2000115-Strengthening-Communities-with-Neighborhood-Data

2 Strengthening Communities with Neighborhood Data
were often available for cities as a whole, but almost never for individual
neighborhoods. This lack of neighborhood-level data resulted from the
prohibitive expense of plotting the locations of thousands of transactions
that backed up each of these indicators and then summarizing the results
by neighborhood.
Some researchers and practitioners saw the lack of data as a serious
problem early on. A good example is the view expressed by Ahlbrandt
and Brophy in their 1975 book Neighborhood Revitalization:
The formulation of a strategy to stem decline in an urban neighborhood requires
an understanding of the specific conditions that prevail in that location. This necessitates
the collection and evaluation of data describing the overall direction of
change in addition to the specific conditions affecting the viability of the neighborhood
housing market. . . . The measurement of housing and neighborhood
conditions has traditionally been expressed in physical terms . . . [that] fall short
of gauging the overall neighborhood conditions that comprise the larger housing
environment. . . . This larger neighborhood environment can be measured
by looking at the economic, social, psychological and demographic aspects of
the area. (53)
Some small-area data were available from the US Census Bureau’s
decennial censuses, but these did not include many indicators that were
of value in neighborhood planning, and updates of those few that were
available were frustratingly infrequent.
This dearth of neighborhood data was not just a problem for revitalization
planners. Police departments knew they needed to understand
many social, economic, and physical aspects of neighborhoods to spatially
target crime-fighting resources efficiently. Foundations realized
they could hardly begin to reliably understand what their grants were
accomplishing without factual information on how neighborhoods differed
from each other and how they were changing.
But in the early 1990s, a transformative new possibility emerged as
two trends reached critical thresholds. First, more and more local government
agencies had automated their administrative records, so that
records on transactions that contained an address or some other geographic
identifier were now computer based. Second, geographic information
system technology had reached a point at which it could process,
plot, and manipulate such data with considerable efficiency.
The payoff from these two developments, however, required yet
another innovation. Some entity in a city had to make it a part of its
mission to collect these data from various local agencies, enter the data