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Creators/Authors contains: "Neang, Andrew B."

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  1. 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. 
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    Free, publicly-accessible full text available August 18, 2026
  2. 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. 
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