EAGER: SMART-DMSP: Streamlining Metadata, Automation, and Research Tracking for Data Management and Sharing Plans

该项目将研究多种策略，以加强和支持在学术环境中采用机器可操作的数据管理和共享计划（maDMSPs）。随着联邦对dmsp的授权不断增加，madmsp提供了一种有效的方法来产生最佳的dmsp，并作为确保遵守这些政策的关键机制。该项目侧重于结构化元数据、pid（持久标识符）、doi（数字对象标识符）和研究输出跟踪，以简化数据管理并有效实施madmsp。此外，该项目旨在通过自动化流程、提高质量和遵守标准，发现优化数据管理和跟踪研究成果的新机会。该研究项目包括两个主要工作包。第一个工作包旨在通过重组DMPTool和试验三个关键功能领域来推进madmsp: DMSP的自动更新，整合外部创建的DMSP，以及为利益相关者开发仪表板。第二个工作包探讨了机器学习（ML）在maDMSP工作流程中的潜力，重点是将叙述性文本文档自动转换为maDMSP，从结构化数据输入生成叙述性dmsp，并解决围绕敏感信息的隐私问题。该奖项反映了美国国家科学基金会的法定使命，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。

This project will investigate multiple strategies to enhance and support the adoption of machine-actionable Data Management and Sharing Plans (maDMSPs) in the academic environment. As federal mandates for DMSPs continue to increase, maDMSPs offer an efficient means to generate optimal DMSPs and serve as a crucial mechanism for ensuring compliance with these policies. The project focuses on structured metadata, PIDs (persistent identifiers), DOIs (digital object identifiers), and research output tracking to streamline data management and effectively implement maDMSPs. In addition, the project aims to uncover new opportunities for optimizing data management and tracking research outputs by automating processes, improving quality, and adhering to standards. The research project consists of two main work packages. The first work package aims to advance maDMSPs by retooling the DMPTool and experimenting with three key feature areas: automated updates to the DMSP, incorporating externally created DMSPs, and developing dashboards for stakeholders. The second work package explores the potential of machine learning (ML) in a maDMSP workflow, focusing on automating the conversion of narrative text documents into maDMSPs, generating narrative DMSPs from structured data inputs, and addressing privacy concerns surrounding sensitive information.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.