Life Science — Audit Trail Creation for Research Data Traceability
FreeThis DAG establishes an audit trail to ensure data traceability in research projects. It captures data modifications and document updates while maintaining stringent security controls.
Overview
The purpose of this DAG is to create a comprehensive audit trail that guarantees the traceability of data utilized in life sciences research projects. It triggers on data modifications and document updates, ensuring that all changes are logged for compliance and transparency. The data sources include research project databases, document management systems, and metadata repositories. The ingestion pipeline begins with the collection of metadata related to data changes, followed by the logging of
The purpose of this DAG is to create a comprehensive audit trail that guarantees the traceability of data utilized in life sciences research projects. It triggers on data modifications and document updates, ensuring that all changes are logged for compliance and transparency. The data sources include research project databases, document management systems, and metadata repositories. The ingestion pipeline begins with the collection of metadata related to data changes, followed by the logging of these modifications in a secure audit database. Processing steps involve validating the integrity of the logged data, implementing security controls to protect sensitive information, and generating detailed audit reports that summarize the changes made. The outputs are stored in a document management system, allowing for easy access and retrieval. Key performance indicators (KPIs) include the number of audits conducted, response time to audit requests, and the accuracy of logged modifications. This DAG not only enhances compliance with regulatory standards but also improves the overall data governance framework within life sciences organizations, providing valuable insights into data usage and integrity.
Part of the AI Assistants & Contact Center solution for the Life Science industry.
Use cases
- Ensures compliance with regulatory requirements
- Enhances data governance and integrity
- Facilitates quick response to audit requests
- Improves transparency in research data usage
- Reduces risk of data mismanagement and breaches
Technical Specifications
Inputs
- • Research project databases
- • Document management systems
- • Metadata repositories
Outputs
- • Audit logs of data modifications
- • Detailed audit reports
- • Compliance documentation for regulatory review
Processing Steps
- 1. Collect metadata from data sources
- 2. Log changes in the audit database
- 3. Validate integrity of logged data
- 4. Apply security controls to protect data
- 5. Generate audit reports for stakeholders
Additional Information
DAG ID
WK-1449
Last Updated
2025-08-12
Downloads
42