Collaborative Research Data Afterlives: The long-term impact of NSF Data Management Plans on data archiving and sharing for increased access

协作研究数据的来世：NSF 数据管理计划对数据归档和共享以增加访问的长期影响

• 批准号: 2020183
• 负责人: Megan Finn
• 金额: $ 17.41万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2020183&HistoricalAwards=false
• 关键词: Collaborative; Research; Data; Afterlives; long

In 2011, the National Science Foundation began requiring that all funded projects provide data management plans (DMPs) to ensure that project data, computer codes, and methodological procedures were available to other scientists for future use. However, the extent to which these data management requirements have resulted in more and better use of project data remains an open question. This project thus investigates the National Science Foundation’s DMP mandate as a national science policy and examines the broad impacts of this policy across a strategic sample of five disciplines funded by the National Science Foundation. It considers the organization and structure of DMPs across fields, the institutions involved in data sharing, data preservation practices, the extent to which DMPs enable others to use secondary project data, and the kinds of data governance and preservation practices that ensure that data are sustained and accessible. Systematic investigation of the impact of DMPs and data sharing cultures across fields will assist funding agencies and research scientists working to produce reproducible and open science by identifying barriers to data archiving, sharing, and access. The principal investigators will use project findings to develop data governance guidelines for information professionals working with scientific data and to articulate best practices for scientific communities using DMPs for data management. This project aims to enhance understanding of the role data management plans (DMPs) play in shaping data lifecycles. It does so by examining DMPs across five fields funded by the National Science Foundation to understand data practices, archiving and access issues, the infrastructures that support data sharing and reuse, and the extent to which project data are later used by other researchers. In phase I, the investigators will gather a strategic sample of DMPs representing a wide range of data types and data retention practices from different scientific fields. Phase II consists of forensic data analysis of a subset of DMPs to discover what has become of project data. Phase III develops detailed case studies of research project data lifecycles and data afterlives with qualitative interviews and archival documentary analysis to help develop best practices for sustainable data preservation, access, and sharing. Phase IV will translate findings into data governance recommendations for stakeholders. The project thus contributes to research about contemporary studies of scientific data production and circulation while assessing the effect of DMPs as a national science policy initiative affecting data management practices in different scientific communities. The comparative research design and mixed methods enables theory building about cross-disciplinary data practices and data cultures across fields and advances knowledge within data studies, information management studies, and science and technology studies.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.

2011 年，美国国家科学基金会开始要求所有资助的项目提供数据管理计划 (DMP)，以确保项目数据、计算机代码和方法程序可供其他科学家将来使用。然而，这些数据管理要求在多大程度上导致了项目数据的更多更好的利用仍然是一个悬而未决的问题。因此，该项目将国家科学基金会的 DMP 任务作为国家科学政策进行调查，并研究该政策对国家科学基金会资助的五个学科的战略样本的广泛影响。它考虑了跨领域 DMP 的组织和结构、参与数据共享的机构、数据保存实践、DMP 使其他人能够使用二级项目数据的程度，以及确保数据持续和可访问的数据治理和保存实践的类型。对 DMP 和跨领域数据共享文化的影响进行系统调查将有助于资助机构和研究科学家通过识别数据归档、共享和访问的障碍来开展可重复和开放的科学工作。主要研究人员将利用项目结果为处理科学数据的信息专业人员制定数据治理指南，并为科学界阐明使用 DMP 进行数据管理的最佳实践。该项目旨在加深对数据管理计划 (DMP) 在塑造数据生命周期中所发挥的作用的理解。它通过检查国家科学基金会资助的五个领域的 DMP 来实现这一目标，以了解数据实践、存档和访问问题、支持数据共享和重用的基础设施，以及项目数据后来被其他研究人员使用的程度。在第一阶段，研究人员将收集 DMP 的战略样本，代表来自不同科学领域的广泛数据类型和数据保留实践。第二阶段包括对 DMP 子集进行取证数据分析，以发现项目数据的变化。第三阶段通过定性访谈和档案文献分析来开发研究项目数据生命周期和数据余生的详细案例研究，以帮助制定可持续数据保存、访问和共享的最佳实践。第四阶段将把研究结果转化为利益相关者的数据治理建议。因此，该项目有助于研究当代科学数据生产和流通的研究，同时评估 DMP 作为影响不同科学界数据管理实践的国家科学政策举措的效果。比较研究设计和混合方法使得能够建立关于跨学科数据实践和跨领域数据文化的理论，并推进数据研究、信息管理研究和科学技术研究方面的知识。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

The New Information Retrieval Problem: Data Availability

新的信息检索问题：数据可用性

• DOI: 10.1002/pra2.796
• 发表时间: 2023
• 期刊: Proceedings of the Association for Information Science and Technology
• 作者: Sharma, Sarika;Wilson, James;Tian, Yubing;Finn, Megan;Acker, Amelia
• 通讯作者: Acker, Amelia

Pathways to Data: From Plans to Datasets

数据之路：从计划到数据集

• DOI: 10.1109/jcdl52503.2021.00077
• 发表时间: 2021
• 期刊: 2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL
• 作者: Bennett, Anastasia;Sutherland, Will;Tian, Yubing;Finn, Megan;Acker, Amelia
• 通讯作者: Acker, Amelia