EAGER: Enhanced Robust Persistent Identification of Data (E-RPID)

EAGER：增强型稳健持久数据识别 (E-RPID)

• 批准号: 1839013
• 负责人: Robert Quick
• 金额: $ 30万
• 依托单位: Indiana University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-10-01 至 2021-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1839013&HistoricalAwards=false
• 关键词: EAGER; Enhanced; Robust; Persistent; Identification

An increasing challenge in modern research is the rapid growth in ability to collect and store research data; this growth is much more rapid than the ability to catalog, make accessible, and reuse these data. Major challenges facing the scientific research enterprise include making data discoverable, accessible, and re-usable at Internet scales; and making it possible to use data to replicate analyses done in published research. The importance of this issue is at the center of many recent initiatives in Open Science and Open Data. The objective of this project is to address these deficiencies and to enable more options for data interoperability and reusability in the current research data landscape. One aim is to demonstrate how technical solutions for data accessibility and management should be designed, implemented, operated, and usable by a broad range of researchers. Another aim is to ultimately increase the publication, discovery, and reuse of data, thus contributing to the greater integrity of the scientific enterprise.This project aims to create a full implementation of the Digital Object Architecture (DOA) concept to improve data interoperability and reusability and potentially transform the way research in many disciplines is conducted. The approach is to integrate existing and new software components into the Robust Persistent Identification of Data (RPID) testbed which itself is a 2-year pilot project supported by NSF (Project ID 1659310). Components to be added include a Digital Object Interface Protocol (DOIP) which defines common operations performed on digital objects; and a Repository Mapping Service which would allow mapping the contents of existing repositories to the Digital Object Architecture (DOA) environment. With the new components, the ensemble "Enhanced-RPID" (E-RPID) testbed will allow managing of data objects by assigning individual identifiers toward making data FAIR (findable, accessible, interoperable, and reusable). This technical effort along with planned educational material are designed to lower the barrier for adoption of Persistent Identification (PID)-centric data management throughout the data lifecycle, from initial data collection to long-term use and reuse. The E-RPID testbed will be housed on the NSF-funded Jetstream computational resource, will be applied to a number of important scientific use cases, and will contribute to activities fostered by the Research Data Alliance (RDA). The outcomes of this project are aimed to broadly benefit disciplinary and multi-disciplinary research and to facilitate better access to and utilization of existing data repositories.This project is supported by the National Science Foundation's Public Access Initiative which is managed by the NSF Office of Advanced Cyberinfrastructure on behalf of the Foundation.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.

现代研究的挑战越来越大，是收集和存储研究数据的能力的快速增长。这种增长比目录，使访问和重复使用这些数据的能力快得多。科学研究企业面临的重大挑战包括在互联网尺度上可以发现数据，可访问和重新使用的数据；并可以使用数据复制在已发表研究中进行的分析。这个问题的重要性是开放科学和开放数据最近许多计划的核心。该项目的目的是解决这些缺陷，并为当前研究数据格局中的数据互操作性和可重复使用启用更多选择。一个目的是证明如何设计，实施，操作和可供广泛的研究人员设计，实施，操作和使用技术解决方案。另一个目的是最终增加数据的出版，发现和重复使用，从而有助于科学企业的更大完整性。此项目旨在创建数字对象体系结构（DOA）概念的全面实施，以提高数据互操作性和可重复性并有可能改变许多学科研究的方式。该方法是将现有和新软件组件集成到对数据（RPID）测试床的稳健持久识别中，该识别本身是由NSF（项目ID 1659310）支持的2年试点项目。要添加的组件包括一个数字对象接口协议（DOIP），该协议定义了在数字对象上执行的常见操作；以及一个存储库映射服务，该服务将允许将现有存储库的内容映射到数字对象体系结构（DOA）环境。借助新组件，集合“增强RPID”（E-RPID）测试床将允许通过分配单个标识符使数据公平（可访问，可访问，可互操作和可重复使用）来管理数据对象。这项技术工作以及计划的教育材料旨在降低整个数据生命周期中采用持续识别（PID）中心数据管理的障碍，从初始数据收集到长期使用和再利用。 E-RPID测试床将安置在NSF资助的Jetstream计算资源上，将应用于许多重要的科学用例，并将为研究数据联盟（RDA）培养的活动做出贡献。 该项目的结果旨在广泛利益纪律和多学科研究，并促进更好地访问和利用现有数据存储库。该项目得到了国家科学基金会的公共访问计划的支持，该项目由NSF高级办公室管理该奖项反映了NSF的法定任务，并被认为是通过基金会的知识分子优点和更广泛的影响标准通过评估来表示支持的。

项目成果

FAIR Data and Services in Biodiversity Science and Geoscience

• DOI: 10.1162/dint_a_00034
• 发表时间: 2020-12-01
• 期刊: DATA INTELLIGENCE
• 影响因子: 3.9
• 作者: Lannom, Larry;Koureas, Dimitris;Hardisty, Alex R.
• 通讯作者: Hardisty, Alex R.