July Data Sharing and Reuse Seminar

Dr. Elizabeth DuPre will present Open Science Enables New Neuroscience: A call for community-driven methods development at the monthly Data Sharing and Reuse Seminar on July 14, 2023, at 12 p.m. EDT.

About the Seminar

In this talk, I will argue for the unique role of community-driven software in modern computational science. In particular, that community-driven methods development provides necessary structure for creating robust and reliable scientific inferences--and that open data availability is critical in supporting these efforts. To advance this argument, I will consider two case studies from my own work on methods for analyzing neuroimaging data. I will conclude with current opportunities and challenges in this space and provide suggestions for how researchers can support community-driven software in their own work.

About the Speaker

Elizabeth DuPre, Ph.D. is a Wu Tsai interdisciplinary postdoctoral research fellow at Stanford University, working between Professor Russ Poldrack and Professor Scott Linderman. As a psychologist and computational neuroscientist, her work focuses on modeling individual brain activity across a range of cognitive states—and assessing the generalizability of these individualized models—by extending statistical methods for human neuroimaging data analysis. Through her work, Dr DuPre has taken an active role developing tools in the open-source Python ecosystem, with a focus on improving the reproducibility of analysis workflows.

About the Seminar Series

The seminar is open to the public and registration is required each month. Individuals who need interpreting services and/or other reasonable accommodations to participate in this event should contact Danielle Johnikin (link sends e-mail) at 301-670-4990. Requests should be made at least five days in advance of the event.

The National Institutes of Health (NIH) Office of Data Science Strategy hosts this seminar series to highlight exemplars of data sharing and reuse on the second Friday of each month at noon ET. The monthly series highlights researchers who have taken existing data and found clever ways to reuse the data or generate new findings. A different NIH institute or center will also share its data science activities each month.