Multi-modal data at all spatial scales

Explore the BRAINCommons:   Community  |  Tools

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.

Brain Disease

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 BRAINCommons 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 BRAINCommons Data Model is the central method of organization of all data ingested by the BRAINCommons. This is designed to maintain data and metadata consistency and provide research-ready data. The BRAINCommons 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 BRAINCommons launched the The Biomarker and Endpoint Assessment to Track Parkinson’s Disease (BEAT-PD) Challenge in January 2020. Data is now available in the BRAINCommons.

Learn more and access data: BEAT-PD Data Release

These data can include:

  1. Preclinical Data
  2. Clinical Data
  3. Imaging Data
  4. Electrophysiology Data
  5. Genomic and other Molecular *.omic Data
  6. Digital Health Data

Data will be stored in three zones:

BRAIN Commons - Data

Zone 1 – Public Access

Any User can access Zone 1 by registering with a valid email (public access).

Zone 2 - Controlled 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

Zone 3 – Restricted Access

Designated Users with cohort-specific permission have access to individual restricted-access research datasets.

Are you interested in contributing data to the BRAINCommons? Learn more about How to Participate.