The village that can climb the hill: Perks & hurdles of designing, collecting, and sharing a FAIR dataset in neuroscience
Over the last three decades, neuroimaging research has seen large strides in the scale, diversity, and complexity of studies, the open availability of data and methodological resources, the quality of instrumentation and multimodal studies, and the number of researchers and consortia. The awareness of rigor and reproducibility has increased with the advent of funding mandates, and with the work done by national and international brain initiatives. This session will focus on the question of FAIRness in neuroimaging research touching on each of the FAIR elements through brief vignettes of ongoing research and challenges faced by the community to enact these principles. This lecture covers the processes, benefits, and challenges involved in designing, collecting, and sharing FAIR neuroscience datasets.
- Our village - who we are
- Our hill - what we are aiming for
- Designing a FAIR dataset - stimuli, protocols, and ethics
- Collecting a FAIR dataset - quality, quality, quality
- Sharing a FAIR dataset - what we are aiming for