Developing Evidence-based Data Sharing and Archiving Policies

获得原始研究数据支持创新，跨学科和综合研究，并使复制和审查以前的工作。因此，越来越多的资助机构、期刊出版商和科学协会现在要求原始研究数据必须在收集或出版后立即共享和存档。然而，关于共享和存档研究数据的最佳方式，仍然有许多未回答的问题。例如：数据储存库如何才能最好地将其有限的资源分配给数据归档和处理的不同方面？让最广泛的受众使用数据的最有效方法是什么？什么样的数据共享政策最有效地实现利益相关者？透明度和创新目标？这个项目通过研究不同的“策展行动”（例如，标准化变量，改进文件），重新使用大学间政治和社会研究联合会（ICPSR）存档的数据。作为世界上最大的社会科学档案馆之一和数字数据管理实践的领导者，ICPSR非常适合作为这个项目的网站。ICPSR还能够为数据共享政策提供资助机构和政策制定者建议，这些政策阐述了评估数据共享和策展计划及其相关成本的适当性所需的指标。该项目通过（1）向资助者，存储库工作人员和研究人员推荐基于证据的数据共享政策以及（2）改进研究数据管理实践来实现更广泛的影响。为了确定各种策展活动对数据重用的影响，该项目首先定义了不同类型的“策展活动”和“影响”，然后解释了活动和影响之间的关系。为了识别影响重用的数据集和ICPSR服务的策展操作和其他功能，该项目检查了ICPSR的遗留策展日志和使用记录（例如下载和引用）。固化日志包含有关特定数据转换或保存步骤的数据。通过将策展日志与数据使用记录相关联，将识别与更高的重用率或访问率相关联的操作。该项目通过将使用日志与国际公共部门会计准则和社会责任方案的数据相关文献书目进行比较，审查了两种影响衡量标准-次级影响和多样性-的效用。ICPSR参考书目将80，000多份研究出版物与它们所依据的ICPSR数据联系起来。“二次影响”是衡量重用出版物被引用的次数的一个指标，它是通过收集书目中所有非原始PI出版物的引用数据来构建的。“多样性”衡量使用数据的学科的广度，同样可以从参考书目中构建。该项目采用多元回归分析和结构方程建模来确定策展活动、元数据、数据集本身、ICPSR服务以及重用和影响之间的关系。这种分析支持成本模型和度量的开发，这些模型和度量允许存储库管理员评估特定策展操作的投资回报。该项目将使用这些模型为基于证据的数据共享和存档政策提供信息。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。

Access to original research data supports innovative, interdisciplinary, and integrative research, and enables replication and review of prior work. Consequently, a growing number of funding agencies, journal publishers, and scientific societies now require that original research data must be shared and archived promptly after its collection or publication. However, there are still many unanswered questions about the best way to share and archive research data. For instance: how can data repositories best allocate their limited resources for different aspects of data archiving and processing? What is the most effective way of making data usable by the broadest audience? What data sharing policies most effectively achieve stakeholders? transparency and innovation goals? This project answers these questions by studying the impact of different "curatorial actions" (e.g., standardizing variables, improving documentation) on the reuse of data archived by the Inter-university Consortium for Political and Social Research (ICPSR). As one of the largest social science archives in the world and a leader in digital data curation practice, ICPSR is well-suited as a site for this project. ICPSR is also well-positioned to provide funding agencies and policy makers recommendations for data sharing policies that articulate the metrics needed in evaluating the appropriateness of data sharing and curation plans and their associated costs. This project achieves broader impacts by (1) recommending evidence-based data sharing policies to funders, repository staff,, and researchers and (2) improving research data curation practices. To determine the impact of various curatorial activities on data reuse, the project first defines the different kinds of "curatorial actions" and "impact," and then explains the relationships among actions and impact. To identify curatorial actions and other features of datasets and ICPSR services that influence reuse, the project examines ICPSR's legacy curation logs and use records (such as downloads and citations). Curation logs contain data about specific data transformations or preservation steps. By connecting curation logs to data usage records, the actions are associated with higher rates of reuse or access will be identified. The project examines the utility of two measures of impact--secondary impact and diversity--by comparing use logs to the ICPSR Bibliography of Data-Related Literature. The ICPSR Bibliography links over 80,000 research publications to the ICPSR data on which they are based. "Secondary impact" is a measure of how many times the reuse publications have been cited and is constructed by gathering citation data for all items in the bibliography that are not the original PI's publications. "Diversity" measures the breadth of disciplines that use the data and can similarly be constructed from the bibliography. The project employs multivariate regression analysis and structural equation modeling to determine the relationships among curatorial actions, metadata, the dataset itself, ICPSR services, and reuse and impact. This analysis enables the development of cost models and metrics that allow repository managers to evaluate the return on investment of specific curatorial actions. The project will use these models to inform evidence-based data sharing and archiving policies.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.