Amy Neeser co-authored this post with Chris Hoffman
Increasingly, researchers in a wide range of fields at UC Berkeley are applying novel data science approaches to very large sensitive and restricted data sets. Working closely with Berkeley Research Computing (BRC), the Research Data Management (RDM) Program has been helping dozens of faculty, students, and postdocs working with sensitive data by providing consulting expertise in a number of disciplines, including the biological sciences, public health, social welfare, demography, computer science, and more. The combined approach of providing data management and computation support helps researchers integrate data management and curation best practices into their larger research workflows while protecting their data.
Because of increasing work with sensitive data by campus researchers, the Research IT team in Research, Teaching and Learning (RTL) has launched the Securing Research Data and Computation initiative. In addition to helping researchers, the initiative also coordinates efforts among campus offices that are involved in reviewing data use agreements and security plans. As a product of this work, the OneIT community is coming together to align service development roadmaps, improve consulting expertise, and develop policy and processes. Recent conversations with campus leadership and faculty in the biological sciences are helping shape these future directions.
Research IT is using Research and Academic Innovation (RAE) benchmarking to compare Berkeley’s services for secure data with peer institutions. Benchmarking results will be used to develop a set of recommendations to help campus stakeholders determine future service investments and enhancements as well as develop service roadmaps. In the coming year, RTL plans to announce several improved and new services for researchers working with sensitive and restricted data.
See also the results of a multi-departmental analysis of this challenge on campus, published in December 2017.