artifacts/standard-named

Data Provenance & Reuse Boundaries

artifacts/standard-named/20260622__CONTINUITY-OFFICE__TRAINING__AI-AND-AUTOMATION-CONTINUITY__v1__data-provenance-and-reuse-boundaries.md

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--- catalog: "Free Training Catalog" training_id: "013" title: "Data Provenance & Reuse Boundaries" subtitle: "Stopping silent data drift" track: "AI & Automation Continuity" estimated_time: "20–30 minutes" audience:

  • IT / Security
  • Compliance
  • Product
  • AI teams

learning_outcomes:

  • Track where data comes from and why it exists
  • Prevent unauthorized reuse
  • Preserve original consent context

prerequisites: "Training 001–012 recommended" level: "Intermediate" license: "Free / Open Training" version: "1.0" last_updated: "2025-12-18" ---

Data Provenance & Reuse Boundaries

Stopping silent data drift

Core stance

Most data risk does not come from breach. It comes from reuse without remembering why data was collected.

What data provenance answers

  • Where did this data come from?
  • For what purpose was it collected?
  • Under what consent?
  • What assumptions applied?

Reuse boundaries

Reuse boundaries define:

  • Permitted secondary uses
  • Prohibited uses
  • Review or renewal conditions

Common failure pattern

“We already have the data, so let’s use it.”

This is how consent quietly expires.

Exercises

  • Pick one dataset and write its origin story
  • List allowed vs disallowed reuse
  • Define a review trigger for expanded use

Suggested next step

Attach a reuse boundary note to one existing dataset.