Archiv für den Tag: 25.2.2009

GGeodata – The Google Spatial Data Infrastructure (GSDI)

Recently, Google announced an extension to its API to pull Map Maker Tiles – something, that was already predicted more than a year ago. Then, shortly after, the news about recent developments related to Google Map Maker – the new directions feature for MapMaker. Also reading about how TomTom is using GPS traits from its customers to improve the quality of their map database, Google’s Street View data coverage and about the new Google Android My Tracks application, that can record tracks from outdoor enthusiasts and then maybe do something not-evil with them… and finally…Blink!

I just can’t help but wonder how long it will take, until Google will have built up its own Spatial Data Infrastructure (SDI) – the GGeodata – a Google SDI that will join the data pools already available from government mapping agencies, the commercial geodata providers like Tele Atlas or Navteq and the OpenStreetMap project. It looks like Google can already build its own base map for many parts of the world. I always wondered why Google does not use OpenStreetMap data to fill in the gaps in their maps, but licence issues are probably a good explanation why that is not happening.

I could imagine that Your Tracks will soon contribute to an offroad map database. In a similar way, all sorts of GPS tracking data, for instance generated via Latitude could be used to enhance the quantity and quality of the huge data pool that may be fed into the super-analysis machine.

I wonder if someone will figure out how to automatically create a routing enabled network from spatio-temporal tracking data – would be much more convinient than waiting for the crowd to do their volunteering job by digitising and defining attributes. What if you could use geospatial lifeline data (pdf!) and all kinds of other automatically generated tracking data and work out the segments and nodes by aggregating all the data and applying some magic analysis recipe to it. Speed of movement at certain times by a certain amount of people… many things could be inferred…

But how do you gather all the required data if you are not Google or a mobile network operator? Maybe you found OpenGeoSpatialLifelines – but that sounds too complicated for a project title – so how about we just call it OpenLifelines – or even better OpenTraces, and make it a place where people can anonymously share their spatio-temporal location data. Then we would only need the magic recipe – So anyone volunteering to have a go at the algorighm?