DATA_GOVERNANCE.md

DataHive Data Governance Framework

The DataHive data governance framework establishes protocols and standards for managing legal data across the distributed network, ensuring compliance, quality, and ethical data handling practices.

Core Components

Data Quality Management

• Data accuracy verification
• Completeness assessment
• Consistency validation
• Timeliness monitoring

Compliance Framework

class GovernanceValidator:
    def __init__(self):
        self.compliance_rules = ComplianceRules()
        self.quality_metrics = QualityMetrics()
        self.audit_trail = AuditTrail()

    async def validate_governance(self, data_entry):
        compliance = await self.check_compliance(data_entry)
        quality = self.assess_quality(data_entry)
        return self.generate_report(compliance, quality)

Governance Policies

Data Access Control

• Role-based access management
• Permission hierarchy
• Access audit trails
• Security protocols

Quality Assurance

• Multi-node validation
• Peer review processes
• Quality metrics tracking
• Improvement workflows

Implementation

Network Responsibilities

• Policy enforcement
• Standard maintenance
• Compliance monitoring
• Performance tracking

Node Operations

• Local policy implementation
• Quality control measures
• Audit participation
• Report generation

Security Measures

Data Protection

• Encryption standards
• Access controls
• Privacy preservation
• Breach prevention

Audit System

• Activity logging
• Compliance tracking
• Performance monitoring
• Issue resolution

Note: This documentation is subject to updates as governance requirements evolve.