RAPID International Type I: Collaborative Research: COVID Data Infrastructure Builders: Creating Resilient and Sustainable Research Collaborations

RAPID 国际 I 类：协作研究：新冠病毒数据基础设施建设者：创建有弹性和可持续的研究合作

• 批准号: 2109653
• 负责人: Amelia Acker
• 金额: $ 3.89万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-02-01 至 2024-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2109653&HistoricalAwards=false
• 关键词: RAPID; International; Type; Collaborative; Research

The COVID-19 pandemic has sparked thousands of new large-scale data projects globally. These COVID data infrastructures are essential: they enable the public, policymakers, public health officials, and others to see and comprehend particular aspects of the global health crisis. This research compares COVID data infrastructures in the U.S. and India, countries that share extremely high COVID infection rates as well as electoral democracy that encourages transparency; 'Data for Social Good' rhetoric; and large IT workforces. The project seeks to reveal how project leaders and contributors confront and manage the disruptions, hardships, and conflicts created by the pandemic. Working across different geographies and institutional settings, the research project will highlight how the pandemic impacts different communities in different ways. The research project will provide policymakers, technologists, and other leaders with insights and recommendations on how to improve the creation and maintenance of emergency data infrastructures. By understanding the dynamics of current COVID data infrastructures, we can be better prepared for the next emergency.This RAPID research project investigates the creation, maintenance, and real-time transformation of novel critical data infrastructures. It uncovers the debates, conflicts, orderings, and important decisions that shape and define COVID data-tracker systems. At a time when the pandemic is disrupting ongoing research across the globe, these data-trackers can provide insights into how to create and maintain resilient and sustainable research-enabling infrastructure under conditions of significant stress. This RAPID project uses cross-national comparative analysis of public COVID data projects in the U.S. and India in order to identify the key factors that enable data infrastructures to endure the social and material disruptions associated with the pandemic. The project’s cross-national and comparative research design ensures that research findings are generalizable. COVID data infrastructures are dynamic: the information, practices, tools, and collaborators that populate these systems constantly evolve. Often, the important adaptations that shape critical data infrastructures are not easily preserved using current web archiving and cumulative public data preservation methods. Additionally, the project’s research design will capture this otherwise ephemeral data--allowing the project to analyze and interpret how these infrastructures are created and maintained under adverse conditions. The project is informed by and will contribute to the scholarly literature on ethnographies of technology development, infrastructure studies, and crisis informatics. Research findings will support concrete recommendations for how these and future data infrastructure can be made (1) sustainable; (2) accountable to different publics; and (3) improved in order to help save lives.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.

2019冠状病毒病大流行在全球引发了数千个新的大型数据项目。这些COVID数据基础设施至关重要：它们使公众、政策制定者、公共卫生官员和其他人能够看到和理解全球卫生危机的特定方面。这项研究比较了美国和印度的COVID数据基础设施，这两个国家的COVID感染率极高，同时也鼓励透明度的选举民主；“数据促进社会公益”的修辞；以及庞大的IT员工队伍。该项目旨在揭示项目负责人和贡献者如何面对和管理疫情造成的破坏、困难和冲突。该研究项目在不同地区和机构环境中开展工作，将重点强调大流行如何以不同方式影响不同社区。该研究项目将为政策制定者、技术专家和其他领导人提供关于如何改进应急数据基础设施的创建和维护的见解和建议。通过了解当前COVID数据基础设施的动态，我们可以更好地为下一次紧急情况做好准备。这个RAPID研究项目调查了新的关键数据基础设施的创建、维护和实时转换。它揭示了塑造和定义COVID数据跟踪系统的辩论、冲突、命令和重要决策。在大流行破坏全球正在进行的研究之际，这些数据跟踪器可以为如何在巨大压力条件下创建和维护有弹性和可持续的研究基础设施提供见解。该RAPID项目对美国和印度的公共COVID数据项目进行跨国比较分析，以确定使数据基础设施能够承受与大流行相关的社会和物质中断的关键因素。该项目的跨国和比较研究设计确保了研究结果的普遍性。COVID数据基础设施是动态的：构成这些系统的信息、实践、工具和合作者都在不断发展。通常，使用当前的web归档和累积公共数据保存方法，不容易保存形成关键数据基础设施的重要调整。此外，该项目的研究设计将捕获这些短暂的数据，使项目能够分析和解释这些基础设施是如何在不利条件下创建和维护的。该项目由技术发展、基础设施研究和危机信息学方面的民族志学术文献提供信息，并将为这些学术文献做出贡献。研究结果将支持如何使这些和未来的数据基础设施具有可持续性的具体建议；(2)对不同的公众负责；(3)为了帮助拯救生命而改进。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。