============= Core Concepts ============= Understanding the fundamental concepts behind ACRO's statistical disclosure control methodology. Principles-Based SDC ==================== ACRO implements a principles-based approach to statistical disclosure control, focusing on: Risk Assessment --------------- * **Automatic detection** of disclosure risks * **Context-aware** evaluation of outputs * **Proportionate response** to identified risks Human-in-the-Loop ----------------- * **Researcher guidance** rather than blocking * **Transparent reasoning** for all decisions * **Flexible override** capabilities for experts Audit and Accountability ------------------------ * **Complete audit trails** for all outputs * **Reproducible workflows** with version control * **Clear documentation** of all decisions Disclosure Control Methods ========================== Cell Suppression ----------------- Current implementation: * **Primary suppression** - Hide risky cells .. note:: **Roadmap Feature**: Secondary and complementary suppression are planned for future releases. Planned suppression methods: * **Secondary suppression** - Protect against inference * **Complementary suppression** - Additional protection Statistical Perturbation ------------------------ .. note:: **Roadmap Feature**: Statistical perturbation methods are planned for future releases. Planned perturbation methods: * **Cell-level perturbation** - Modify individual values * **Table-level perturbation** - Systematic adjustments * **Controlled rounding** - Round to safe multiples Output Restriction ------------------ Limiting what can be released: * **Threshold enforcement** - Minimum cell requirements * **Aggregation requirements** - Force higher-level summaries * **Model coefficient restrictions** - Limit regression detail ACRO Implementation =================== Safety Checks ------------- ACRO performs multiple safety checks: 1. **Threshold checks** - Minimum observation counts 2. **Dominance checks** - Concentration of values 3. **Model disclosure** - Regression coefficient safety Configuration System -------------------- Flexible configuration through: * **YAML configuration files** - Environment-specific settings * **Policy templates** - Organizational standards .. note:: **Roadmap Feature**: Method-specific runtime parameter overrides are planned for future releases. Integration Points ================== Data Analysis Libraries ----------------------- ACRO integrates with: * **pandas** - DataFrame operations and aggregations * **statsmodels** - Statistical modeling and regression * **matplotlib/seaborn** - Visualization with safety checks Research Environments --------------------- Designed for: * **Trusted Research Environments (TREs)** - Secure analysis platforms * **Data enclaves** - Controlled access environments * **Multi-user systems** - Collaborative research settings Quality Assurance ================= Validation Framework -------------------- ACRO includes comprehensive validation: * **Unit testing** - Individual function verification * **Integration testing** - End-to-end workflow validation * **Regression testing** - Consistency across versions Performance Monitoring ---------------------- .. note:: **Roadmap Feature**: Performance monitoring capabilities are planned for future releases. Planned performance tracking features: * **Execution timing** - Analysis performance metrics * **Memory usage** - Resource consumption monitoring * **Scalability testing** - Large dataset handling Best Practices ============== Configuration Management ------------------------ * Use version-controlled configuration files * Document all threshold customizations * Test configurations with sample data Workflow Design --------------- * Plan analysis workflows in advance * Use meaningful output names and descriptions * Implement regular checkpoint saves Quality Control --------------- * Review all disclosure warnings before finalizing * Validate results against expected patterns * Maintain detailed analysis documentation