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Using Local Data to Drive Housing Loss Decision-Making

Mar 8 at 9:00 am - 10:00 am

Virtual Event Virtual Event
Free

Access to safe and affordable housing is a crucial determinant of well-being and resilience for individuals and families. Yet every year, five million Americans lose their homes through evictions and mortgage foreclosures. This displacement is linked to poor outcomes, including adverse health impacts, gaps in educational attainment, and chronic homelessness.

While many social organizations aim to reduce housing loss, they are often limited by piecemeal and low-quality data. Across the United States, the ability to access and understand housing loss varies widely by community. Data availability varies by locality and an individual’s ability to interpret it.

DataKind and New America Future of Land and Housing have teamed up to create and release an eviction and foreclosure data tool for the public good. As an open source, open access digital toolkit, this solution is intended to make digesting and analyzing jurisdiction-level eviction and foreclosure data easier for any actor. By making this information accessible to policymakers and direct service institutions, these actors can make data-driven decisions to combat housing insecurity. In this scenario, locally collected data can provide early indicators of housing insecurity that are likely or known to be predictors of vulnerability or eventual housing loss such that interventions can be deployed.

This event will include presenters and panelists from the technology and policy sectors to discuss this toolkit and demonstrate insights derived from NYC Open Data. Curious individuals will be encouraged to recreate the NYC Open Data solutions using the toolkit and NYC Open Data on their personal computers.

Details

Date:
Mar 8
Time:
9:00 am - 10:00 am
Cost:
Free
Event Category:
Event Tags:

Venue

Online

Organizers

DataKind
New America Future of Land and Housing

Other

Event Type
Online
Event Format
Talk or Panel, Presentation, Showcase
Social Media URL
https://twitter.com/datakind