Location is everywhere, literally. Therefore almost every dataset contains geographic information like coordinates, addresses or toponyms. This information enables the data to be embedded in the space we live in. The embedding of multiple datasets facilitates their combination and comparison and allows for more complex spatial analyses. As in other disciplines the main challenge in spatial analytics is the practical application. That's where the focus of the Expert Group lies, i.e. in :
Spatial information integration (i.e. georeferencing): How can data be prepared for spatial analytics, i.e. what are suitable geodata models, formats (and ev. tools)?
Open geodata catalog: Is it possible to build and maintain a living list of geo-datasets that can be used for spatial analytics?
Applying location-based algorithms: What algorithms exist and what are the dos and don’ts?
Visualization: What tools exist for communicating the spatial analytics output?