- Replace problematic Material Design Icons with verified working icons - Fix icon rendering issues in provenance.md and change_management.md - Replace :material-route: with :material-link-variant: for Complete Lineage - Replace :material-account-tree: with :material-graph: for Knowledge Graph Versioning - Replace :material-schema: with :material-shape: for Ontology Versioning - Replace :material-audit: with :material-clipboard-check: for Audit Trail Compliance - Replace :material-bridge: with :material-share-variant: for Bridge Axiom Support - Remove PR_DESCRIPTION.md and SNOWFLAKE_IMPLEMENTATION.md unused files - All cards now display consistently with proper icons
9.2 KiB
Change Management
Enterprise-grade version control and audit trails for knowledge graphs and ontologies with data integrity verification
Overview
The Semantica change management module provides enterprise-grade version control, audit trails, and compliance tracking for knowledge graphs and ontologies. Designed for high-stakes domains where every change must be tracked, verified, and auditable with complete data integrity guarantees.
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:material-history:{ .lg .middle } Version Control
Complete snapshot management with SHA-256 integrity verification
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:material-database:{ .lg .middle } Dual Storage
InMemory (development) and SQLite (production) with ACID guarantees
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:material-graph:{ .lg .middle } Knowledge Graph Versioning
Entity and relationship-level change tracking with detailed diffs
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:material-shape:{ .lg .middle } Ontology Versioning
Structural change tracking for classes, properties, and axioms
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:material-clipboard-check:{ .lg .middle } Audit Trail Compliance
Complete change logs with author attribution and timestamps
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:material-shield-check:{ .lg .middle } Data Integrity
SHA-256 checksums for tamper detection and verification
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:material-compare:{ .lg .middle } Change Comparison
Detailed diff algorithms for entities, relationships, and ontology structures
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:material-backup-restore:{ .lg .middle } Backward Compatibility
Legacy support for existing ontology version management
Key Features
- ✅ Enterprise Version Control — Complete snapshot management with SHA-256 integrity verification
- ✅ Dual Storage Backends — InMemory (development) and SQLite (production) with ACID guarantees
- ✅ Knowledge Graph Versioning — Entity and relationship-level change tracking with detailed diffs
- ✅ Ontology Versioning — Structural change tracking for classes, properties, and axioms
- ✅ Audit Trail Compliance — Complete change logs with author attribution and timestamps
- ✅ Data Integrity — SHA-256 checksums for tamper detection and verification
- ✅ Change Comparison — Detailed diff algorithms for entities, relationships, and ontology structures
- ✅ Backward Compatibility — Legacy support for existing ontology version management
Quick Start
from semantica.change_management import TemporalVersionManager
# Initialize version manager
manager = TemporalVersionManager(storage_path="versions.db")
# Create versioned snapshot
snapshot = manager.create_snapshot(
graph={"entities": [...], "relationships": [...]},
version_label="v1.0",
author="user@example.com",
description="Initial knowledge graph"
)
# Compare versions
diff = manager.compare_versions("v1.0", "v2.0")
What this does:
- Initializes version manager with persistent SQLite storage
- Creates a versioned snapshot of knowledge graph data
- Compares two versions to detect changes
- Provides complete audit trail with author attribution
Core Components
ChangeLogEntry
Standardized metadata for tracking version changes with validation.
from semantica.change_management import ChangeLogEntry
@dataclass
class ChangeLogEntry:
timestamp: str # ISO 8601 format
author: str # Email address
description: str # Max 500 characters
change_id: Optional[str] = None
Key Method:
create_now(author, description, change_id=None)- Create entry with current timestamp
Storage Backends
InMemoryVersionStorage
Fast, volatile storage for development and testing.
from semantica.change_management import InMemoryVersionStorage
storage = InMemoryVersionStorage()
SQLiteVersionStorage
Persistent storage with ACID guarantees for production.
from semantica.change_management import SQLiteVersionStorage
storage = SQLiteVersionStorage("versions.db")
VersionStorage (Abstract)
Base interface for custom storage implementations.
Core Methods:
save(snapshot)- Store version snapshotget(label)- Retrieve by version labellist_all()- List all versionsexists(label)- Check if version existsdelete(label)- Remove version
Version Managers
BaseVersionManager
Abstract base class providing common version management functionality.
from semantica.change_management import BaseVersionManager
manager = BaseVersionManager(storage_path="versions.db")
Common Methods:
list_versions()- Get all version metadataget_version(label)- Retrieve specific versionverify_checksum(snapshot)- Validate data integrity
TemporalVersionManager
Knowledge Graph Version Management
Perfect for tracking changes in knowledge graphs with entity and relationship diffs.
from semantica.change_management import TemporalVersionManager
manager = TemporalVersionManager(storage_path="kg_versions.db")
# Create snapshot
snapshot = manager.create_snapshot(
graph={
"entities": [
{"id": "e1", "name": "Entity 1", "type": "Person"},
{"id": "e2", "name": "Entity 2", "type": "Organization"}
],
"relationships": [
{"source": "e1", "target": "e2", "type": "works_for"}
]
},
version_label="v1.0",
author="user@example.com",
description="Initial knowledge graph"
)
# Compare versions with detailed diffs
diff = manager.compare_versions("v1.0", "v2.0")
print(f"Entities added: {diff['summary']['entities_added']}")
print(f"Relationships modified: {diff['summary']['relationships_modified']}")
Key Features:
- Entity-level change tracking
- Relationship diff analysis
- SHA-256 checksums for integrity
- Detailed change summaries
OntologyVersionManager
Ontology Version Management
Designed for structural changes in ontologies with class, property, and axiom tracking.
from semantica.change_management import OntologyVersionManager
manager = OntologyVersionManager(storage_path="ontology_versions.db")
# Create ontology snapshot
snapshot = manager.create_snapshot(
ontology={
"uri": "https://example.com/ontology",
"structure": {
"classes": ["Person", "Organization"],
"properties": ["name", "email"],
"axioms": ["Person hasEmail exactly 1 Email"]
}
},
version_label="ont_v1.0",
author="architect@example.com",
description="Initial ontology design"
)
# Compare structural changes
diff = manager.compare_versions("ont_v1.0", "ont_v2.0")
print(f"Classes added: {diff['classes_added']}")
print(f"Axioms modified: {diff['axioms_modified']}")
Key Features:
- Class and property tracking
- Axiom change detection
- Structural comparison
- Import/export support
Data Integrity
compute_checksum
Generate SHA-256 checksum for data integrity verification.
from semantica.change_management import compute_checksum
data = {"entities": [...], "relationships": [...]}
checksum = compute_checksum(data)
print(f"SHA-256: {checksum}")
Use cases:
- Verify data integrity before storing snapshots
- Detect unauthorized modifications to version data
- Ensure consistency across distributed systems
- Generate unique identifiers for data versions
verify_checksum
Validate data integrity using stored checksums.
from semantica.change_management import verify_checksum
snapshot = manager.get_version("v1.0")
is_valid = verify_checksum(snapshot)
if not is_valid:
print("WARNING: Data integrity compromised!")
Use cases:
- Validate snapshot integrity after retrieval
- Detect data corruption or tampering
- Ensure compliance with data integrity requirements
- Verify backup and restore operations
Legacy Support
VersionManager
Original ontology version manager for backward compatibility.
from semantica.change_management import VersionManager, OntologyVersion
Note: Use OntologyVersionManager for new projects.
Error Handling
from semantica.utils.exceptions import ValidationError, ProcessingError
try:
snapshot = manager.create_snapshot(...)
except ValidationError as e:
print(f"Invalid input: {e}")
except ProcessingError as e:
print(f"Operation failed: {e}")
Common Errors:
ValidationError- Invalid email, missing fields, bad timestampsProcessingError- Database issues, file system errors
Best Practices
Performance Tips
- Use
InMemoryVersionStoragefor development/testing - Use
SQLiteVersionStoragefor production - Implement retention policies for old versions
Security Considerations
- Validate author emails for audit trails
- Use checksums for data integrity
- Store sensitive data with appropriate permissions
Usage Patterns
from semantica.change_management import TemporalVersionManager
# Development workflow
dev_manager = TemporalVersionManager() # In-memory
# Production workflow
prod_manager = TemporalVersionManager(
storage_path="secure/production_versions.db"
)
# Audit trail generation
for version in prod_manager.list_versions():
print(f"{version['timestamp']}: {version['description']} by {version['author']}")