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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. 

The question of how to develop and maintain appropriate, socially informed and sophisticated infrastructural systems is an ongoing concern for CSCW. Information infrastructure development efforts are usually large endeavors that involve many stakeholders, including several organizations that need to interoperate with legacy systems. Projects typically take several years to develop. The duration, variety, and sites of engagement in the development of information infrastructures can be challenging to approach with typical CSCW approaches. In this paper, we compare and analyze our varied experiences in order to generate lessons learned based on being embedded for three or more years as action researchers and ethnographers in infrastructure development projects in the domains of traffic engineering, vocational education, and ocean science. Drawing upon these experiences, as well as literature in infrastructure studies, design methodologies, and organizational studies, we extract guidance for researchers and practitioners seeking to understand and engage in long-term organizationally complex system development projects. Among these lessons, we encourage revisiting previously gathered data as scope and scale change, observing changes in the discursive reference public who will benefit from the system, and planning for different intellectual points of entry and exit. This paper lays groundwork for future developments in theory and method of collaborative design and development in and with complex systems. 

Drawing from a longitudinal case study, we inspect the activities of an expanding team of scientists and their collaborators as they sought to develop a novel software pipeline that worked both for themselves and for their wider community. We argue that these two tasks - making the software work for themselves and also for their wider scientific community - could not be differentiated from each other at the beginning of the software development process. Rather, this division of labor and software capacities emerged, articulated by the actors themselves as they went about their tasks. The activities of making the novel software work at all, and the extra work of making that software repurposable or reusable could not be distinguished until near the end of the development process - rather than defined or structured in advance. We discuss implications for the trajectory of software development, and the practical work of making software repurposable. 

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.