Why is Ordnance Survey interested in Semantics?
We are investing in semantic technology research to cut the cost and improve the accuracy of data integration. Data integration is widely acknowledged to be expensive and problematic. When such activities involve the inclusion of complex datasets such as OS MasterMap® the challenge becomes that much greater. The problem is more than a syntactic one and cannot be solved by everyone adhering to one file format or standard. Rather it is also a problem of understanding what the data means: is the Ordnance Survey definition of a field the same as the way the Government Department for the Environment, Food and Rural Affairs (DEFRA) would understand it? Our definition is spatially delineated by barriers such as fences or ditches, while DEFRA might distinguish a field’s extent by the kind of crops that were grown, as part of their task of calculating farmers’ subsidies. By providing a machine-readable description known as an ontology of Ordnance Survey’s data, these semantic differences are ma
