FAIR Data Cube (FDCube)

The FAIR Data Cube (FDCube) facilitates the reuse of multi-omics data by making it Findable, Accessible, Interoperable, and Reusable (FAIR) and enabling integration across different data layers while ensuring data security and privacy.

Key Features:

• FAIR Data and Metadata Creation: Adopts and applies FAIR principles to help researchers create FAIR data and metadata.
• Data Reuse Facilitation: Facilitates re-use of multi-omics data and external datasets.
• Workflow Transparency: Makes data analysis workflows transparent.
• Privacy-Preserving Federated Analysis: Enables federated analysis of FAIR data as a privacy-preserving solution for optimal use of multi-omics data.
• Data Security and Privacy: Ensures data security and privacy for human multi-omics data that may be privacy-sensitive.

Scientific Applications:

• Multi-omics Data Integration: Integrates data generated within X-omics and external datasets across different data layers.
• Privacy-Sensitive Human Multi-omics Analysis: Enables reuse of privacy-sensitive human multi-omics data without infringing the privacy of individuals from whom data were derived.
• Actionable Knowledge Generation: Transforms multi-omics data into actionable knowledge through privacy-preserving federated analysis.

Methodology:

The FDCube adopts and applies FAIR principles and enables federated analysis of FAIR data.