Purpose
- Document the technical architecture that enables HRL data collection, publication, ingestion, storage, analysis, and reporting.
Layers to describe
- Source systems – Field/lab systems and static publication repositories such as EDI.
- Ingestion & processing – R/Python pipelines, containers, orchestration, and CI/CD services.
- Storage & serving – Cloud object storage, databases, catalogs, APIs, and SDKs.
- Access & application – Dashboards, decision-support tools, reporting pipelines, and user interfaces.
Cross-cutting concerns
- Authentication/authorization, segmentation of sensitive data, and compliance with CARE agreements.
- Observability, logging, monitoring, and incident response procedures.
- Cost management, scalability, and sustainability over the eight-year program.
Artifacts to include
- Architecture diagrams, sequence flows, infrastructure inventories, and dependency lists.
- References to backup/disaster-recovery strategies and large-file management plans.
Ownership and evolution
- Central Data Team roles in maintaining the architecture and proposing enhancements.
- Change management process for approving new platforms, tools, or integrations via HRL governance bodies.