The course provides an introduction to the growing field of electrophysiology standards, infrastructure, and initiatives. From data curation on open research infrastructures like EBRAINS, to overviews of national data analytics platforms like Australia's AEDAPT, the lessons in this course highlight already available resources for the global neuroinformatics commuity while also reinforcing the need for and importance of FAIR science principles in future research projects.
FAIR Approaches for Electrophysiology
Course Features
Lectures
Videos
Slides
Lessons of this Course
1
1
Duration:
8:11
Speaker:
This lecture discusses the FAIR principles as they apply to electrophysiology data and metadata, the building blocks for community tools and standards, platforms and grassroots initiatives, and the challenges therein.
2
2
Duration:
15:57
Speaker:
This lecture contains an overview of electrophysiology data reuse within the EBRAINS ecosystem.
3
3
Duration:
13:34
Speaker:
This lecture contains an overview of the Distributed Archives for Neurophysiology Data Integration (DANDI) archive, its ties to FAIR and open-source, integrations with other programs, and upcoming features.
4
4
Duration:
18:56
Speaker:
This lecture contains an overview of the Australian Electrophysiology Data Analytics Platform (AEDAPT), how it works, how to scale it, and how it fits into the FAIR ecosystem.
5
5
Duration:
15:51
Speaker:
This lecture discusses how to standardize electrophysiology data organization to move towards being more FAIR.
6
6
Duration:
12:56
Speaker:
This lecture contains an overview of the China-Cuba-Canada neuroinformatics ecosystem for Quantitative Tomographic EEG Analysis (qEEGt).
