EAGER: Expanding public access to restricted research data

行为科学、社会科学、教育科学、计算科学和生命科学等学科的研究人员收集的数据，由于隐私问题、政治风险、文化敏感性、法律的或政策限制以及知识产权限制，这些数据的共享可能会带来重大的实践和道德挑战。研究人员应该如何保护数据，同时使访问尽可能开放，符合开放科学的原则？数据存储库应该如何以鼓励适当使用的方式清楚地传达谁拥有什么样的访问权限？ 该项目将创建可推广的模型和基础设施，在提供研究数据和材料的开放访问与保护研究数据之间取得平衡。这些成果将通过加强现有的研究数据基础设施来支持跨科学领域的透明、可复制、综合、跨学科和产生洞察力的研究。该基础设施专门用于与有限的科学受众共享敏感的研究数据。拟议的基础设施建立在Databrary.org上，这是一个专门存储和共享视频数据和文档的受限访问数据库。数据库由PI在NSF的支持下共同开发。该项目有两个目标：（1）对NSF支持的数据库数字图书馆实施接口和元数据增强，以使敏感的、限制访问的数据最大限度地向最广泛的受众开放，包括NSF公共访问存储库（NSF-PAR）的用户，以及（2）确保数据库体现最佳实践并广泛分享其创新。与这些目标相关的活动将扩大对数据库现有馆藏的访问，提高共享数据的可查找性、可访问性、互操作性和可重用性，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进行评估，被认为值得支持的搜索.

Researchers in disciplines across the behavioral, social, educational, computational, and life sciences collect data whose sharing can pose significant practical and ethical challenges due to privacy concerns, political risk, cultural sensitivities, legal or policy restrictions, and intellectual property constraints. How should researchers protect data while making access as open as possible, in alignment with the principles of open science? And how should data repositories clearly communicate who has what sort of access in ways that encourage suitable uses? This project will create generalizable models and infrastructure that strike a balance between providing open access to research data and materials while protecting research data. The results will bolster transparent, reproducible, integrative, interdisciplinary and insight-generating research across scientific fields by enhancing an existing research data infrastructure that specializes in sharing sensitive research data with restricted scientific audiences.The proposed infrastructure builds on Databrary.org, a restricted access data library specializing in storing and sharing video data and documentation. Databrary was co-developed by the PI with support from NSF. The project has two aims: (1) Implement interface and metadata enhancements to the NSF-supported Databrary digital library to make sensitive, restricted-access data maximally discoverable to the widest range of audiences, including users of the NSF Public Access Repository (NSF-PAR), and (2) Ensure that Databrary embodies best practices and shares its innovations widely. The activities associated with these aims will expand access to Databrary’s existing holdings, improve the findability, accessibility, interoperability, and reusability of data shared there, and provide insights and knowledge that should benefit other scholarly communities facing similar challenges.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.