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

COVID-19疫情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，选举民主鼓励透明度;“数据促进社会公益”的言论;以及庞大的IT劳动力。该项目旨在揭示项目领导者和贡献者如何面对和管理大流行造成的中断，困难和冲突。该研究项目跨越不同的地理和机构环境，将突出疫情如何以不同的方式影响不同的社区。该研究项目将为政策制定者、技术人员和其他领导者提供有关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，我们可以为下一次紧急情况做好更好的准备。这个RAPID研究项目研究了新型关键数据基础设施的创建，维护和实时转换。它揭示了形成和定义COVID数据跟踪系统的辩论、冲突、排序和重要决策。在大流行扰乱了地球仪正在进行的研究之际，这些数据跟踪器可以提供有关如何在重大压力条件下创建和维护弹性和可持续研究支持基础设施的见解。该RAPID项目对美国和印度的公共COVID数据项目进行了跨国比较分析，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破坏的关键因素。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：填充这些系统的信息、实践、工具和合作者不断发展。通常，使用当前的网络存档和累积公共数据保存方法，不容易保存塑造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捉这些短暂的数据-允许该项目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。该项目是知情的，并将有助于技术发展，基础设施研究和危机信息学民族志的学术文献。研究结果将支持具体的建议，这些和未来的数据基础设施可以（1）可持续发展;（2）对不同的公众负责;（3）改善，以帮助拯救生命。这个奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

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.