Computational research and data analytics increasingly relies on complex ecosystems of open source software (OSS) “libraries” – curated collections of reusable code that programmers import to perform a specific task. Software documentation for these libraries is crucial in helping programmers/analysts know what libraries are available and how to use them. Yet documentation for open source software libraries is widely considered low-quality. This article is a collaboration between CSCW researchers and contributors to data analytics OSS libraries, based on ethnographic fieldwork and qualitative interviews. We examine several issues around the formats, practices, and challenges around documentation in these largely volunteer-based projects. There are many different kinds and formats of documentation that exist around such libraries, which play a variety of educational, promotional, and organizational roles. The work behind documentation is similarly multifaceted, including writing, reviewing, maintaining, and organizing documentation. Different aspects of documentation work require contributors to have different sets of skills and overcome various social and technical barriers. Finally, most of our interviewees do not report high levels of intrinsic enjoyment for doing documentation work (compared to writing code). Their motivation is affected by personal and project-specific factors, such as the perceived level of credit for doing documentation work versus more ‘technical’ tasks like adding new features or fixing bugs. In studying documentation work for data analytics OSS libraries, we gain a new window into the changing practices of data-intensive research, as well as help practitioners better understand how to support this often invisible and infrastructural work in their projects.

中文翻译：

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数据分析开源软件库中文档的类型，角色和做法

计算研究和数据分析越来越依赖于开放源代码软件（OSS）“库”的复杂生态系统，这些生态系统是精选的可重用代码集合，程序员可以导入这些代码来执行特定任务。这些库的软件文档对于帮助程序员/分析人员了解哪些库可用以及如何使用它们至关重要。但是，开源软件库的文档被普遍认为是低质量的。本文是CSCW研究人员与数据分析OSS库的撰稿人之间的合作，基于人种学现场调查和定性访谈。在这些主要基于志愿者的项目中，我们研究了有关格式，实践和文档方面的挑战的几个问题。这些库周围存在许多不同种类和格式的文档，扮演着各种教育，促销和组织的角色。文档背后的工作类似地是多方面的，包括编写，审阅，维护和组织文档。文档工作的不同方面要求贡献者具有不同的技能，并克服各种社会和技术障碍。最后，我们的大多数受访者并未表示从事文档工作（与编写代码相比）的内在享受很高。他们的动机受个人和项目特定因素的影响，例如，进行文档工作的信誉程度，以及添加新功能或修复错误等更多的“技术”任务。在研究数据分析OSS库的文档工作时，我们获得了一个新窗口，可以了解数据密集型研究的不断变化的实践，