Data Information System (DAISY)

Data Information System (DAISY) maps data and data flows to support GDPR accountability for biomedical research institutions.

Key Features:

• Data-flow mapping: Maps data and data flows at the project level to capture project-specific processing and complex data movement.
• Project-centric model: Represents data processing around research projects rather than generic, process-based models.
• Collaborative processing capture: Documents collaborative and cross-institutional data processing inherent to biomedical research.
• GDPR obligation analysis: Integrates analysis of transparency and record-keeping obligations associated with each GDPR principle.
• Comprehensive record generation: Produces detailed records of data processing and data flows to support accountability and documentation.

Scientific Applications:

• GDPR accountability and documentation: Provides documentation to demonstrate adherence to GDPR transparency and record-keeping obligations.
• Biomedical research data management: Captures and documents complex, project-specific data processing workflows in biomedical research.
• Cross-institutional data mapping: Maps data flows across collaborating institutions such as the Luxembourg Centre for Systems Biomedicine and the ELIXIR-Luxembourg data hub.

Methodology:

DAISY performs project-centric data-flow mapping and an analysis of transparency and record-keeping obligations for each GDPR principle to produce comprehensive documentation of data processing.