Improving Communities through Integrated Data Systems: Homeless Shelter Entry and Neighborhood Conditions
New York University’s Furman Center for Real Estate and Urban Policy is planning to work with the NYC Center for Innovation through Data Intelligence (CIDI) to study the factors that best predict entry into New York City homeless shelters. The planned project would identify the specific individual, housing, and neighborhood situations, such as receipt of public assistance and other city services, housing code violations, property turnover, a property’s status as subsidized housing, incidence of foreclosures, and neighborhood crime rates, families face before they enter the shelter system.
Data on building characteristics and neighborhood conditions will come from the Furman Center’s own databases. The Subsidized Housing Information System (SHIP) contains property-level data on the financial and physical characteristics of privately-owned subsidized rental properties in New York City. The Furman Center also has access to 311 complaints, rental registrations, code violations, building characteristics, property sales, mortgages, property taxes, crime complaints, building permits, and building complaints. This building and neighborhood data will be linked at the address-level to CIDI’s Worker Connect, an IDS that includes information on household composition and on city services used. Additional data on shelter entry and exits is in the process of procurement.
Analysis of these data, when linked, can help New York City’s Department of Homeless Services (NYC DHS) make more informed decisions about where and when to concentrate prevention services to help stabilize a family’s housing situation.