Collaborative Proposal: School Attendance Boundary Information System (SABINS)

协作提案- 1123727约翰·罗伯特·沃伦（PI）社会学系，系统的史蒂文·曼森（Co-PI）地理学系，明尼苏达大学的- 1123894塞尔瓦托·萨波里托（PI）社会学系，威廉和玛丽学院协作提案：学校出勤边界信息系统（SABINS）摘要由美国国家科学基金（NSF）资助（SES 0921794, 0921279），威廉玛丽学院和明尼苏达大学的pi创建了学校出勤边界信息系统（SABINS）数据基础设施项目。它旨在通过www.sabinsdata.org在GIS框架中传播小学、初中和高中出勤边界的丰富的新数据源。该数据库目前包含2009-2010学年三个州（明尼苏达州、特拉华州和俄勒冈州）的k -12年级入学率数据，全国13个大都市区的500多个学区，以及位于农村地区的5000多个统一学区。SABINS数据库中的每个学校出勤边界都与2010年十年一次人口普查和美国社区调查（ACS）的人口和住房数据相结合，允许用户分析一套广泛的社会和经济特征，描述居住在每个学校出勤区域内的人口。SABINS数据还与来自数据共同核心（CCD）的校级信息相结合，以便用户能够确定为每个学校出勤边界提供服务的学校的特征。SABINS项目的第二阶段以两种方式建立在最初投资的社会科学数据基础设施的基础上。首先，该数据库为现有的地理和表格文件增加了年度纵向更新，以便用户可以探索2009-2010学年至2011-2012学年的出勤率边界信息。由于ACS和CCD数据每年更新一次，用户将能够探索学校及其相应集水区的教育地理变化、人口变化和教育成果之间的动态相互作用。第二，新的活动将支持改进的数据检索系统，加强外联活动并提供强有力的用户支助。这一新阶段通过向包括学校和学区在内的所有用户免费提供SABINS数据，对国家网络基础设施做出了重大贡献。此外，该项目通过改进现有的软件工具来优化SABINS和相关数据（ACS， CCD）的数据传播和分析，利用美国国家科学基金会对明尼苏达大学国家历史地理信息系统（NHGIS）的现有投资。该数据库已经被广泛用于社会科学培训、地方、州和联邦各级的政策研究以及私营部门。SABINS项目将越来越多地用于基础社会科学研究，扩大地方和区域分析的范围，同时探索跨越时间和空间的变化。通过明尼苏达大学的NHGIS进行纵向数据的补充和传播，旨在使地方、州和联邦管理人员能够更有效地提供教育服务。

Collaborative ProposalSES - 1123727John Robert Warren (PI) Department of SociologySteven Manson (Co-PI) Department of GeographyUniversity of MinnesotaSES - 1123894Salvatore Saporito (PI)Department of SociologyThe College of William and MaryCollaborative Proposal: School Attendance Boundary Information System (SABINS)AbstractWith prior NSF funding (SES 0921794, 0921279), the PIs at the College of William and Mary and the University of Minnesota created the School Attendance Boundary Information System (SABINS) data infrastructure project. It is designed to disseminate a rich, new data source of elementary, middle and high school attendance boundaries in a GIS framework via www.sabinsdata.org. The database currently contains 2009-2010 school year data on K-12th grade school attendance boundaries for three states (Minnesota, Delaware and Oregon), over 500 districts embedded in 13 metropolitan areas across the country, and over 5,000 unified school districts located in mostly rural areas. Each school attendance boundary in the SABINS database is integrated with population and housing data from the 2010 Decennial Census and the American Community Survey (ACS), allowing users to analyze an extensive set of the social and economic characteristics describing populations residing within each school attendance zone. SABINS data are also integrated with school-level information from the Common Core of Data (CCD) so that users can identify the characteristics of schools that supply services to each school attendance boundary. This second phase of the SABINS project builds on the initial investment social science data infrastructure in two ways. First, the database adds annual, longitudinal updates to the existing geographic and tabular files so that users can explore school attendance boundary information for the 2009-2010 through the 2011-2012 school years. Since the ACS and CCD data are updated yearly, users will be able to explore the dynamic interplay between shifting educational geography, demographic change, and educational outcomes across schools and their corresponding catchment areas. Second, new activities will support an improved data retrieval system, enhance outreach activities and provide robust user support. Broader Impacts This new phase involves a significant contribution to national cyberinfrastructure by making the SABINS data freely available to all users, including schools and school districts. Moreover, the project leverages NSF's existing investment into the National Historical GIS (NHGIS) housed at the University of Minnesota by improving existing software tools that optimize data dissemination and analysis of SABINS and associated data (ACS, CCD). The database is already being used widely for social science training, for policy research at the local, state and federal levels, and in the private sector. The SABINS project will be increasingly accessible for basic social science research, broadening the scope of local and regional analyses to explore variations across time and space simultaneously. The addition of longitudinal data combined with dissemination via the NHGIS at the University of Minnesota seeks to enable local, state, and federal administrators to deliver educational services more efficiently.