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EAGER: Completing the Lifecycle: Developing Evidence Based Models of Research Data Sharing

EAGER：完成生命周期：开发基于证据的研究数据共享模型

基本信息

批准号：
2135874
负责人：
Cynthia Vitale
金额：
$ 29.7万
依托单位：
Association of Research Libraries
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-08-01 至 2023-10-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2135874&HistoricalAwards=false
关键词：
EAGER Completing Lifecycle Developing Evidence

项目摘要

Effective data sharing practices are vital for the success of scientific research, especially in the emerging context of Open Science principles. This project will conduct a detailed analysis of data sharing activities in several specific institutional and organizational contexts in order to better understand the patterns, practices, costs, barriers, and workflows that support public access to research data. The project is being undertaken with coordination between several major associations which are key supporters of scientific research in the United States. Many academic institutions provide infrastructure to support researchers in data sharing activities. These services and infrastructures are often distributed across the institution, housed in various administrative units, such as campus IT, the university libraries, and the research office, among others. Given this distributed and often undocumented ad hoc nature, the true costs of public access to research data is not well understood. This project is designed to illuminate many of the currently unknown factors about the institutional landscape for public access to research data. The technical aspects of this analysis project are as follows. An assessment of research data repository use patterns will be accomplished by analyzing metadata harvested by means of the DataCite application programming interface (API). A retrospective study of discipline-specific and format-specific research data practices will be accomplished utilizing a NIST-based institutional functional model for public access to research data applied to a series of institutions and sub-disciplines. Finally, financial data will be collected and analyzed from the institutions using a combination of NAS and NIST cost models to consistently compare costs of data sharing activities and thereby produce a generalizable understanding of institutional expenditures.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.

有效的数据共享实践对于科学研究的成功至关重要，特别是在开放科学原则的新兴背景下。该项目将对若干具体机构和组织背景下的数据共享活动进行详细分析，以便更好地了解支持公众获取研究数据的模式、做法、成本、障碍和工作流程。该项目是在几个主要协会的协调下进行的，这些协会是美国科学研究的主要支持者。许多学术机构提供基础设施，以支持研究人员进行数据共享活动。这些服务和基础设施通常分布在整个机构中，位于各个行政单位中，例如校园IT，大学图书馆和研究办公室等。鉴于这种分散的、往往没有记录的临时性质，公众获取研究数据的真正成本还没有得到很好的理解。该项目旨在阐明公众获取研究数据的机构格局中目前未知的许多因素。该分析项目的技术方面如下。将通过分析利用DataCite应用程序编程接口（API）收集的元数据，完成对研究数据储存库使用模式的评估。将利用基于NIST的机构功能模型对应用于一系列机构和子学科的研究数据进行公众访问，对特定学科和特定格式的研究数据实践进行回顾性研究。最后，将使用NAS和NIST成本模型的组合从机构收集和分析财务数据，以持续比较数据共享活动的成本，从而对机构支出产生可概括的理解。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。