A Secure Hub for Access, Reliability, and Exchange of Data (SHARED)

芝加哥大学的Secure Hub for Access，Reliability，and Exchange of Data（SHARED）是数据驱动型研究的资源，也是集成数据管理平台的核心。它为跨学科的项目提供联合数据存储，以促进数据管理中的协作和最佳实践。它与芝加哥大学的机构知识库集成，根据FAIR原则进行数据共享。SHARED由大学图书馆和研究计算中心领导，与大学信息技术服务，数据科学研究所和物理科学部门合作。与大学的数据收集，分析，发布，分发和长期存档的生命周期战略相一致，它确保了对数据的访问并将其整合到更广泛的生态系统中。SHARED迎合了跨越宇宙学、粒子物理学、语言学和心理学的各种科学应用。通过SHARED的3.9PB ceph存储平台，该项目支持专注于暗物质搜索，超越标准模型的物理学，宇宙再电离模拟，宇宙微波背景辐射调查和天体物理等离子体动力学模拟的项目。此外，它保留了宝贵的神经和语言数据，有助于理解认知过程和语言多样性。SHARED项目促进跨学科研究，并通过与少数民族服务机构和K-12学生的合作提供数据科学教育机会。利用像芝加哥大学和芝加哥城市学院数据科学导师计划这样的合作伙伴关系，它增强了劳动力的多样性，并促进了数据相关的教育。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The University of Chicago's Secure Hub for Access, Reliability, and Exchange of Data, (SHARED), serves as a resource for data-driven research and nucleus of an integrated data management platform. It provides federated data storage for projects across disciplines to facilitate collaboration and best practice in data management. It is integrated with UChicago's institutional repository for data sharing according to FAIR principles. SHARED is led by the University Library and Research Computing Center, with collaboration from University Information Technology Services, the Data Sciences Institute, and the Physical Sciences Division. Aligned with the university's data lifecycle strategy for collection, analysis, publication, distribution, and long-term archiving, it ensures access to data and their integration into broader ecosystems. SHARED caters to diverse scientific applications spanning cosmology, particle physics, linguistics, and psychology. Through SHARED’s 3.9PB ceph-based storage platform, the project supports projects focused on dark matter searches, physics beyond the Standard Model, simulations of cosmic reionization, surveys of cosmic microwave background radiation, and kinetic simulations of astrophysical plasmas. Additionally, it preserves valuable neural and linguistic data, contributing to understanding cognitive processes and language diversity. The SHARED project promotes interdisciplinary research and provides educational opportunities in data science through collaborations with minority-serving institutions and K-12 student engagement. Leveraging partnerships like the University of Chicago and Chicago City Colleges Data Science Preceptorship program, it enhances workforce diversity and fosters data-related education.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.