EAGER: Collaborative Research: A Benchmark Data Linkage Repository (DLRep)

EAGER：协作研究：基准数据链接存储库 (DLRep)

• 批准号: 1744065
• 负责人: Margaret Levenstein
• 金额: $ 26万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2021-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1744065&HistoricalAwards=false
• 关键词: EAGER; Collaborative; Research; Benchmark; Data

This EAGER award provides pilot funding for a new kind of software repository that could help data scientists create better ways to combine existing data sets. The goal is to encourage collaboration between scientists who consider data methodology, users and builders of integrated data sets, and data custodians. The result may be new high-quality methods for record linkages and better use of existing data. Common, transparent, and reproducible approaches to linkage methodology and privacy preservation will help data analysts meet the highest scientific standards. The project may decrease the gap between research and practice in data science, resulting in better evidence for U.S. policymakers, businesses, and citizens.The PIs will establish a common benchmarking repository of linkage methodologies, Data Link Repository (DLRep) at the Inter-University Consortium for Political and Social Research (ICPSR) at the University of Michigan. Participants in the repository will be able to add comments and ask questions, allowing for engagement between data custodians, providers, producers, holders and data users, as well as between various groups of data users. In addition data users will be able to upload and share code snippets related to the data, allowing for knowledge sharing and better reproducibility. Data users will be able to link related publications and citations via DOI import or by manually entering citation information. This will provide feedback to data providers and other data users about how the data have been used. The repository will accelerate the development of new record linkage algorithms and evaluation methods by providing access to both methods and relevant data. This community effort will improved the reproducibility of analysis conducted on integrated data. The repository will facilitate comparisons of alternative linkage methodologies when using the same and different data, and move forward the provision of privacy-aware integrated data.

EAGER奖为一种新型软件存储库提供试点资金，该软件存储库可以帮助数据科学家创建更好的方法来联合收割机组合现有数据集。目标是鼓励考虑数据方法的科学家、综合数据集的用户和构建者以及数据保管人之间的合作。其结果可能是记录联系和更好地利用现有数据的新的高质量方法。通用、透明和可复制的链接方法和隐私保护方法将有助于数据分析师达到最高的科学标准。该项目可能会缩小数据科学研究与实践之间的差距，为美国决策者、企业和公民提供更好的证据。PI将在密歇根大学的跨大学政治和社会研究联盟（ICPSR）建立一个通用的链接方法基准库，即数据链接库（DLRep）。存储库的参与者将能够添加评论和提出问题，从而使数据保管人、提供者、制作者、持有者和数据用户之间以及不同数据用户群体之间能够进行互动。此外，数据用户将能够上传和共享与数据相关的代码片段，从而实现知识共享和更好的再现性。数据用户将能够通过DOI导入或手动输入引文信息链接相关出版物和引文。这将向数据提供者和其他数据使用者提供有关数据使用情况的反馈。该储存库将通过提供查阅方法和相关数据的途径，加快新的记录链接算法和评价方法的开发。这一社区努力将提高对综合数据进行分析的可重复性。该数据库将便利在使用相同和不同数据时对备选联系方法进行比较，并推动提供注重隐私的综合数据。