Topic: data quality

The panel explores the reuse of scientific data through the speakers’ practical experience. It considers how data quality affects reuse, what makes data suitable for artificial-intelligence applications, and the benefits of working with existing datasets. The discussion also addresses how researchers can acknowledge data creators and give appropriate credit for the resources they reuse.

MRI data quality is crucial to the result. This workshop talks some aspects we need to pay attention during the data acquisition, including FoV/slice brain coverage, synchronization between image acquisition and stimulus presentation, instruction to participant, real time quality monitoring, the usage of physiological data. Prior to the meeting, we are collecting questions for Xiangrui on anything related to mri protocol/parameters: https://www.tricider.com/admin/2YW93TsWZJ3/2DBkJUoE5Ot