Integrated Spatio-Temporal Aggregate Data Series

该项目将创建并免费传播美国1790年至2010年的综合时空聚合数据系列（ISTADS）。为了减少研究障碍，该项目将建立一个综合数据库，使研究人员能够对共和国成立后几十年至今数千个小地理区域的空间和时间变化进行一致的分析。 该项目包括五项相辅相成的任务。 1.扩大现有的时空数据库，以纳入从若干来源获得的新的人口普查汇总数据，并增加国家一级的生命统计数据。2.设计一个有效的元数据系统，以确定各次普查的可比数据要素。该元数据将建立在明尼苏达大学和其他地方开发的数据整合元数据设计的最新创新基础上。3.编制涵盖两次至二十三次普查的综合统计表，在每个普查年列出可密切比较的类别，以便容易分析一段时间内的变化。4.创建综合地理单元，通过汇总和插值最大限度地提高跨时间可比性。5.为数据和元数据提供一个基于网络的接口，以便用户能够轻松地识别跨时间可比的数据，并能够导出适合统计分析和可视化的多年合并数据集，并将统计数据和相应的shapefile纳入地理信息系统或统计包。 这是人口和健康研究的基本基础设施，迫切需要。在地理信息系统框架内随时提供综合普查数据将为解决广泛的研究问题提供机会。关键领域包括居住隔离和定居模式;郊区化和城市无计划扩张;农村人口减少;贫困集中;生态系统变化的原因和程度;犯罪学;以及环境正义。几乎所有这些主题都对公共卫生有重要影响。现在，调查人员很难在不同时间以一致的方式分析小区域数据。通过创建访问这一庞大集合的基础设施，数据系列将首次使研究人员能够同时处理时间的广泛范围和空间组织的细节。这种跨时间和空间同时分析人类行为变化的能力将刺激从历史到流行病学等领域的创新。公共卫生相关性：拟议的数据库与国家卫生研究院作为国家医学和行为研究管理者的中心使命直接相关;这一基础设施将促进对人类人口动态性质的基础知识，并将激发新的健康相关研究。研究人员将有机会获得大量的汇总数据，包括自1900年以来的详细生育率和死亡率统计数据，这将使新的研究能够同时解决广泛的时间和空间组织的细节。

DESCRIPTION (provided by applicant): Project Summary This project will create and freely disseminate an Integrated Spatio-Temporal Aggregate Data Series (ISTADS) for the United States covering the years between 1790 and 2010. To reduce barriers to research, the project will build an integrated database that will enable researchers to undertake consistent analyses of spatial and temporal variation across thousands of small geographic areas from the first decades of the republic to the present. The project entails five complementary tasks. 1. Expand an existing spatio-temporal database to include newly-available aggregate census data from several sources and add county-level vital statistics. 2. Design an efficient metadata system that will identify comparable data elements across censuses. This metadata will build on recent innovations in the design of data integration metadata developed at the University of Minnesota and elsewhere. 3. Construct integrated statistical tables spanning between two and twenty-three censuses with closely comparable categories in each census year, allowing easy analysis of change over time. 4. Create integrated geographic units that maximize cross-temporal comparability through aggregation and interpolation. 5. Provide a web-based interface to data and metadata so that users can easily identify data that are comparable across time and can export multi-year merged datasets suitable for statistical analysis and visualization, and incorporate the statistical data and corresponding shapefiles into a GIS system or statistical package. This is basic infrastructure for population and health research and it is urgently needed. The ready availability of integrated aggregate census data in a GIS framework will offer opportunities to address a broad range of research problems. Key areas include residential segregation and settlement patterns; suburbanization and urban sprawl; rural depopulation; concentration of poverty; causes and levels of change in ecosystems; criminology; and environmental justice. Virtually all of these topics have important implications for public health. It is now exceedingly difficult for investigators to analyze small area data in a consistent way across time. By creating the infrastructure to access this vast collection, the data series will allow researchers for the first time to address simultaneously the broad sweep of time and the detail of spatial organization. This power to analyze variation in human behavior simultaneously across both time and space will stimulate innovation across fields ranging from history to epidemiology. PUBLIC HEALTH RELEVANCE: The proposed database is directly relevant to the central mission of the National Institutes of Health as the steward of medical and behavioral research for the nation; this infrastructure will advance fundamental knowledge about the nature of human population dynamics and will spark new health-related research. Researchers will have access to a vast collection of aggregate data including detailed fertility and mortality statistics for the period since 1900 that will allow new studies that address simultaneously the broad sweep of time and the detail of spatial organization.