Data, Software, and Advanced Computational Usage of University of Washington Research Leaders

Scientific research is increasingly data-intensive, relying more and more upon advanced computational resources to be able to answer the questions most pressing to our society at large. This report presents findings from a brief descriptive survey sent to a sample of 342 leading researchers at the University of Washington (UW), Seattle, Washington in 2010 and 2011 as the first stage of the larger National Science Foundation project “Interacting with Cyberinfrastructure in the Face of Changing Science.” This survey assesses these researcher’s use of advanced computational resources, data, and software in their research. We present high-level findings that describe UW researchers’: demographics, interdisciplinarity, research groups, data use, software and computational use—including software development and use, data storage and transfer activities, and collaboration tools, and computing resources. These findings offer insights into the state of computational resources in use during this time period as well as offering a look at the data intensiveness of UW researchers.

Surveying Scientists About Their Software

Software is an important infrastructural component of scientific research practice. The work of research often requires scientists to develop, use, and share software in order to address their research questions. This report presents findings from a survey of researchers at the University of Washington in three broad areas: Oceanography, Biology, and Physics. This survey is part of the National Science Foundation funded study Scientists and their Software: A Sociotechnical Investigation of Scientific Software Development and Sharing (ACI-1302272). We inquired about each respondent’s research area and data use along with their use, development, and sharing of software. Finally, we asked about challenges researchers face with and about concerns regarding software’s effect on study replicability. These findings are part of ongoing efforts to develop deeper characterizations of the role of software in twenty-first century scientific research.

Approaches and Strategy for Cancer Research and Surveillance Data: Integration, Information Pipeline, Data Models, and Informatics Opportunities

Thesis (Ph.D.)--University of Washington, 2016-04