EAGER: Developing a framework to identify and mitigate perceptual and technical barriers in code sharing to facilitate reproducible and transparent research
EAGER: Developing a framework to identify and mitigate perceptual and technical barriers in code sharing to facilitate reproducible and transparent research
批准号:
2135954
负责人:
Serghei Mangul
金额:
$19.99万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-09-01 至 2023-08-31
中文摘要
该项目将对使研究代码公开访问的障碍和策略进行探索性研究。虽然在为开放科学和可重复性目的提供研究数据集方面取得了重大进展,但在研究项目中开发的代码和其他形式的软件很少能够持续提供。在科学研究中,不仅必须发布研究设计、方法、结果和解释的详细描述,而且迫切需要使所有的研究产品(包括代码和软件)公开可用、可共享、有良好的文档和组织,以促进可复制和透明的研究。用于分析的分析代码是一种重要的研究产品,是确保研究可重复性的基本要素。与科学期刊和研究组织广泛实施的数据共享相比,代码共享的指导有限,除了数据之外,代码共享是可重复和严格研究的重要组成部分。该项目将带来:A)描述性信息,将通过电话会议的一对一访谈收集,以及随机选择由NSF和/或NIH支持的5,000名主要研究人员进行调查。B)通过与知情专家(特别是对代码共享和可重复研究有浓厚兴趣的科学期刊编辑)进行一系列结构化电话会议,制定代码共享建议。C)成立研究代码联盟(RCA),制定框架,以减轻代码共享中的感知和技术障碍,促进可重复和透明的研究。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
This project will conduct exploratory research into the barriers and strategies for making research code publicly accessible. While there has been significant progress in making research datasets accessible for purposes of open science and reproducibility, code and other forms of software developed in research projects are less frequently made available persistently. In scientific research, it is not only imperative to publish a detailed description of the study design, methodology, results, and interpretation, but there is a pressing need to make all the research products (including code and software) publicly available, shareable, well documented, and organized to facilitate reproducible and transparent research.An important research product that is an essential element ensuring reproducible research is the analytic code used for the analysis. In contrast to sharing data, which is widely enforced by scientific journals and research organizations, there is limited guidance on code sharing which in addition to data represents an essential component of reproducible and rigorous research. The project will result in: A) Descriptive information which will be collected through one-to-one interviews through teleconferencing, as well as by distributing surveys across 5,000 randomly selected principal investigators who were supported by NSF and/or NIH, B) Recommendations for code sharing to be developed through a series of structured teleconferences with informed experts, notably editors of scientific journals with a strong interest in code sharing and reproducible research, and C) Formation of a Research Code Alliance (RCA) to develop a framework to mitigate perceptual and technical barriers in code sharing to facilitate reproducible and transparent 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.
期刊论文(4)
专著(0)
科研奖励(0)
会议论文
DOI:
10.3389/fsysb.2022.918792
发表时间:
2022-04
期刊:
bioRxiv
影响因子:
--
作者:
[Yu-Ning Huang;Naresh Amrat Patel;Jay Himanshu Mehta;Srishti Ginjala;P. Brodin;C. Gray;Yesha M Patel;L. Cowell;A. Burkhardt;S. Mangul]
通讯作者:
Yu-Ning Huang;Naresh Amrat Patel;Jay Himanshu Mehta;Srishti Ginjala;P. Brodin;C. Gray;Yesha M Patel;L. Cowell;A. Burkhardt;S. Mangul
RCN-UBE: Sustainable, nationwide network to promote reproducible big-data analysis in biology programs within community colleges and minority-serving institutions
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批准号:2316223
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项目类别:Standard Grant
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资助金额:$49.88万
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财政年份:2023
-
负责人:Serghei Mangul
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依托单位:
CAREER: Developing efficient and scalable bioinformatics methods and databases to analyze the adaptive immune repertoires of vertebrate species
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批准号:2041984
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项目类别:Continuing Grant
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资助金额:$74.43万
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财政年份:2021
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负责人:Serghei Mangul
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依托单位:
海外基金