EAGER: Collaborative Research: Supporting Public Access to Supplemental Scholarly Products Generated from Grant Funded Research

EAGER：合作研究：支持公众获取资助研究产生的补充学术产品

• 批准号: 1649545
• 负责人: Helen Berman
• 金额: $ 6万
• 依托单位: Rutgers University New Brunswick
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1649545&HistoricalAwards=false
• 关键词: EAGER; Collaborative; Research; Supporting; Public

This EAGER project addresses the urgent need to better understand the research community's Data Management Plan (DMP) requirements and, based on this understanding, provides an open software tool that helps investigators generate structured and machine-readable Data Management Plans that fulfill both the researcher's need to easily deliver a standardized set of information to the funder, and the funder's need to analyze the information contained in DMPs. This allows funders to identify trends in data and software submission, repository use patterns, and carry out other analyses that can assist in understanding community use patterns and needs. The Principal Investigators (PIs) will leverage an existing DMP Tool built for the geosciences community by initially assessing the DMPs not only of the geosciences, but also the biological and social, behavioral, and economic sciences and upgrading the DMP Tool to serve those communities as well. Ultimately, the team will work to determine if this upgraded DMP Tool is extendable and scalable to all science, engineering, and educational research funded by the National Science Foundation. If successful, this will ultimately enhance the reproducibility and reuse of scientific research and help improve public access to supplementary scholarly products from federally funded research.The National Science Foundation has required Data Management Plans (DMPs) for all grant proposals submitted for review since 2011. The DMPs submitted thus far are mostly free text and do not follow any specified format or structure and because of this limitation, current DMPs are not easy to compare or analyze. Consistent and comprehensive structured and machine-readable DMPs may substantially advance understanding of the data management landscape and address gaps that will improve data access which will lead to enhanced re-use and more reproducible science. The PIs propose to modify and upgrade the DMP Tool that has been developed and operated by IEDA (Interdisciplinary Earth Data Alliance) to serve the broadest research communities possible. This DMP Tool gathers relevant data management planning information from investigators in a structured manner into a relational database that can be mined and analyzed. As part of this project, they will analyze the information from the more than 1,350 DMPs that have already been generated with the IEDA DMP Tool to understand gaps, successes, and patterns of use. They will initially focus on the DMP requirements of science communities funded by the National Science Foundation's GEO, BIO, and SBE directorates, and use the results of this research to guide the development and prototyping of the extended version of the IEDA DMP Tool. They will subsequently focus on other directorates.

这个迫切的项目满足了更好地了解研究社区的数据管理计划(DMP)要求的迫切需要，并基于这种理解，提供了一个开放的软件工具，帮助调查人员生成结构化和机器可读的数据管理计划，以满足研究人员轻松向资助者提供标准化信息集的需求，以及资助者分析DMP中包含的信息的需求。这使资助者能够确定数据和软件提交、存储库使用模式的趋势，并执行其他分析，以帮助理解社区使用模式和需求。首席调查员将利用为地球科学界建立的现有DMP工具，不仅初步评估地球科学的DMP，而且还评估生物、社会、行为和经济科学的DMP，并升级DMP工具，以便也为这些社区服务。最终，该团队将致力于确定这个升级的DMP工具是否可扩展和扩展到所有由国家科学基金会资助的科学、工程和教育研究。如果成功，这将最终提高科学研究的再现性和重用性，并有助于改善公众对联邦资助研究的补充学术产品的获取。自2011年以来，国家科学基金会要求所有提交审查的拨款提案都必须有数据管理计划(DMP)。到目前为止提交的DMP大多是自由文本，不遵循任何指定的格式或结构，因此，当前的DMP不容易进行比较或分析。一致的、全面的、结构化的和机器可读的数据管理计划可大大促进对数据管理格局的了解，并填补将改善数据获取的差距，从而提高可重复使用程度和更具重现性的科学。PIS提议修改和升级由IEDA(跨学科地球数据联盟)开发和操作的DMP工具，以尽可能为最广泛的研究界服务。该DMP工具以结构化方式收集来自调查人员的相关数据管理规划信息，并将其放入可挖掘和分析的关系数据库中。作为该项目的一部分，他们将分析IEDA DMP工具已经生成的1350多个DMP的信息，以了解差距、成功和使用模式。他们将首先关注由国家科学基金会的GEO、BIO和SBE理事会资助的科学界的DMP要求，并使用这项研究的结果来指导IEDA DMP工具扩展版本的开发和原型制作。他们随后将把重点放在其他董事身上。