EAGER: Reproducibility and Cyberinfrastructure for Computational and Data-Enabled Science

该项目旨在提高对科学界如何适应日益增加的计算和大规模数据资源使用的理解。一个挑战是确保计算结果--例如来自模拟的结果--是“可重现的”，即当一个人重复使用相同的输入数据、方法、软件和分析条件时，获得相同的结果。2019年，美国国家科学、工程和医学研究院(NASEM)发布了一份关于《科学中的可再现性和复制》的报告，并提出了一系列建议。该项目将评估这些建议对以计算和数据为基础的研究的科学发现过程的影响。以下研究问题将指导这项研究：(1)NASEM建议暴露了哪些可重复性问题，它们对计算基础设施意味着什么约束和要求？(2)这些问题和约束对整个计算基础设施生态系统有什么影响？为了探索和说明这些问题的答案，我们将使用各种科学用例来涵盖研究人员与计算基础设施交互的不同方式。还将把形式主义应用于用例，以阐明计算基础设施在提高透明度和再现性方面的作用，并阐明计算基础设施如何符合NASEM报告的建议。总体目标是在透明度、重复性和支持科学发现的计算基础设施的交叉点上阐明未来研究的途径。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This project seeks to improve understanding of how the scientific community can adapt to the increasing use of computing and large-scale data resources. One challenge is ensuring that computational results - such as those from simulations - are "reproducible," that is, the same results are obtained when one re-uses the same input data, methods, software and analysis conditions. In 2019, the National Academies of Science, Engineering, and Medicine (NASEM) issued a report on "Reproducibility and Replication in Science" with a series of recommendations. The project will assess the implications of these recommendations on the scientific discovery process for computationally- and data-enabled research.The following research questions will guide this study: (1) what reproducibility issues are surfaced by the NASEM recommendations and what constraints and requirements do they imply for computational infrastructure?; and (2) what are the implications of these issues and constraints on the computational infrastructure ecosystem as a whole? To explore and illustrate answers to these questions, we will employ diverse scientific use cases chosen to cover different ways researchers interact with computational infrastructure. Formalisms will also be applied to the use cases to articulate the role of computational infrastructure in enabling transparency and reproducibility, and to elucidate how computational infrastructure can conform to the NASEM report recommendations. The overall aim is to articulate avenues for future research at the intersection of transparency, reproducibility and computational infrastructure that supports scientific discovery.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.