Collaborative: EAGER: Exploring and Advancing the State of the Art in Robust Science in Gravitational Wave Physics

合作：EAGER：探索和推进引力波物理学稳健科学的最新技术

• 批准号: 1841399
• 负责人: Michela Taufer
• 金额: $ 7.5万
• 依托单位: University of Tennessee Knoxville
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-06-01 至 2020-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1841399&HistoricalAwards=false
• 关键词: Collaborative; EAGER; Exploring; Advancing; State

Science is increasingly based on computation for science simulations, data management and analysis, instrument control and collaboration. For scientific results generated through computation to be considered robust and become widely accepted, the computational techniques should be automated, reproducible and trustworthy. By exploring the practices of gravitational-wave astronomy researchers working on the Laser Interferometer Gravitational-Wave Observatory (LIGO) project, this project seeks to create a set of case studies documenting broadly applicable methods for reproducible computational science. Specifically, the project will explore and articulate what reproducibility, automation, and trust mean with respect to computation-based research in gravitational-wave astronomy, identify, implement and validate a set of experimental practices, that will include computational techniques, and finally, evaluate how these experimental practices can be extended to other science domains. Robust computational science builds on rigorous methods and is composed of three key elements: (1) reproducibility, which enables the verification and leveraging of scientists' findings; (2) automation, which speeds up the exploration of alternative solutions and the processing of large amounts of data while reducing the introduction of errors; and (3) trust, providing security and reliability for software and data, while supplying the necessary attributes for confidence in the scientist's own results and results from others. This project explores robust science in the LIGO project through the following activities within the context of gravitational-wave astronomy: (1) articulating the roles of reproducibility, automation, and trust in gravitational-wave astronomy; (2) identifying, implementing and validating a set of experimental practices, including computational techniques; and (3) advancing towards the project's vision of general computational methods for robust science by evaluating how the experimental practices can be extended to other science domains. The project will develop and use a survey to collect information about LIGO workflows that are composed of a series of experimental, computational, and data manipulation steps. The analysis of the survey will result in a document that describes what reproducibility means in the LIGO context and help identify potential improvements in LIGO's practices. The project will generalize these findings by documenting a mapping of LIGOÕs original and enhanced approach to other science workflows including those of the molecular dynamics and bioinformatics communities. The final project document will target a broad audience that includes researchers and students at various levels of education, with the goal of introducing them to the concept of robust computational research, and the underlying concepts of reproducibility, automation and trust, teaching them to access code, data, and workflow information to regenerate findings, learn about the scientific methods, and to engage in STEM research.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.

科学越来越依赖于科学模拟、数据管理和分析、仪器控制和协作的计算，为了使通过计算产生的科学结果被认为是稳健的并被广泛接受，计算技术应该是自动化的、可重复的和值得信赖的。该项目由从事激光干涉仪引力波天文台 (LIGO) 项目的引力波天文学研究人员组成，旨在创建一组案例研究，记录可重复计算科学的广泛适用的方法。该项目将探索和阐明可重复性、自动化和信任对于引力波天文学中基于计算的研究意味着什么，识别、实施和验证一组实验实践，其中包括计算技术，最后评估这些实验如何稳健的计算科学建立在严格的方法之上，由三个关键要素组成：（1）可重复性，可以验证和利用科学家的发现；（2）自动化，可以加快探索速度；的替代解决方案和处理大量数据，同时减少错误的引入；（3）信任，为软件和数据提供安全性和可靠性，同时提供必要的属性，以保证科学家自己的结果和他人的结果。项目通过引力波天文学背景下的以下活动探索​​ LIGO 项目中的稳健科学：(1) 阐明引力波天文学中的可重复性、自动化和信任的作用；(2) 识别、实施和信任；验证一系列实验实践，包括计算技术；(3) 通过评估如何将实验实践扩展到其他科学领域，推进该项目的通用计算方法愿景。收集有关 LIGO 工作流程的信息，这些工作流程由一系列实验、计算和数据操作步骤组成。调查分析将生成一份文件，描述可重复性在 LIGO 背景下的含义，并帮助确定 LIGO 实践项目的潜在改进。将概括这些发现通过记录 LIGO 的原始和增强方法与其他科学工作流程（包括分子动力学和生物信息学界的工作流程）的映射，最终项目文件将面向包括不同教育水平的研究人员和学生在内的广泛受众。健壮的计算研究的概念，以及可重复性、自动化和信任的基本概念，教他们访问代码、数据和工作流程信息以重新生成研究结果、了解科学方法并参与 STEM 研究。该奖项反映了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，NSF 的法定使命被认为值得支持。

项目成果

Initial Thoughts on Cybersecurity And Reproducibility

关于网络安全和可重复性的初步想法

• DOI: 10.1145/3322790.3330593
• 发表时间: 2019-01
• 期刊: 2nd International Workshop on Practical Reproducible Evaluation of Computer Systems (P-RECS'19
• 作者: Deelman, Ewa;Stodden, Victoria;Taufer, Michela;Welch, Von
• 通讯作者: Welch, Von

A Case Study in Scientific Reproducibility from the Event Horizon Telescope (EHT).

事件视界望远镜 (EHT) 的科学再现性案例研究。

• 发表时间: 2021-09
• 期刊: Proceedings of the 20th IEEE International Conference on eScience
• 作者: Ross Ketron; Jacob Leonard
• 通讯作者: Jacob Leonard

A Case Study in Scientific Reproducibility from the Event Horizon Telescope (EHT)

事件视界望远镜 (EHT) 的科学再现性案例研究

• DOI: 10.1109/escience51609.2021.00045
• 发表时间: 2021-09
• 期刊: 2021 IEEE 17th International Conference on eScience (eScience
• 作者: Ketron, R.;Leonard, J.;Roachell, B.;Patel, R.;White, R.;Caino;Tan, N.;Miles, P.;Vahi, K.;Deelman, E.;et al
• 通讯作者: et al

Applicability Study of the PRIMAD Model to LIGO Gravitational Wave Search Workflows

PRIMAD 模型对 LIGO 引力波搜索工作流程的适用性研究

• DOI: 10.1145/3322790.3330591
• 发表时间: 2019-01
• 期刊: 2nd International Workshop on Practical Reproducible Evaluation of Computer Systems (P-RECS'19
• 作者: Chapp, Dylan;Rorabaugh, Danny;Brown, Duncan A.;Deelman, Ewa;Vahi, Karan;Welch, Von;Taufer, Michela
• 通讯作者: Taufer, Michela