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National Neighborhood Data Archive (NaNDA)

National Neighborhood Data Archive

Existing and New Data

Mar 3, 2023

Image of a laptop computer on a desk next to a printout of various charts - a line chart, a bar chart, a pie chart.Today we’re here to share more about what datasets we already have and what we’re still working on.

Neighborhoods are complicated systems of location and characteristics and cannot be easily defined or pinned to a specific street or block. To aid researchers, we provide measures at a variety of levels—usually census tract, zip code tabulation areas, or counties.

We have datasets on the following characteristics:

Infrastructure
Broadband Internet Availability, Speed, and Adoption
Internet Access
Street Connectivity
Primary and Secondary Roads
Public Transit Stops
Traffic Volume
Education
Neighborhood School Gap
School District Characteristics
School Counts
Environment
Parks
Land Cover
Polluting Sites
Community
Socioeconomic and Demographic Characteristics
Voter Registration, Turnout, and Partisanship
Urbanicity
Crimes

For more details about our current datasets, visit the data page on our website and the curated list with ICPSR.

Additionally, we are currently updating datasets on the following characteristics:

  • Fast Food Restaurants
  • Eating and Drinking Places
  • Religious Organizations
  • Civic and Social Organizations
  • Arts, Entertainment, and Recreation Organizations
  • Retail Establishments
  • Law Enforcement Organizations
  • Personal Care Services and Laundromats
  • Social Services
  • Health Care Services
  • Grocery Stores
  • Liquor, Tobacco, and Convenience Stores
  • Dollar Stores

Some of these datasets are being curated by ICPSR staff, and others we are still cleaning up. We want to make sure we are using the best possible source data, so we are taking our time to make sure each dataset is accurate and fix minor errors before publishing them. We will post on here and our Twitter as new datasets are released.

Lastly, we wanted to share two recent publications that used NaNDA datasets:

We’ll be back soon to share what else we’ve been up to!