and fuel types will show up after then.
 Technical Details for Google Earth Visualization
The KML file is generated by a combination of tools. We use an R script to query the SPARQL endpoint of Enipedia for the latest data (using the SPARQL library for R). Once the data is loaded, we use the geosphere library to help draw the circles indicating power output, and then pass all this through the regionator python library to generate the network links that enable a smooth browsing experience by progressively loading data.