2000115-Strengthening-Communities-with-Neighborhood-Data

318 Strengthening Communities with Neighborhood Data
are dynamic because they are in constant motion: even stable neighborhoods
are constantly renewing their population, business base, and
housing stock. Moreover, these dynamics are determined by the operation
of social, political and economic systems (such as housing and labor
markets, social networks, and local governance) that go well beyond the
neighborhood itself. Neighborhoods are also diverse: there are different
types of neighborhoods (ranging from bedroom communities to “bohemian”
areas to “ports of entry”) characterized by their mix of people,
businesses, real estate, and physical environment. Different types of
neighborhoods are likely to perform different functions for their residents
and play different roles within the regional economy in which they
are embedded.
The ability to measure and analyze complex neighborhood dynamics
starts with good data, which are increasingly available thanks to initiatives
like the National Neighborhood Indicators Partnership (NNIP). For many
large cities at least, neighborhood- or even parcel-level data can now be
found for various real estate, business, and demographic indicators.
These data now make it possible to engage in more detailed analyses
and more in-depth investigations of the drivers of neighborhood
change. Building on better data and knowledge, it is also possible to build
more powerful tools to guide neighborhood investment. The Dynamic
Neighborhood Taxonomy project, described in this essay, was designed
as a baseline research and development effort with the goal of advancing
community and economic development in this direction.
The Dynamic Neighborhood Taxonomy Project
Living Cities, a collaborative of 22 of the world’s largest foundations and
financial institutions, launched the Dynamic Neighborhood Taxonomy
project (DNT) in 2007 as an ambitious, large-scale effort to begin developing
a new generation of community development tools. The project
was designed to improve our understanding of how neighborhoods
operate, including how they change over time, what factors determine
their success, and how these basic dynamics vary across different types of
neighborhoods. More important, DNT aimed to fundamentally enhance
the field’s ongoing capacity to routinely, accurately, and more easily analyze
the challenges and opportunities for development in particular
places. Ultimately, the goal was to help businesses, investors, funders,