In 2010 the American Community Survey (ACS) replaced the long form of the decennial census as the principal source for geographically detailed information about the population and economy of the United States. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ĭompeting interests: The authors have declared that no competing interests exist.
The Janus supercomputer is a joint effort of the University of Colorado Boulder, the University of Colorado Denver and the National Center for Atmospheric Research. This work utilized the Janus supercomputer, which is supported by the National Science Foundation (award number CNS-0821794) and the University of Colorado Boulder. įunding: This work was supported by the National Science Foundation (award number 113238).
All of the analysis code, sample data files, and a tutorial on their use are available at. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are creditedĭata Availability: This paper uses public domain data from the US Census Bureau. Received: ApAccepted: NovemPublished: February 27, 2015Ĭopyright: © 2015 Spielman, Folch. PLoS ONE 10(2):Īcademic Editor: Alejandro Raul Hernandez Montoya,
#CODE ON TIME DATA DRIVEN SURVEY HOW TO#
Here rather than focusing on the technical aspects of regionalization we demonstrate how to use a purpose built open source regionalization algorithm to process survey data in order to reduce the margins of error to a user-specified threshold.Ĭitation: Spielman SE, Folch DC (2015) Reducing Uncertainty in the American Community Survey through Data-Driven Regionalization. Regionalization is a complex combinatorial problem. This article presents a heuristic spatial optimization algorithm that is capable of reducing the margins of error in survey data via the creation of new composite geographies, a process called regionalization. Uncertainty of this magnitude complicates the use of social data in policy making, research, and governance. For example, in over 72% of census tracts, the estimated number of children under 5 in poverty has a margin of error greater than the estimate. However, estimates from the ACS can be highly unreliable. The ACS is used to allocate billions in federal spending and is a critical input to social scientific research in the US. The American Community Survey (ACS) is the largest survey of US households and is the principal source for neighborhood scale information about the US population and economy.
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