Collaborative Research: DASS: Transitioning open-source software projects to accountable community governance
合作研究:DASS:将开源软件项目转变为负责任的社区治理
基本信息
- 批准号:2217653
- 负责人:
- 金额:$ 15万
- 依托单位:
- 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:2022-07-15 至 2024-06-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Open-source software (OSS) underlies critical infrastructure around the US, and has a hand in every aspect of digital life. However, most OSS projects are run as “benevolent dictatorships” with no formal accountability to their community or society. Fortunately, increasing numbers of prominent OSS projects are voluntarily transitioning out of founder-ownership into democratic community ownership. By understanding how these transitions proceed, and how often they succeed, critical OSS projects will face fewer risks as they navigate a dynamic policy landscape and shifting community needs. By addressing these challenges, this team can capture the institutional context of accountable OSS design, and develop general tools for transitioning software projects to accountable governance. To leverage the social benefit of serving the OSS ecosystem, and improve its accountability to community members and other stakeholders, we will host workshops and publish a guide on how to transition OSS projects to community governance.This research pursues three research questions. The first is using data science to explore the accountability systems that OSS communities define for themselves, and how they co-evolve with their code and contributor network. The second is using case studies to develop a deep understanding of the range of governance-transition processes. The third is engineering software for helping OSS projects design their transition to community accountability. The work is providing the following main innovations: (1) advances in the computational representation of policy texts, (2) an extension of theories of governance dynamics into discontinuous governance transitions (i.e., transitions to community governance), (3) an extension of community governance processes to the OSS context, and (4) theoretically-informed governance design tools.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.
开源软件(OSS)是美国周围关键基础架构的基础,并且在数字生活的各个方面都有一支。但是,大多数OSS项目都是作为“仁慈独裁政权”运行的,对其社区或社会没有正式的责任。幸运的是,越来越多的著名OSS项目正在自愿将创始人所有权转变为民主社区所有权。通过了解这些过渡如何进行,以及它们成功的频率,关键的OSS项目在导航动态的政策格局和改变社区需求时会面临更少的风险。通过解决这些挑战,该团队可以捕获负责任的OSS设计的机构背景,并开发用于将软件项目转换为负责治理的一般工具。为了利用为OSS生态系统服务,并提高对社区成员和其他利益相关者的问责制的社会利益,我们将举办研讨会并发布有关如何将OSS项目转变为社区治理的指南。这项研究提出了三个研究问题。首先是使用数据科学来探索社区自行定义的问责制,以及它们如何与代码和贡献者网络共同发展。第二个是利用案例研究来深入了解治理转变过程的范围。第三个是工程软件,用于帮助OSS项目设计其向社区问责制的过渡。这项工作正在提供以下主要创新:(1)政策文本的计算表示进展,(2)将治理动态理论扩展到不连续的治理转变(即向社区治理过渡),(3)将社区治理过程扩展到OSS上下文,并统计了统计的统计范围,以及(4)统计的统计范围。值得通过基金会的智力优点和更广泛的影响审查标准来通过评估来支持。
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
GitHub OSS Governance File Dataset
- DOI:10.1109/msr59073.2023.00089
- 发表时间:2023-04
- 期刊:
- 影响因子:0
- 作者:Yibo Yan;Seth Frey;Amy Zhang;V. Filkov;Likang Yin
- 通讯作者:Yibo Yan;Seth Frey;Amy Zhang;V. Filkov;Likang Yin
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Amy Zhang其他文献
Preliminary mapping of HopZ1b resistance-associated loci in Arabidopsis thaliana via EMS and ecotype screens
- DOI:
- 发表时间:
2016-11 - 期刊:
- 影响因子:0
- 作者:
Amy Zhang - 通讯作者:
Amy Zhang
A review of principles in design and usability testing of tactile technology for individuals with visual impairments
视觉障碍人士触觉技术的设计和可用性测试原则回顾
- DOI:
10.1080/10400435.2016.1176083 - 发表时间:
2017 - 期刊:
- 影响因子:1.8
- 作者:
Emily L. Horton;R. Renganathan;Bryan N. Toth;Alexa J. Cohen;Andrea V. Bajcsy;A. Bateman;Mathew C. Jennings;Anish Khattar;Ryan S. Kuo;Felix A. Lee;Meilin K. Lim;Laura W. Migasiuk;Amy Zhang;Oliver K. Zhao;Márcio A. Oliveira - 通讯作者:
Márcio A. Oliveira
Visual outcomes of combined cataract and minimally invasive glaucoma surgery.
白内障和微创青光眼联合手术的视力结果。
- DOI:
- 发表时间:
2020 - 期刊:
- 影响因子:2.8
- 作者:
S. Sarkisian;N. Radcliffe;P. Harasymowycz;S. Vold;Thomas D. Patrianakos;Amy Zhang;L. Herndon;J. Brubaker;M. Moster;Brian A. Francis - 通讯作者:
Brian A. Francis
A Deep Learning Approach to Population Based COVID-19 Case Prediction in the US
美国基于人群的 COVID-19 病例预测的深度学习方法
- DOI:
- 发表时间:
2021 - 期刊:
- 影响因子:0
- 作者:
Sameer Sundrani;Amy Zhang - 通讯作者:
Amy Zhang
Learning Action-based Representations Using Invariance
使用不变性学习基于动作的表示
- DOI:
10.48550/arxiv.2403.16369 - 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Max Rudolph;Caleb Chuck;Kevin Black;Misha Lvovsky;S. Niekum;Amy Zhang - 通讯作者:
Amy Zhang
Amy Zhang的其他文献
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{{ truncateString('Amy Zhang', 18)}}的其他基金
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2340651 - 财政年份:2024
- 资助金额:
$ 15万 - 项目类别:
Continuing Grant
CAREER: Tools for User and Community-Led Social Media Curation
职业:用户和社区主导的社交媒体管理工具
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2236618 - 财政年份:2023
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$ 15万 - 项目类别:
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协作研究:SaTC:核心:大型:加密通信平台的隐私保护滥用预防
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2120497 - 财政年份:2021
- 资助金额:
$ 15万 - 项目类别:
Continuing Grant
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