The Types, Roles, and Practices of Documentation in Data Analytics Open Source Software Libraries: A Collaborative Ethnography of Documentation Work

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

Beyond advertising: New infrastructures for publishing integrated research objects

ABSTRACT: Moving beyond static text and illustrations is a central challenge for scientific publishing in the 21st century. As early as 1995, Donoho and Buckheit paraphrased John Claerbout that “an article about [a] computational result is advertising, not scholarship. The actual scholarship is the full software environment, code and data, that produced the result” [1]. Awareness of this problem has only grown over the last 25 years; nonetheless, scientific publishing infrastructures remain remarkably resistant to change [2]. Even as these infrastructures have largely stagnated, the internet has ushered in a transition “from the wet lab to the web lab” [3]. New expectations have emerged in this shift, but these expectations must play against the reality of currently available infrastructures and associated sociological pressures. Here, we compare current scientific publishing norms against those associated with online content more broadly, and we argue that meeting the “Claerbout challenge” of providing the full software environment, code, and data supporting a scientific result will require open infrastructure development to create environments for authoring, reviewing, and accessing interactive research objects

Open grant narrative: A Collaborative Interactive Computing Service Model for Global Communities | MetaDocencia

We recently submitted a grant to Chan Zuckerberg Initiative and wish to share some details about it as well as the grant narrative for others to read and re-use

Narrativa abierta de financiamiento: Modelo de servicio computacional interactivo y colaborativo para comunidades globales

Compartimos la narrativa de un modelo de servicio presentado colaborativamente

Encoding and Decoding with Electrocorticography - Computational Challenges

<p>A short talk on one computational approach to analyzing data collected with Electrocorticography.  This approach uses linearized General Linear Models to model the neural response to an input stimulus.  In this talk, I discuss its application to studying the auditory system.</p

Portable Learning Environments for Hands-On Computational Instruction

Recent tools and practices developed at UC Berkeley to utilize container and cloud technology for teaching data science

Practices and documentation in the Open Source community

Responses and analysis code to a questionnaire asking open source developers about their practices in open source software, and their beliefs about documentation's role in the community

earthlab/earth-analytics-open-gis-python-workshop: Earth Analytics Workshop on Get Started With GIS in Open Source Python

This workshop provides lessons on open source packages that can be used to plot and manipulate spatial data in Python including GeoPandas, Rasterio and Matplotlib

Community, Time, and (Con)text: A Dynamical Systems Analysis of Online Communication and Community Health among Open‐Source Software Communities

International audienceFree and open-source software projects have become essential digital infrastructure over the past decade. These projects are largely created and maintained by unpaid volunteers, presenting a potential vulnerability if the projects cannot recruit and retain new volunteers. At the same time, their development on open collaborative development platforms provides a nearly complete record of the community's interactions; this affords the opportunity to study naturally occurring language dynamics at scale and in a context with massive real-world impact. The present work takes a dynamical systems view of language to understand the ways in which communicative context and community membership shape the emergence and impact of language use-specifically, sentiment and expressions of gratitude. We then present evidence that these language dynamics shape newcomers' likelihood of returning