Multi-modal data at all spatial scales
Neuroscience data are heterogeneous and multi-dimensional, and it is evident that the volume, speed, and complexity of data is growing beyond the current capacity of existing analytical systems.
High-throughput molecular analyses, as well as neuroimaging and sensor technologies, are generating petabyte-sized datasets daily, and high compute speeds are required for rapid analytics at this scale. Existing environments cannot contend with the scale and diversity of data that will be required for breakthrough discovery at petabyte scale. At this scale, transferring data becomes cost- and time-prohibitive, therefore computation, tools, analysis and researchers have to be moved to the data.
The BRAIN Commons is leveraging what has been learned from the United States National Cancer Institute’s Genomic Data Commons and builds upon those data standards for managing data. This infrastructure allows for a data commons that will scale beyond the petabyte level; is interoperable; and offers co-location of data, storage and computing infrastructure facilitating data harmonization, data analysis and data sharing in the cloud.
The BRAIN Commons Data Model is the central method of organization of all data ingested by the BRAIN Commons. This is designed to maintain data and metadata consistency and provide research-ready data. The BRAIN Commons Data Model accommodates multiple types of heterogenous data found in brain research. This is essential so that we can enable data integration and analyses within and across cohorts, allowing our analyses to work across all projects within and across clouds. This also allows for computation to happen in a co-located place so that one can compute over the data in a safe and complaint way, taking computation to the data for multiple users simultaneously.
We no longer have to move data around; now, we move to the data.
BEAT-PD Data Release
The Michael J. Fox Foundation (MJFF) in coordination with Sage Bionetworks and the BRAIN Commons launched the The Biomarker and Endpoint Assessment to Track Parkinson’s Disease (BEAT-PD) Challenge in January 2020. Data is now available in the BRAIN Commons.
Learn more and access data: BEAT-PD Data Release
These data can include:
- Preclinical Data
- Clinical Data
- Imaging Data
- Electrophysiology Data
- Genomic and other Molecular *.omic Data
- Digital Health Data
Data will be stored in three zones:
Zone 1 – Public Access
Any User can access Zone 1 by registering with a valid email (public access).
Zone 2 – Controlled Access
All Qualified Researchers with Data Access Committee (DAC) approval have access to shared, restricted-access research data.
Zone 3 – Restricted Access
Designated Users with cohort-specific permission have access to individual restricted-access research datasets.