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EAGER: Cyberinfrastructure Reproducibility Project: Computational Science and Engineering

EAGER：网络基础设施再现性项目：计算科学与工程

基本信息

批准号：
1747669
负责人：
Lorena Barba
金额：
$ 29.98万
依托单位：
George Washington University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-09-01 至 2021-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1747669&HistoricalAwards=false
关键词：
EAGER Cyberinfrastructure Reproducibility Project Computational

项目摘要

The progress of science today relies heavily on the use of computers, from lab workstations to national supercomputers. This project confronts the issue of ensuring that scientific knowledge stemming from computational research complies to high standards of reproducibility and rigor. The NSF CISE Directorate "Dear Colleague Letter: Encouraging Reproducibility in Computing and Communications Research" (NSF 17-022, 2016) encourages researchers to embrace completeness and transparency in developing rigorous protocols. Reproducibility concerns often focus on transparency via open data, code, and other research objects. But providing the data and code to run all analyses again is, however, a minimum standard. In the context of high-performance computing where research uses multi-million-dollar facilities the understanding of where lie the sources of non-reproducibility is still lacking. This project uses methodical replication of previous studies in computational fluid dynamics as the model for reaching that understanding and for developing the guiding principles of study design that can guarantee, as much as possible, reproducible findings. The results of this project will serve NSF's mission to promote the progress of science; to advance the national health, prosperity and welfare; to secure the national defense by bringing new and necessary understanding about how to achieve rigorous, reproducible computational research. This project conducts methodical replication of published studies in computational fluid dynamics, as a model for the broad field of computational science and engineering. Its aims are to 1) identify and characterize sources of non-reproducibility, and 2) develop guidelines on Design for Reproducibility, i.e., study design guaranteeing reproducible findings. The project addresses the role of scientific software libraries (like linear algebra solvers), the influence of hardware architectures , the role of new technologies for reproducible research (e.g., containers, cloud services). The project also provides guidelines for making assessments about the success of replication studies in the context of high-performance computing, including when it is reasonable or not to expect bit-by-bit numerical reproducibility. The research tackles three phases of computational research: Research methods; Research communication; Research assessment. The project also develops openly licensed training materials on reproducible computational research, including a graduate seminar course and a Responsible Conduct of Research (RCR) module.

今天的科学进步在很大程度上依赖于计算机的使用，从实验室工作站到国家超级计算机。该项目面临的问题是，确保来自计算研究的科学知识符合高标准的再现性和严谨性。NSF CISE理事会“亲爱的同事信：鼓励在计算和通信研究中复制”（NSF 17-022，2016）鼓励研究人员在制定严格的协议时采用完整性和透明度。可复制性问题通常集中在通过开放数据，代码和其他研究对象的透明度上。但是，提供数据和代码来再次运行所有分析是最低标准。在高性能计算的背景下，研究使用数百万美元的设施，对不可再现性来源的理解仍然缺乏。该项目使用计算流体动力学以前研究的系统复制作为模型，以达到这种理解，并制定研究设计的指导原则，以保证尽可能多的可重现的结果。该项目的结果将服务于NSF的使命，以促进科学的进步;促进国家的健康，繁荣和福利;通过对如何实现严格的，可重复的计算研究带来新的和必要的理解来确保国防。该项目对已发表的计算流体动力学研究进行了系统的复制，作为计算科学和工程广泛领域的模型。其目的是：1）识别和表征不可再现性的来源，2）制定可再现性设计指南，即，研究设计保证了结果的可重复性。该项目解决了科学软件库（如线性代数求解器）的作用，硬件架构的影响，可重复研究的新技术的作用（例如，容器、云服务）。该项目还提供了在高性能计算的背景下评估复制研究成功与否的指导方针，包括何时合理或不合理地期望逐位数字再现性。研究涉及计算研究的三个阶段：研究方法;研究交流;研究评估。该项目还开发了关于可重复计算研究的公开许可培训材料，包括研究生研讨会课程和负责任的研究行为（RCR）模块。