One way firefighters world wide assist themselves while navigating through towns and cities is recording ‘distinctive points’ (actually that is how we navigate through smoke as well.) So instead of a ‘turn left at the third traffic light’ we often record ‘turn left at ABC Pharmacy’. So where does linked data come into play?
In the current economic situation shops come and go, so ‘ABC Pharmacy’ from the example might be long gone, leaving a driver clueless as where to turn left!
What stays the same is the address, but then again navigating on addresses is not really trustworthy so how can we use this address to generate a distinctive point?
In The Netherlands we have a public data set called ‘Building and Address Base Administration’ this is a official nation wide register of all buildings, dwellings and addresses throughout the country. One of the interesting features is that this data is internally interlinked, and uses nation wide unique identifiers. A absolute ideal situation to generate linked data from. If you inspect the dataset more closely you will actually find out that a address and a building are loosely coupled, that means if for some reason a full restructure of addresses takes place, the building identifiers stay the same.
Back to our problem, we want to know the business located in a specific building so we can use it to navigate. For this we use a semi official open chamber of commerce dataset which uses the building identifiers as location specifiers. This means that for generating the distinctive points, we only need to locate a building based on its address and then query the chamber of commerce data to see what business is located there!
So no matter what business is located in the building, as long as the building doesn’t move we can automatically find the businesses in that building and generate up to date distinctive points with linked data!