Description: There is an increasing focus within the neuroscience community on best practices for managing and sharing data with the ultimate goal of promoting data transparency and reuse to accelerate science. While it is crucial for experimentalists to reflect on their own data management and sharing policies, it is equally important for experimentalists to consider how data reuse might accelerate their own research. This seminar will be a brief overview of some of the pre-existing data repositories and resources currently available to researchers and discussion on validating, selecting, and appropriately crediting the use of pre-existing data. 

Audience: This is a peer-led seminar targeted to other researchers at the graduate student/postdoc level. However, anyone at any level with an interest in neuroscience research is welcome. 

Goals: Attendees should be able to better recognize when a research problem could be addressed using pre-existing data, search for and explore pre-existing datasets, validate and select datasets, and credit the author(s) of data they use. Attendees are encouraged to discuss and share resources for data reuse within their own labs and the wider neuroscience community.