Values into Infrastructure: an Ethnographic Archaeology of Distributed Computational Scientific Work

该项目对数字科学基础设施的发展进行了人种学研究，跟随两个科学团队-环境水文学和化学工程，因为他们建立和实施了旨在为专家和更广泛的受众提供分层访问的计算模型。这些基础设施模型将允许用户使用远程超级计算机访问用于数据挖掘、分析、可视化、教程和解决问题的高级工具，可以说构成了21世纪世纪的科学解决问题环境。这个研究项目的目标是开发一个经验和理论上知情的理解如何道德，认识论和社会和政治价值观出现在各种行为者和机构的互动，并写入技术系统。 研究通过“基础设施倒置”进行，即通过开放观察和分析计算和其他构成知识发展基础的要素，但通常隐藏在视野之外。 它涉及观察环境水文学和化学工程小组各自实验室的科学做法，以及与他们合作建立基础设施的赋能技术小组的科学做法。 这些观察使研究人员能够概述对数字科学基础设施贡献者正在移动的学科网络的分析，对他们的工作至关重要的技术和象征性承诺，以及他们以特定方式开发基础设施的理由。现场访问将包括对实验室成员的正式和非正式采访，了解他们的具体做法及其对数字科学基础设施的贡献。 研究人员将记录，转录，编码和分析所有的采访，将分析与写入基础设施的技术决策分析交织在一起。 研究结果将在相关的科学建模会议、专业协会会议、期刊和书籍中报告。

This project undertakes an ethnographic examination of the development of digital scientific infrastructure, following two scientific teams - environmental hydrology, and chemical engineering, as they build and implement computational models intended to provide layered access to specialists and broader audiences. These infrastructural models will allow users to access advanced tools for data mining, analysis, visualization, tutorials, and problem solving, using remote supercomputers, arguably constituting the scientific problem-solving environment of the 21st century. The goal of this research project is to develop an empirically and theoretically informed understanding of how ethical, epistemological and social and political values emerge in the interactions of various actors and agencies and get written into technical systems. The research proceeds by "infrastructural inversion," that is, by opening to observation and analysis computational and other elements that underlie knowledge development, but are usually hidden from view. It involves observing scientific practices at the respective laboratories of the environmental hydrology and chemical engineering teams, as well as those of the enabling technology teams working with them to create the infrastructure. The observations allow the researchers to outline an analysis of the disciplinary networks through which the contributors to the digital science infrastructure are moving, the technical and symbolic commitments that have become crucial to their work, and the justifications they provide for developing infrastructure in the particular ways that they do. Site visits will include formal and informal interviews with laboratory members about their specific practices and their contributions to the digital scientific infrastructures. The researchers will record, transcribe, code and analyze all the interviews, interlacing the analyses with analysis of the technical decisions being written into the infrastructure. Results will be reported at relevant scientific modeling conferences, at professional society meetings, in journals, and in a book.