Making sense of the flood of Geo-tagged data

The web is a flood of geo-tagged data. Tools of the future will try to merge this data in to a meaningful larger picture. Photosynth from Microsoft tries to merge these images in to a larger 3D representation:



Clima.me is trying to aggregate larger corpus of data about a location than just images. Clima.me tries to build a index for the amount of geo-tagged data has been crowd sourced for any given location



Unlike Photosynth Clima.me can't tell you what a place looks like. But Photosynth can not tell you anything about the history or activity of an area. Clima.me score for the Covent Garden Apple stores shows it is an area of intense commerce, history and activity.



Here is an image taken from the British Museum. And below the Clima.me score for the same location.



Here you how the image aggregation and data analysis work together. You can tell from the statue that this location is a important cultural place, Clima.me confirms and extends this knowledge showing you it is a place with many entries in Wikipedia, many venues in Foursquare and Yelp, and how many images are being uploaded.

Form the image you can guess that this is a high cultural area able to hold some of the greatest treasures in human history. Form the Clima.me scores you can guess that any museum in the area would likely be first world.

The world of crowd sourced text and crowd sourced images reinforce each other, giving you a more complete idea of how the real world.

But Web data can often provide clues to a location the image can never hold. The above image by itself could be taken in any number of remote places. You can tell this is a peaceful spot, but how isolated is it.



Using the Clima.me score for the location you can easily see that this is a park close to a settled area, there is still web 3.0 activity and a good deal of Yelp activity around it.