EAGER: Secure Research Impact Metric Data Exchange: Data Supply Chain and Vocabulary Development

EAGER：安全研究影响指标数据交换：数据供应链和词汇开发

• 批准号: 2335827
• 负责人: Christina Drummond
• 金额: $ 10万
• 依托单位: University of North Texas
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2335827&HistoricalAwards=false
• 关键词: EAGER; Secure; Research; Impact; Metric

Fostering open science requires usage and impact data for publicly accessible information. This project will advance open science by accomplishing the following: a) documenting the usage and impact data supply chain for article and data research outputs, to complement findings for books, and b) engaging research infrastructure stakeholders to crosswalk usage and impact related vocabularies across scholarship outputs and disciplines. The usage and impact data pertaining to a single publicly accessible research output (book, article, or dataset) are created across a complex array of public and private publishers, publication distributors and aggregators, repositories, discovery services and service platforms. Comparable, high-quality information access is vital to research information management systems, impact reporting, and innovation policy; and is inherent to the provision of scholarship impact statements alongside data management plans. Yet, compiling usage and impact metrics for publicly accessible scholarship across public and private repositories, services, and publishers is a time and data-science intensive activity undertaken by individual researchers, universities, libraries, and publishers. While services provision some usage data, challenges related to secure data brokerage, automated data access, and auditing by a trusted, neutral infrastructure complicate the exchange and aggregation of usage data across commercial and non-commercial competitors. This project aims to inform whether a national cyberinfrastructure is needed to support the exchange and processing of sensitive and proprietary usage and impact metrics generated by US-based research publishers and distributors.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.

促进开放科学需要公开获取信息的使用和影响数据。该项目将通过完成以下工作来推进开放科学：a)记录文章和数据研究产出的使用和影响数据供应链，以补充书籍的发现；b)吸引研究基础设施利益相关者在学术产出和学科之间交叉使用和影响相关词汇。与单一可公开访问的研究成果（书籍、文章或数据集）相关的使用和影响数据是在公共和私人出版商、出版物分销商和聚合器、存储库、发现服务和服务平台的复杂数组中创建的。可比较的、高质量的信息获取对研究信息管理系统、影响报告和创新政策至关重要；这是提供奖学金影响声明和数据管理计划所固有的。然而，在公共和私人存储库、服务和出版商中编制可公开访问的奖学金的使用情况和影响指标是一项耗时且数据科学密集型的活动，由个人研究人员、大学、图书馆和出版商承担。虽然服务提供了一些使用数据，但与安全数据代理、自动数据访问和可信的中立基础设施审计相关的挑战使跨商业和非商业竞争对手的使用数据交换和聚合变得复杂。该项目旨在告知是否需要一个国家网络基础设施来支持交换和处理美国研究出版商和分销商产生的敏感和专有使用和影响指标。该奖项反映了美国国家科学基金会的法定使命，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。