Data Governance for Ethical Research: Frameworks, Consent Models, and IRB Readiness

Mayta
May 21
2 min read

Updated: Jun 3

🔑 What Is Data Governance?

Data governance is the system that makes ethical use of data traceable, auditable, and compliant. It tells IRBs:➡ “We’ve thought it through.”➡ “We have safeguards at every step.”➡ “We can prove it.”

Think of it as the “operating system” of your ethical data use.

🏗️ 1. The Four Pillars—Mapped to Belmont

Pillar	What It Does	Ethical Anchor
People	Roles like stewards, DACs, analysts manage access and decisions	Respect for Persons—autonomy upheld by gatekeeping
Policies	Rules on use, sharing, retention	Beneficence—clear boundaries reduce harm
Processes	SOPs for daily ethics: logs, reviews	Justice—systematic fairness and auditability
Technology	Encryption, secure storage, access controls	Respect + Beneficence via confidentiality safeguards

🌐 2. Frameworks That Win EC Trust

FAIR = Findable, Accessible, Interoperable, Reusable—only within consent limits.
TRUST = Transparency, Responsibility, User Focus, Sustainability, Technology—repository governance quick-check.
Five Safes = Safe Projects, People, Settings, Data, Outputs—risk logic for IRB sections.
NIH 2023 = Shows US-funder expectations: data sharing ≠ ethics gap.
EU AI Act 2024, Art. 10 = Flag for IRBs: documented governance required even outside the EU.

🔍 Ethics committees are increasingly citing these in their reviews—cite them first.

🌀 3. Data Lifecycle—7 Ethical Checkpoints

Stage	Key Safeguard
Plan	DMP includes frameworks, consent model
Collect	Confirm legal basis: consent/waiver/legit interest
Store	Encrypt + separate identifiers + retention clock
Use	Role-based access + secure analysis enclaves
Share	DAC-reviewed + Five Safes + DUA
Retain	Regular necessity + compliance checks
Dispose	Certified erasure (crypto wipe or shred)

IRBs fixate on Store–Use–Share. Preempt them by governing all seven.

✅ 4. Consent Logic as Governance Choice

Consent Type	When to Use	Governance Requirements
Specific	One study	ID-linked, single use
Broad	Biobanks/future studies	Oversight body, SOPs
Tiered	Flexible	Log participant choices
Dynamic	Tech-enabled	App tracking & updates
Waiver	Minimal risk + impracticable + high value	De-ID + opt-out + audit

🔍 "Broad consent ≠ blanket consent"—you need governance and scope clarity.

📁 5. Build Your Governance Packet

🧰 Include:

Governance Charter (2-3 pages): Who decides what, when?
SOPs: Breach, access, de-ID, destruction.
DAC Terms: Who’s on it, how conflicts are managed.
DMP Annex: Tie to FAIR/TRUST + funder templates.
Training Log: Who did the GDPR/HIPAA modules?

💡 This wins audits + accelerates IRB approval.

❓ 6. Prepare for These IRB Hot Seats

“How do you stop re-ID of rare disease patients?”
“Can someone withdraw data mid-analysis? How?”
“Who governs use after study ends?”
“Why this retention duration?”
“Who holds the encryption key?”

📄 Draft answers once—reuse forever.

⚖️ 7. Justice and Equity: Not Optional

Ethical governance returns value to participants:

Co-design with under-resourced clinics, don’t just extract.
Share aggregate results in local languages.
Budget for local infrastructure/training.

🌍 Governance = ethics + justice + reciprocity.

🧠 Key Takeaways

Data governance translates ethics into practice—trackable, auditable, defensible.
Use FAIR, TRUST, and Five Safes as structure, not just labels.
Map every data stage to safeguards. IRBs hate gaps.
Choose a consent model and defend it with governance detail.
Create a lean, referenced governance bundle that survives both IRB and sponsor audit.