Purpose
- Define how HRL maintains consistent data structures and categorical values across ingestion, storage, and analysis.
Schema artifacts
- Machine-readable schema files (JSON/YAML) per dataset family plus associated data dictionaries.
- Guidance on tidy data orientation, units, coordinate systems, and missing-value codes.
Vocabulary management
- Standard lists for species, locations, habitat types, gear, QA codes, and other enums.
- Processes for requesting new terms, reviewing changes, and versioning vocabularies.
Quality and validation
- Automated checks that enforce schema/vocabulary compliance at ingestion and analysis stages.
- Error reporting workflows and remediation tracking.
Governance
- Ownership by the Central Data Team with review cadence involving the HRL Science Committee.
- Publication of updates through the data catalog, templates, and quickstarts.