Standardize Your Data

Active Workflow Canonical Terms Required Package-first

Use this page when you need the shortest correct path from a messy source dataset to a standards-aligned salmon data package.

This page is intentionally concise. For full package details or SPSR intake rules, use the linked canonical pages.

Start here

1. Map your columns to canonical terms
   • Use GC DFO Salmon Ontology (WIDOCO) and the metasalmon reusing-standards vignette
   • Record the full IRI for each mapped field
2. Create a salmon data package
   • Prefer the maintained metasalmon workflow: 5-Minute Quickstart and Publishing Data Packages
   • Use the canonical layout: metadata/ + data/ with optional root datapackage.json
   • Use the Salmon data package specification when you need the field-by-field contract
3. Review + validate before you upload or publish
   • Complete the metasalmon review loop on the package folder
   • Run metasalmon::validate_salmon_datapackage(pkg_path, require_iris = TRUE) before downstream submission
4. Choose your destination path
   • SPSR / FSAR intake → Salmon data package + guided review + SPSR intake path
   • External release → Publish Your Data

Minimal standardization checklist

• scope and grain are clear
• identifiers, time fields, measurements, and controlled values are mapped
• canonical IRIs are recorded in metadata/column_dictionary.csv
• package structure follows metadata/ + data/
• package-level validation passes before downstream submission

Cookbook spotlight

If you are working with escapement data, use the focused recipe:

• CU/composite escapement estimates for package-first SPSR intake

For a longer implementation walkthrough, use:

• FSAR Data Standardization Workflow
• FSAR to SPSR: End-to-End Example

Next Steps

• Salmon Data Integration System — Start Here
• Salmon data package specification
• Salmon data package + guided review + SPSR intake path
• Data Stewardship Unit contact