Integrated Spatio-Temporal Aggregate Data Series

描述(由申请者提供)：项目摘要该项目将为美国创建并免费传播涵盖1790年至2010年的综合时空聚集数据系列(ISTADS)。为了减少研究障碍，该项目将建立一个综合数据库，使研究人员能够对从共和国成立头几十年到现在的数千个小地理区域进行一致的空间和时间变化分析。 该项目需要五项相辅相成的任务。 1.扩展现有的时空数据库，以包括来自几个来源的最新可用的综合普查数据，并增加县一级的重要统计数据。2.设计一个有效的元数据系统，以确定不同普查的可比数据元素。这一元数据将建立在明尼苏达大学和其他地方开发的数据集成元数据设计方面的最新创新之上。3.编制涵盖两次至二十三次人口普查的综合统计表，每一普查年的类别具有密切的可比性，便于分析随时间变化的情况。4.创建综合地理单元，通过聚合和内插最大限度地提高跨时间可比性。5.提供基于网络的数据和元数据界面，以便用户能够容易地识别具有时间可比性的数据，并能够输出适用于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并入地理信息系统或统计资料包。 这是人口与健康研究的基本基础设施，也是迫切需要的。在地理信息系统框架内随时可以获得综合汇总普查数据，这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。几乎所有这些话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范围的数据。通过创建访问这些海量集合的基础设施，这些数据系列将首次使研究人员能够同时处理广泛的时间范围和空间组织的细节。这种同时分析人类行为在时间和空间上的差异的能力将刺激从历史到流行病学的各个领域的创新。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核心使命直接相关；这一基础设施将促进对人类人口动态性质的基础知识，并将引发新的与健康相关的研究。研究人员将获得大量汇总数据，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处理广泛的时间范围和空间组织的细节。

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.