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.
In the Bay Area of San Francisco, the earthquake contours are not easy to define: seismology is still a relatively recent science, and controversies around methods to evaluate the earthquake risk are constant. In this context, the invitation to think about the modes of citizen science is an opportunity to reflect on the modality of hybridized scientific practices as well as the process by which the plurality and complexity of the earthquake characteristics can be articulated, and sometime reconciled. Looking at different existences of the earthquake risk, the paper investigates different assemblages that question the clear-cut distinction between citizen science and science. I’ll situate the question of the mode of citizen science within the larger framework of interdisciplinarity knowledge infrastructures and the work on ‘mode of existence’ initiated by Bruno Latour and Isabelle Stengers (2009). Expanding our understanding with regard to how CS is performed opens the possibility of reconsidering the specific types of assemblages and infrastructures from which these modes emerge and on their distinct trajectories. It is also an invitation to make visible the integration processes, the communities, and the imaginations that “make” science.
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