Project Summary
My work as a Cloud Research Support Engineer will be firmly rooted in the research tradition which emphasizes that studying the uptake of a new technology or technological approach, no matter the type of work or profession, begins with capturing how the people charged with changing their activities respond to the change “on the ground.” In this vein, the study will first aim to document the current status of cloud research in one scientific discipline—astronomy. Through ethnographic interviews and observations of scientific meetings, public discussions, and other communication outlets, I will categorize the types of research currently employing cloud-based tools, including how cloud computing has changed the methodological approaches, research roles, and necessary skills required for scientific discovery.
In the next step, I will document the barriers researchers face in conducting their work using cloud services. This portion of the study will focus on both scientists who are currently conducting research using high performance and cloud computing services offered by a given organization (e.g., the National Center for Supercomputing Applications) and those who are attempting to begin utilizing cloud services in their work. Semi-structured interview protocols will include questions about the human and organizational support structures scientists engage with in carrying out cloud research, where those structures currently succeed or fall short in supporting research, and how organizations might better support cloud research efforts. Armed with themes generated from qualitative data analysis, I will develop and deploy a survey about researchers’ experiences with cloud research. I hope to develop this part of the study into actionable recommendations for promoting cloud research, governing cloud services use, and augmenting the humanware systems scientists rely upon to coordinate discovery. Throughout the project, I’ll aim to work toward publications in the organization science and human-computer interaction fields and in generalized reports and white papers.
Bio
Dan Sholler is a Postdoctoral Fellow with the rOpenSci Project at the University of California, Berkeley. He received his Ph.D. from the University of Texas at Austin School of Information in 2017, where he was a member of the Information Work Research Group. He studies the creation, development, and governance of digital infrastructures in a variety of industries, focusing on technology adoption, resistance, and use in the day-to-day work of users. In his dissertation work, advised by Dr. Diane Bailey, Dan studied the implementation of a federal program aimed at constructing an infrastructure to support data-driven healthcare delivery. The qualitative, ethnographic study examined the sources and outcomes of caregivers’ resistance to the program, focusing on the local realities of electronic medical records use and the resulting national-level movement of resistance to upend the federal program.
In his current work, Dan is working alongside co-advisors Dr. Karthik Ram and Dr. Carl Boettiger (UC-Berkeley) and Dr. Daniel Katz (University of Illinois Urbana-Champaign) to examine the development of infrastructures to support “open science.” The open science movement intends to make the processes and products of scientific research freely available to the public. Infrastructure development in scientific research requires voluntary contributions from disparate members of the scientific community, necessitating unique governance strategies that elicit engagement and manage resistance. By comparing governance strategies within and across scientific disciplines, the study seeks to document how organizations develop and implement strategies, explain how scientists are responding, and develop the findings into actionable recommendations for open science organizations, universities, and policymakers. At Berkeley, Dan is also a founding member of the Berkeley School of Information’s Algorithmic Fairness and Opacity Working Group and the Berkeley Institute for Data Science’s Best Practices and Meta-Research Working Group. He is also a fellow at the Berkeley Center for Technology, Society & Policy.