The Urban Data Store is a collection of databases on the social, economic and environmental performance of the city.
These databases can be organised by an Urban DataFrame. Like threads being organised by a loom. Without the loom they are just threads: disconnected on reels or tangled in a pile. The DataFrame organises and makes sense of the threads.
Components of the Urban DataFrame
The DataFrame has spatial and temporal components.
The Temporal DataFrame is perhaps the more straightforward. A linear sequence – 1 dimension ie time goes forwards and backwards, not sideways or upwards. Databases are time-stamped, allowing temporal analysis: what happened when?
The Spatial DataFrame of the City is its street network and building footprints. Being more complex – having 3 dimensions – this is organised configurationally using Space Syntax spatial network analysis. What happened where?
Benefits of the Urban DataFrame
In combination with the Urban DataConnector, the DataFrame makes sense if the data threads, finding cause-and-effect associations and correlational patterns within them. This knowledge forms the basis for future evidence-informed urban policy making and planning decisions, the likely impacts of which can be modelled in advance.