Collaborative Research: AOC: Monitoring, Modeling and Memory: Dynamics of Data and Knowledge in Scientific Cyberinfrastructures

合作研究：AOC：监控、建模和记忆：科学网络基础设施中数据和知识的动态

• 批准号: 0827316
• 负责人: Paul Edwards
• 金额: $ 69.23万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-10-01 至 2014-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0827316&HistoricalAwards=false
• 关键词: Collaborative; Research; AOC; Monitoring; Modeling

Scientists and supporters of science have long worked to improve the sharing, reuse, storage, and retrieval of scientific data. Today, efforts focus on advanced "cyberinfrastructure": using networked computers, databases, and organizations to bridge divides among diverse scientific disciplines. Cyberinfrastructure divides into three main activities. First, large numbers of automatic sensors monitor subjects of interest, such as ecosystems and Earth's climate, producing massive volumes of digitized data. Second, in many fields computer models have replaced laboratory experiments as the principal means of data collection, prediction, and decision-making. Third, increasingly vast data resources (scientific memory) are now available, but are often distributed across thousands of research sites and institutions, in numerous incompatible formats. For cyberinfrastructure-enabled science to deliver on its transformative potential, cyberinfrastructure designers need better ways of understanding how scientists actually create and share data in practice, and how they use it to create new knowledge. To investigate data practices empirically, this project examines four large cyberinfrastructure efforts: the Long Term Ecological Research Network, the Center for Embedded Network Sensing, the WATer and Environmental Research Systems Network, and the Earth System Modeling Framework. In each case, the investigators will study how cyberinfrastructure is used in monitoring, modeling, and memory. These projects spread across many disciplines addressing three important domains, all related to climate change concerns: ecology and environment; hydrology and water management; and earth system science. In conducting the project, the investigators will develop innovative methods of distributed ethnography, collaborative history, and multimodal network analysis. In addition to published findings, the project will produce a 'best practices' handbook meant to guide data practices and coordination in cyberinfrastructure. The project will partner with organizations working to enhance the role of women in computing; to build database systems for American Indian communities; and to engage other groups often ignored in information infrastructure development. The project will thus lay groundwork for an inclusive, theoretically rich, and practically engaged social science of cyberinfrastructure.

科学家和科学的支持者长期以来一直致力于改善科学数据的共享、重用、存储和检索。 今天，人们的努力集中在先进的“网络基础设施”上：使用联网的计算机、数据库和组织来弥合不同科学学科之间的分歧。 网络基础设施分为三个主要活动。首先，大量的自动传感器监测感兴趣的主题，如生态系统和地球气候，产生大量的数字化数据。 其次，在许多领域，计算机模型已经取代实验室实验，成为数据收集、预测和决策的主要手段。 第三，现在有越来越庞大的数据资源（科学记忆），但往往分布在数千个研究地点和机构，并以许多不兼容的格式。 为了使网络基础设施支持的科学发挥其变革潜力，网络基础设施设计者需要更好的方法来了解科学家在实践中如何实际创建和共享数据，以及他们如何使用数据来创造新知识。 为了实证研究数据实践，该项目研究了四个大型网络基础设施的工作：长期生态研究网络，嵌入式网络传感中心，水和环境研究系统网络，以及地球系统建模框架。 在每种情况下，研究人员将研究网络基础设施如何用于监控，建模和记忆。 这些项目涉及许多学科，涉及三个重要领域，都与气候变化问题有关：生态和环境;水文和水管理;地球系统科学。 在进行该项目时，研究人员将开发分布式民族志，协作历史和多模式网络分析的创新方法。 除了公布调查结果外，该项目还将编写一本“最佳做法”手册，旨在指导网络基础设施的数据做法和协调。 该项目将与致力于加强妇女在计算方面的作用的组织合作;为美洲印第安人社区建立数据库系统;并使在信息基础设施发展中经常被忽视的其他群体参与进来。 因此，该项目将为网络基础设施的包容性，理论丰富和实际参与的社会科学奠定基础。