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.

在2011年，国家科学开始要求所有资助的数据管理计划（DMP）确保其他科学家可以使用项目代码，以供将来使用。更好地使用项目数据的一个开放性问题。 ，DMP在多大程度上使其他人使用次要项目数据，以及确保数据持续和访问数据的数据治理和保存的类型调查人员将使用项目治理来进行数据治理，以使科学界的科学界使用DMP，用于管理DMP。数据实践，支持数据共享和重复使用的Inf RASTRUTION，以及其他研究人员在第二阶段使用的项目数据，将收集DMPS的战略性样本，以压制广泛的数据类型和数据保留范围来自不同的领域。可持续的数据保存和分享的利益相关者。关于跨跨学科数据实践和数据文化的理论化学范围以及数据研究中的知识以及科学技术研究的知识。该奖项反映了Sawsfsf的法定使命，尽管评估了基金会的智力优点和更广泛的影响，但仍引起了人们的支持。 。

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