Collaborative Research: EAGER: Characterizing Research Software from NSF Awards

协作研究：EAGER：获得 NSF 奖项的研究软件特征

• 批准号: 2211278
• 负责人: Karthik Ram
• 金额: $ 1.8万
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-15 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2211278&HistoricalAwards=false
• 关键词: Collaborative; Research; EAGER; Characterizing; Software

Software underlies many of the national economic advances of the last 60 years, from better weather models that enable more productivity to better-designed products that lower material usage and costs. Most of these advances originated in research software, initially via algorithms and licensing, and more recently via open-source code. Despite these numerous successes, much of the software produced in science and engineering research is not sustainable - it is not shared, maintained, or developed in ways that enable meaningful reuse. This lack of sustainable development hampers both research and economic progress. Using a combination of self-reported and administrative data this project is systematically investigating the development and maintenance of software produced in research projects funded by the National Science Foundation. The data collected for this study is being used to develop a set of models for research software sustainability planning. These models support scientists and engineers planning for software sustainability; help research funding agencies be better prepared to evaluate research software in grant applications, and enable institutions that support software development and maintenance to be equipped to support impactful research that in turn, produces impactful research software.The goals of this project are: 1) to understand what factors influence software sustainability by gathering data from grant-funded research projects; 2) to describe current models of sustainability planning and suggest potential new models that could increase the likelihood of achieving long-term software sustainability; and 3) to develop emergent methods to evaluate research software sustainability. Data collection to meet these goals includes a survey and interviews with researchers that have produced software as part of an NSF-funded award. This project also uses emerging methods in analyzing research software code repositories in order to understand what activities in software development correlate with sustainability. This research has three intended impacts: 1) to provide a proof of concept for large-scale analysis of research software sustainability using a mixed-methods approach; 2) to modify existing standardized metrics of software health so that they can be used to evaluate the sustainability of research software; and 3) to create an initial set of sustainability models that researchers can use to better plan research software projects, funders can use to make better award decisions, and institutions can use to better allocate internal resources.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.

软件是过去 60 年来许多国民经济进步的基础，从提高生产力的更好的天气模型到降低材料使用和成本的更好设计的产品。这些进步大部分源自研究软件，最初是通过算法和许可，最近是通过开源代码。尽管取得了这些巨大的成功，但科学和工程研究中产生的许多软件都是不可持续的——它们没有以实现有意义的重用的方式共享、维护或开发。缺乏可持续发展阻碍了研究和经济进步。该项目结合自我报告和管理数据，系统地调查由国家科学基金会资助的研究项目中产生的软件的开发和维护。本研究收集的数据用于开发一套研究软件可持续性规划模型。这些模型支持科学家和工程师规划软件可持续性；帮助研究资助机构更好地准备评估赠款申请中的研究软件，并使支持软件开发和维护的机构能够支持有影响力的研究，进而产生有影响力的研究软件。该项目的目标是： 1) 通过收集赠款资助的研究项目的数据，了解哪些因素影响软件的可持续性； 2）描述当前的可持续性规划模型，并提出可能增加实现长期软件可持续性可能性的新模型； 3) 开发评估研究软件可持续性的紧急方法。为实现这些目标而收集的数据包括对作为 NSF 资助的奖项的一部分开发软件的研究人员进行调查和访谈。该项目还使用新兴方法来分析研究软件代码存储库，以了解软件开发中的哪些活动与可持续性相关。这项研究具有三个预期影响：1）为使用混合方法对研究软件可持续性进行大规模分析提供概念证明； 2）修改现有的软件健康标准化指标，以便它们可用于评估研究软件的可持续性； 3) 创建一套初始的可持续性模型，研究人员可以用它来更好地规划研究软件项目，资助者可以用它来做出更好的奖励决策，机构可以用它来更好地分配内部资源。该奖项反映了 NSF 的法定使命，并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，被认为值得支持。