RCN: Building an Interdisciplinary Community of Big Microdata Researchers

该研究奖将支持大微数据网络的创建。通过多次收集，研究人员现在可以获得20亿份人口普查记录，这些记录描述了从19世纪中期到现在的整个美国人口。尽管这些数据集合具有丰富的研究潜力，但海量数据的规模和范围对研究人员提出了新的挑战。该网络将通过建立一个开放的跨学科研究人员社区来应对这些挑战。它将通过在线交流和面对面会议，包括四次年度研究会议，将这些研究人员联系起来。它将通过创建工作组来提供培训和指导，从而降低研究门槛。该网络还将向社区新成员开展外联活动，包括举办年度培训讲习班。外展工作将侧重于来自代表性不足群体的学者、职业生涯早期学者以及主要研究机构以外的人。该网络将通过参加该机构的暑期多样性奖学金计划，直接帮助培训人数不足的研究生和本科生。利用研究界的广泛经验和专业知识，该网络将吸引新的学者使用这些宝贵的数据资源，使新的研究成为可能。大微数据网络将支持一个新兴的跨学科科学家社区，使用大量人口普查微数据，描述从19世纪中叶到现在的美国人口。它将利用之前联邦政府在大规模人口普查数据收集方面的投资，这些数据描述了美国人口。IPUMS完整统计普查收集提供了1850年至1940年的一致编码数据，这些数据来自在72年要求之后公开发布的普查记录。联邦统计研究数据中心根据适当的数据安全措施提供对1960年至2010年十年一次的人口普查数据的访问。然而，一些研究人员缺乏利用这些数据所需的计算能力，即使是那些拥有足够资源的人也需要新的编程策略来操纵和分析这种规模的数据。记录关联带来了一系列问题，从分析决策到计算能力。致力于开发地理细节的调查人员还面临着相当大的启动成本，用于地理编码、开发地理信息系统边界文件，以及对邻居和邻居的新地理测量进行概念化。有关数据访问的限制限制了共享资源，并给数据复制和保存带来了困难。通过增加访问和降低使用这些数据的门槛，该网络将帮助研究人员克服这些挑战。它将推动一系列领域的学术研究，包括经济学、社会学、人口学、统计学、地理学、流行病学、城市规划和公共政策。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This research award will support the creation of the Big Microdata Network. Through multiple collections, researchers now have access to two billion census records describing the entire American population from the mid-nineteenth century to the present day. Although these data collections have rich research potential, the massive scale and scope of the data poses new challenges for researchers. The Network will address these challenges by building an open interdisciplinary community of researchers. It will connect these researchers through online communication and in-person meetings, including four annual research conferences. It will lower barriers to research by creating working groups to provide training and guidance. The Network also will conduct outreach to new community members, including annual training workshops. Outreach efforts will focus on scholars from underrepresented groups, early career scholars, and those outside major research institutions. The Network will directly contribute to the training of underrepresented graduate and undergraduate students through participation in the institution's Summer Diversity Fellowship program. Leveraging the broad experiences and expertise of the research community, the Network will attract new scholars to these valuable data resources, enabling new research.The Big Microdata Network will support an emerging interdisciplinary community of scientists using vast collections of census microdata describing the American population from the mid-nineteenth century to the present day. It will leverage previous federal investment in massive census data collections which describe the American population. The IPUMS full-count census collection provides consistently coded data from 1850 to 1940 from census records that have been released publicly following the 72-year requirement. The Federal Statistical Research Data Centers provide access to decennial census data for 1960 to 2010 under appropriate data security measures. Some researchers, however, lack the computing power necessary to take advantage of these data, and even those with sufficient resources still require new programming strategies to manipulate and analyze data of this scale. Record linkage poses a host of problems, from analytic decisions to computational capacity. Investigators working to exploit geographic detail also face considerable startup costs for geocoding, developing GIS boundary files, and conceptualizing new geographic measures of neighbors and neighborhoods. Restrictions around data access pose constraints for sharing resources and present difficulties for data replication and preservation. By increasing access and lowering barriers to using these data, the Network will help researchers overcome these challenges. It will advance scholarship across a range of fields, including economics, sociology, demography, statistics, geography, epidemiology, urban planning, and public policy.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.