Best Practices for Managing Open Source Communities
管理开源社区的最佳实践
基本信息
- 批准号:393064881
- 负责人:
- 金额:--
- 依托单位:
- 依托单位国家:德国
- 项目类别:Research Grants
- 财政年份:2018
- 资助国家:德国
- 起止时间:2017-12-31 至 2022-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Community open source projects, which make up the majority of open source projects, rely on volunteer labor and need to understand how to attract, retain and motivate their volunteers. The current understanding of the practices which can be used to successfully manage volunteers in open source communities is based largely on practitioner publications. These recommendations are often anecdotal and lack scientific rigor. Meanwhile, the general volunteering literature from outside of open source contains many propositions which have not been examined in an open source context. We propose to first systematically analyze multiple sources of volunteering information and then to consolidate them as a best practice handbook. The sources are general volunteering literature, general volunteering practitioner guides, open source literature and open source practitioner guides. We will perform qualitative analysis of the sources to build our theory in the form of a best practice handbook. We will then select and validate a group of proposed best practices for open source community management. We expect to identify major gaps in the domain of episodic volunteering. Our preliminary work suggests that episodic volunteering is present in open source, but it is not addressed in the existing open source literature. Episodic volunteers are individuals who prefer short term volunteering assignments or specific tasks over a sustained commitment to a project or organization. We plan to determine how prevalent episodic volunteering is in open source communities and to derive proposed best practices for managing episodic volunteers in open source communities. Finally, we will evaluate these best practices using action research and validate them using hypothesis testing surveys.At the conclusion of this research, we expect to have: (a) created a comprehensive collection of volunteer management observations abstracted into theories of community management and expressed as a best practice handbook, (b) increased the body of knowledge on open source community management by quantifying and describing episodic volunteering, and (c) validated a group of proposed best practices of open source community management.
社区开源项目,占开源项目的大多数,依赖于志愿者的劳动,需要了解如何吸引,留住和激励他们的志愿者。目前的理解的做法,可以用来成功地管理志愿者在开源社区主要是基于从业人员的出版物。这些建议往往是轶事,缺乏科学严谨性。与此同时,来自开源之外的一般志愿文献包含许多尚未在开源环境中进行检查的命题。我们建议首先系统地分析志愿服务信息的多种来源,然后将其整合为最佳实践手册。这些来源包括一般志愿服务文献、一般志愿服务从业者指南、开源文献和开源从业者指南。我们将对来源进行定性分析,以最佳实践手册的形式建立我们的理论。然后,我们将选择并验证一组建议的开源社区管理最佳实践。我们希望找出在偶发性志愿服务领域的主要差距。我们的初步工作表明,情节志愿服务是目前在开源,但它不是在现有的开源文献中解决。情景志愿者是指那些更喜欢短期志愿任务或特定任务而不是对项目或组织的持续承诺的人。我们计划确定情景志愿服务在开源社区中的流行程度,并提出在开源社区管理情景志愿者的最佳实践。最后,我们将使用行动研究来评估这些最佳实践,并使用假设检验调查来验证它们。在本研究结束时,我们预计会:(a)建立了一个全面的志愿人员管理意见集,将其抽象为社区管理理论,并以最佳做法手册的形式表达,(B)通过量化和描述偶发志愿服务,增加了关于开源社区管理的知识体系,以及(c)验证了一组拟议的开放源码社区管理最佳做法。
项目成果
期刊论文数量(0)
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会议论文数量(0)
专利数量(0)
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Professor Dr. Dirk Riehle其他文献
Professor Dr. Dirk Riehle的其他文献
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{{ truncateString('Professor Dr. Dirk Riehle', 18)}}的其他基金
Domain Modeling Using Qualitative Data Analysis
使用定性数据分析进行领域建模
- 批准号:
418643865 - 财政年份:2019
- 资助金额:
-- - 项目类别:
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Requirements Specification using Qualitative Data Analysis
使用定性数据分析的需求规范
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508498149 - 财政年份:
- 资助金额:
-- - 项目类别:
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Industry Best Practices for Microservice Integration
微服务集成的行业最佳实践
- 批准号:
458284784 - 财政年份:
- 资助金额:
-- - 项目类别:
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