Our urban landscape is always changing: A booming housing development industry makes for a steady stream of new doorsteps on city blocks. Furthermore, regular government capital projects—such as the development of new parks or the redesign of dangerous street intersections—means the physical makeup of our city is constantly shifting, bit by bit. Changing neighborhood demographics necessitate redrawn City Council districts every decade.
Throughout these changes, the City’s operational agencies require trusted, up-to-date, and highly detailed geographic information. This is especially crucial for emergency services: When a New Yorker calls 911, or when streets are covered in snow, the clock starts ticking. The Police Department, the Fire Department, the Department of Sanitation, and many other agencies rely on Citywide Street Centerline (CSCL), a public dataset which serves as the geospatial data backbone of New York City government. CSCL lets agencies know where things are—and how to get there.
Jointly managed by the Department of City Planning and DoITT, CSCL data is updated daily with geographic data provided by the Borough Presidents, the Department of Buildings, the Department of Finance, the Board of Elections, and the City Council. Information on address ranges for a given block, the direction traffic can move on a given street segment, boundaries of community board and election districts, and LinkNYC kiosk locations are only a few of the dozens of locational attributes that fall under the purview of CSCL.
The effects of CSCL can be seen across the NYC Open Data Platform. Thanks to Local Law 108 of 2015, all datasets on NYC Open Data that contain a street address are required to have eight standardized geospatial attributes. The 80% of datasets that have so far met this requirement have CSCL to thank: The dataset supplies information to power GeoSupport, an application maintained by the Department of City Planning that is used by analysts and developers across the City to add locational attributes to data for mapping and analysis.