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GDPR Compliance Guide

This document explains how an ORM framework and a data query framework can meet EU GDPR compliance requirements from a technical and architectural perspective.

It is intended for framework designers, platform architects, and technical compliance reviews, not as legal advice.


1. Why GDPR Matters at the Framework Level

GDPR compliance is not only a business or application-layer concern.

For ORM and data query frameworks, GDPR introduces platform-level responsibilities, because frameworks:

  • Define how data is accessed by default
  • Control how much data is returned
  • Shape how easily misuse or over-collection can happen
  • Determine whether compliance is easy or hard for application developers

A GDPR-ready framework makes non-compliant behavior technically difficult by default.


2. Core GDPR Principles Mapped to Framework Responsibilities

GDPR PrincipleFramework-Level Responsibility
Data MinimizationAvoid SELECT *, support field-level selection
Purpose LimitationTrack and constrain why data is accessed
Privacy by DefaultConservative defaults, explicit opt-in for sensitive data
AccountabilityAutomatic audit logging
Right of AccessFull, structured data export
Right to ErasureDeletion / anonymization mechanisms
Storage LimitationRetention-aware fields and policies
Data IsolationStrong tenant / scope enforcement

3. Data Minimization by Design

Required Capabilities

An ORM / query framework should:

  • Support explicit field selection
  • Avoid expanding relations automatically
  • Exclude large or sensitive fields by default

Example (Conceptual)

Q.usersWithMinimalFields().executeForList(ctx)

Only returns identifiers, not full personal profiles.


4. Sensitive Data Awareness

Framework-Level Typing

Sensitive data should be explicitly typed, not inferred by convention.

Examples:

  • email
  • phone
  • address
  • password
  • biometric

Framework behavior:

  • Sensitive fields are not selectable by default
  • Require explicit intent or purpose
  • Can enforce masking, hashing, or encryption

5. Purpose-Aware Data Access

GDPR requires knowing why personal data is processed.

Framework Capability

  • Accept a purpose context with each query
  • Use purpose to restrict selectable fields
  • Record purpose in audit logs

Conceptual example:

userContext.withPurpose("customer_support")

6. Accountability & Auditability

ORM / query frameworks should automatically generate audit records.

Minimum audit information:

ItemExample
Whouser / service identity
Whentimestamp
Whatentity + fields
Whypurpose
Resultrecord count

Audit logging must be:

  • Automatic
  • Tamper-resistant
  • Independent of business code

7. Right of Access & Data Portability

Frameworks should enable:

  • Export of all data related to a data subject
  • Structured formats (JSON / CSV)
  • Inclusion of related objects
  • Optional masking of sensitive fields

This should be possible without custom SQL per entity.


8. Right to Erasure (Right to Be Forgotten)

Frameworks must support multiple erasure strategies:

StrategyDescription
Hard DeletePhysical row removal
Soft DeleteLogical deletion + access blocking
AnonymizationData retained but no longer identifiable

Key requirements:

  • Cascading handling of relations
  • Proof of erasure without retaining personal data

9. Privacy by Default

Default framework behavior should be privacy-preserving:

AreaDefault Behavior
QueriesMinimal fields
RelationsNot auto-expanded
Sensitive fieldsNot selectable
LogsNo raw personal data
ErrorsNo data leakage

10. Multi-Tenancy & Data Isolation

For SaaS systems, GDPR strongly implies data isolation.

Framework responsibilities:

  • Mandatory tenant filters
  • No cross-tenant queries
  • Automatic scope injection

Conceptual behavior:

Q.users.execute(ctx)
// Implicitly scoped to ctx.tenantId

11. What Frameworks Should NOT Do

  • Do not default to SELECT *
  • Do not rely on developer discipline alone
  • Do not treat GDPR as a documentation-only concern
  • Do not leave audit logging to application code
  • Do not expose sensitive data via error messages

12. Auditor-Friendly Outcome

A GDPR-compliant ORM / query framework can answer:

  • Why was this data accessed?
  • Which fields were accessed?
  • By whom and for what purpose?
  • Can this data be deleted or anonymized?
  • Is misuse technically constrained?

13. Final Summary

A GDPR-compliant ORM or data query framework does not enforce business rules — it enforces safe defaults, explicit intent, and traceability.

The framework ensures that:

  • Compliance is achievable
  • Misuse is hard
  • Audits are explainable
  • Privacy is built into the system architecture

This document describes technical design patterns for GDPR-aligned data frameworks and does not replace formal legal advice.