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This collaborative "essay of essays" begins with an introduction by a professor of human centered design and engineering who has been working concurrently with PhD students to study collaborative system design. We undertake widely scoped qualitative research studies, that we categorize as "extended studies," that cut across units of analysis, organizations, or time. Our research explores how people create new ways to enact systems that support the knowledge work of different stakeholders. In response to an anchor essay, the students have written reflections about the multifaceted experience of doing extended studies. Many of these studies began by focusing on a particular project to develop a particular system or information infrastructure, and associated standards. Over time the studies came to center on collaborative dynamics per se, and also how collaborative dynamics shifted the scope and functionality of products, sometimes also affecting programmatic and infrastructural level changes. 

Studies of research software development have focused on how to promote or encourage the adoption of software engineering practices, but we do not have a good empirical understanding of strategies that researchers have already begun to take in order to integrate those practices into research work in sustainable ways. We conduct a comparative case study of two research groups in different fields, and characterize two approaches that they have taken to get research software engineering work done: practice integration and differentiating expertise. From these findings we argue that examining outcomes of change in research software development practice is critical for understanding sustainability and the ramifications of such changes for scientific work. 

Along with a number of other computing technologies, cloud computing services are increasingly being promoted as a way of enabling openness, reproducibility, and the acceleration of scientific work. While there have been a variety of studies of the cloud in terms of computing performance, there has been little empirical attention to the changes going on around cloud computing at the level of work and practice. Through a qualitative, ethnographic study, we follow a cosmology research group’s transition from a shared high performance computing cluster to a cloud computing service, and examine the cloud service as a coordinative artifact being integrated into a larger ecology of existing practices and artifacts. We find that the transition involves both change and continuity in the group’s coordinative work and maintenance work, and point out some of the effects this adoption has on the group’s larger set of practices. Finally, we discuss practical implications this has for the broader adoption of cloud computing in university-based scientific work. 

Black women remain severely underrepresented in computing despite ongoing efforts to diversify the field. Given that Black women exist at the intersection of both racial and gendered identities, tailored approaches are necessary to address the unique barriers Black women face in computing. However, it is difficult to quantitatively evaluate the efficacy of interventions designed to retain Black women in computing, since samples of computing students typically contain too few Black women for robust statistical analysis. Using about a decade of student survey responses from an National Science Foundation–funded Broadening Participation in Computing alliance, we use regression analyses to quantitatively examine the connection between different types of interventions and Black women’s intentions to persist in computing and how this compares to other students (specifically, Black men, white women, and white men). This comparison allows us to quantitatively explore how Black women’s needs are both distinct from—and similar to—other students. We find that career awareness and faculty mentorship are the two interventions that have a statistically significant, positive correlation with Black women’s computing persistence intentions. No evidence was found that increasing confidence or developing skills/knowledge was correlated with Black women’s computing persistence intentions, which we posit is because Black women must be highly committed and confident to pursue computing in college. Last, our results suggest that many efforts to increase the number of women in computing are focused on meeting the needs of white women. While further analyses are needed to fully understand the impact of complex intersectional identities in computing, this large-scale quantitative analysis contributes to our understanding of the nuances of Black women’s needs in computing. 

Abstract Sustainable agricultural water systems are critical to ensure prosperous agricultural production, secure water resources, and support healthy ecosystems that sustain livelihoods and well-being. Many growing regions are using water unsustainably, leading to groundwater and streamflow depletion and polluted water bodies. Often, this is driven by global consumer demands, with environmental and social impacts occurring in regions far from where the crop is ultimately consumed. This letter defines sustainable agricultural water limits, both for quantity and quality, tying them to the impacts of agricultural water use, such as impacts on ecosystems, economies, human health, and other farmers. Imposing these limits will have a range of both positive and negative impacts on agricultural production, food prices, ecosystems, and health. Pathways forward exist and are proposed based on existing studies, showing the gains that can be made from the farm to global scale to ensure sustainable water systems while sustaining agricultural production. 

Recent CSCW research on the collaborative design and development of research infrastructures for the natural sciences has increasingly focused on the challenges of open data sharing. This qualitative study describes and analyzes how multidisciplinary, geographically distributed ocean scientists are integrating highly diverse data as part of an effort to develop a new research infrastructure to advance science. This paper identifies different kinds of coordination that are necessary to align processes of data collection, production, and analysis. Some of the hard work to integrate data is undertaken before data integration can even become a technical problem. After data integration becomes a technical problem, social and organizational means continue to be critical for resolving differences in assumptions, methods, practices, and priorities. This work calls attention to the diversity of coordinative, social, and organizational practices and concerns that are needed to integrate data and also how, in highly innovative work, the process of integrating data also helps to define scientific problem spaces themselves.