Home / OpenDataLedger / OpenDataLedger Specification

OpenDataLedger

The Open Ledger for the Internet’s Data

Specification

OpenDataLedger is an independent, open-source, modular API and data interoperability specification designed to provide a universal interface between applications, services, databases, data sources, and distributed infrastructure.

OpenDataLedger provides a vendor-neutral abstraction layer for connecting, querying, transforming, synchronizing, protecting, governing, auditing, publishing, and exchanging data across otherwise incompatible systems.

The architecture is local-first, zero-trust, modular, extensible, and designed to operate without requiring dependence on a single cloud provider, database vendor, authentication provider, AI provider, storage provider, or centralized service.

OpenDataLedger is designed to support virtually any database or data source through an extensible adapter and plugin architecture.

Core Modules

API Gateway Module

The API Gateway Module provides the primary interface between applications and OpenDataLedger.

Capabilities shall include:

REST APIs
GraphQL APIs
WebSocket APIs
Event-driven APIs
Request routing
Response routing
Request validation
Response validation
API versioning
API authentication
API authorization
Request size controls
Connection controls
Rate limiting
Burst controls
API quotas
Query cost controls
Endpoint policies
Identity-aware routing

The gateway shall be capable of operating independently of any specific database vendor.

Database Adapter Module

The Database Adapter Module provides the abstraction layer between OpenDataLedger and external data systems.

The adapter architecture shall allow new database systems to be added without modifying the core query engine.

Adapters shall be capable of declaring supported capabilities including:

Connection methods
Authentication methods
Schema discovery
Query translation
Read operations
Write operations
Transactions
Joins
Aggregations
Full-text search
Streaming
Change Data Capture
Versioning
Encryption
Native functions
Bulk operations

The system shall detect adapter capabilities and adjust available operations accordingly.

SQL Connectivity

The adapter framework shall support SQL systems including:

MySQL
MariaDB
PostgreSQL
SQLite
Microsoft SQL Server
Oracle
CockroachDB
YugabyteDB
DuckDB
Other SQL-compatible systems

NoSQL Connectivity

The adapter framework shall support NoSQL systems including:

MongoDB
Redis
Dragonfly
Cassandra
ScyllaDB
DynamoDB
CouchDB
Other document databases
Other key-value databases

Search and Analytics Connectivity

The adapter framework shall support analytical and search systems including:

Elasticsearch
OpenSearch
Meilisearch
ClickHouse
Other analytical engines
Other search engines

Cloud Data Connectivity

The adapter framework shall support cloud data sources including:

Snowflake
BigQuery
Amazon Athena
Amazon Redshift
Amazon S3
MinIO
Google Cloud Storage
Azure Blob Storage
Other cloud storage systems
Other cloud data services

File and Structured Data Connectivity

The adapter framework shall support:

CSV
JSON
JSONL
XML
YAML
Parquet
Avro
Local files
Network-accessible files

External API Connectivity

The adapter framework shall support:

REST APIs
GraphQL APIs
SOAP services
Webhooks
Custom HTTP services
External data services

Streaming Connectivity

The adapter framework shall support:

Apache Kafka
Apache Pulsar
Redpanda
Amazon Kinesis
WebSockets
Server-Sent Events
Custom event streams

Query Engine Module

The Query Engine Module provides a universal query abstraction across connected data sources.

Capabilities shall include:

Query parsing
Query validation
Query planning
Query optimization
Query cost estimation
Query execution
Query transformation
Query result merging
Query result validation
Query caching
Query auditing
Query provenance

The query engine shall translate universal query definitions into source-specific operations.

Cross-Database Query Module

The Cross-Database Query Module shall allow multiple independent data sources to participate in a single logical operation.

Capabilities shall include:

Cross-database joins
Cross-database filtering
Cross-database aggregation
Cross-database transformations
SQL-to-NoSQL operations
SQL-to-search operations
Federated GraphQL
Federated REST
Distributed query execution
Query result merging
Query validation
Query planning
Query optimization

The system shall identify source capabilities before executing a distributed query.

Schema Management Module

The Schema Management Module shall provide a universal representation of connected data structures.

Capabilities shall include:

Schema discovery
Schema comparison
Schema mapping
Field mapping
Type mapping
Relationship mapping
Schema aliases
Schema normalization
Schema compatibility testing
Schema versioning
Schema evolution
Schema migration recommendations
Schema change detection

Schema Virtualization Module

The Schema Virtualization Module shall provide logical schemas independent of underlying database implementations.

Capabilities shall include:

Virtual tables
Virtual collections
Virtual fields
Logical relationships
Semantic field mapping
Legacy schema abstraction
Cross-source schema mapping
Unified logical models

Applications shall be able to interact with different underlying systems through consistent logical representations.

Automatic API Generation Module

The Automatic API Generation Module shall generate interfaces from connected schemas and data sources.

Capabilities shall include:

Automatic CRUD endpoints
Automatic route generation
Filtering
Sorting
Pagination
Searching
Aggregation
Relationships
Joins
Bulk operations
Batch requests
API versioning
OpenAPI generation
Endpoint documentation
GraphQL schema generation
GraphQL resolver generation
GraphQL subscriptions
WebSocket channels
Webhook generation

Authentication Module

The Authentication Module shall provide identity verification for users, applications, services, and nodes.

Supported mechanisms may include:

API keys
OAuth
OpenID Connect
JWT
Service accounts
SSO
Multi-factor authentication
Passkeys
Hardware security keys
Federated identity

The authentication system shall support external identity providers through adapters or plugins.

Authorization Module

The Authorization Module shall control access to APIs, databases, datasets, schemas, fields, rows, queries, and operations.

Capabilities shall include:

Role-based access control
Attribute-based access control
Row-level security
Field-level permissions
Dataset permissions
Endpoint permissions
Tenant isolation
Least-privilege access
Dynamic authorization
Temporary access
Access expiration
Access revocation
Policy-based authorization

Zero-Trust Security Module

The Zero-Trust Security Module shall assume that network location alone does not establish trust.

Every applicable request shall be evaluated according to:

Identity
Authentication state
Authorization
Device or node identity
Requested resource
Requested operation
Policy
Data classification
Geographic restrictions
Risk state

No component shall automatically receive unrestricted access solely because it operates within a trusted network.

Encryption Module

The Encryption Module shall provide cryptographic protection for data and communications.

Capabilities shall include:

TLS 1.3
Application-layer encryption
End-to-end encryption where supported
Field-level encryption
Encrypted metadata modes
Encrypted credentials
Encrypted connector configurations
Signed requests
Signed responses
Cryptographic integrity verification
Secure node-to-node communication
Key rotation
Key revocation
Per-user encryption keys
Per-tenant encryption keys
Hardware-backed keys

Supported cryptographic algorithms shall be replaceable through an algorithm-agile architecture.

End-to-End Encryption

OpenDataLedger shall distinguish between transport encryption and end-to-end encryption.

Transport encryption protects communications between network endpoints.

End-to-end encryption shall protect applicable data so that intermediary infrastructure cannot access plaintext when the architecture and operation permit true end-to-end protection.

The implementation shall document exactly which components can access plaintext for each operation.

The system shall not describe encrypted transport alone as end-to-end encryption.

Cryptographic Key Management Module

The Key Management Module shall provide:

Key generation
Key storage
Key rotation
Key revocation
Key expiration
Key recovery
Key escrow where explicitly configured
Hardware-backed keys
TPM support
HSM support
Security key support
Cryptographic key versioning

Clients shall be able to maintain control over encryption keys where supported.

Post-Quantum Cryptography Module

The architecture shall support migration toward post-quantum cryptography.

Capabilities shall include:

Algorithm agility
Hybrid classical and post-quantum cryptography
Cryptographic versioning
Key migration
Post-quantum key exchange
Post-quantum signatures

Post-quantum functionality shall be replaceable as standards evolve.

Credential Vault Module

The Credential Vault Module shall protect:

Database credentials
API keys
Certificates
Encryption keys
Connector credentials
Service credentials

Credentials shall be encrypted at rest and protected by configurable access policies.

Policy Engine Module

The Policy Engine shall provide centralized evaluation of security and data usage policies.

Policies may define:

Who can access data
Which fields may be accessed
Which queries are permitted
Which regions may process data
How long access remains valid
Retention requirements
Export restrictions
Encryption requirements
Dataset usage restrictions
Human approval requirements

Policy-as-Code Module

Policies shall support machine-readable representations including:

YAML
JSON
Rego
Declarative policy definitions

The system shall validate policies before deployment where practical.

Data Transformation Module

The Data Transformation Module shall transform data during supported operations.

Capabilities shall include:

Field transformations
Type conversions
Normalization
Aggregation
Filtering
Mapping
Formatting
Validation
Data enrichment
Cross-source transformation

Data Normalization Module

Normalization capabilities shall support:

Dates
Times
Time zones
Phone numbers
Email addresses
Names
Addresses
Identifiers
Units of measurement

Normalization rules shall be configurable.

Data Validation Module

The Data Validation Module shall validate incoming and outgoing data.

Capabilities shall include:

Schema validation
Type validation
Constraint validation
Format validation
Range validation
Relationship validation
Input sanitization
Output validation
Custom validation rules

Data Contract Module

Data contracts shall define expected data structures and operational requirements.

Contracts may specify:

Schema
Data types
Relationships
Permissions
Validation rules
Usage policies
Version requirements
Compatibility requirements

Data Federation Module

The Data Federation Module shall allow data from multiple systems to be represented and accessed through a federated architecture.

Federated sources may include:

Databases
Organizations
Cloud providers
Regions
Edge nodes
On-premises systems
Public datasets
Private datasets
External APIs

Federation shall support:

Federated authentication
Federated schemas
Federated queries
Federated permissions
Federated provenance
Federated auditing

Synchronization Module

The Synchronization Module shall coordinate data between independent systems.

Capabilities shall include:

One-way synchronization
Bidirectional synchronization
Change Data Capture
Conflict resolution
Scheduled synchronization
Event-triggered synchronization
Offline synchronization
Incremental synchronization
Synchronization status tracking

Event Module

The Event Module shall provide event-driven communication.

Capabilities shall include:

Event streams
Queues
Durable events
Replayable events
Fan-out
Event filtering
Event routing
Event transformation
Event-driven workflows

Real-Time Data Module

The Real-Time Data Module shall provide supported real-time data delivery through:

WebSockets
Server-Sent Events
Streaming protocols
Database change events
Event subscriptions

Workflow Module

The Workflow Module shall allow data operations to be connected into repeatable workflows.

Supported triggers may include:

New record
Updated record
Deleted record
Schema change
API request
Security event
Scheduled event
External webhook

Workflow operations may include:

Validate
Transform
Encrypt
Query
Synchronize
Publish
Route
Cache
Export
Notify

Audit Module

The Audit Module shall maintain records of applicable system activity.

Audit information may include:

Timestamp
Identity
Source
Destination
Query
Endpoint
Operation
Result metadata
Transformation
Policy decision
Encryption state
Integrity information

Audit records shall support configurable retention and access policies.

Audit Ledger Module

The Audit Ledger Module shall provide tamper-evident audit records.

Supported mechanisms may include:

Append-only records
Hash-linked records
Cryptographic signatures
Integrity verification
Immutable storage extensions

The audit ledger shall not require blockchain infrastructure.

Provenance Module

The Provenance Module shall track the origin and processing history of data.

Provenance information may include:

Original source
Source system
Data owner
Transformation history
Query history
Dataset versions
Processing nodes
API operations
Derived datasets

Digital Provenance Certificate Module

The system may generate cryptographically verifiable provenance certificates containing:

Data origin
Dataset version
Transformation history
Processing timestamp
Integrity hashes
Digital signatures
Source identifiers

Data Versioning Module

The Data Versioning Module shall support:

Dataset versions
Schema versions
Version comparison
Version restoration
Historical schemas
Historical queries
Historical states
Change tracking

Query Replay Module

The Query Replay Module shall support forensic and development workflows involving historical operations.

Capabilities may include:

Query comparison
Query result comparison
Execution plan comparison
Historical replay
Result reconstruction
Debugging
Forensic investigation

Replay shall remain subject to applicable authorization and privacy policies.

Caching Module

The Caching Module shall reduce repeated data processing.

Supported cache architectures may include:

Local memory
Distributed cache
Redis
Connector-specific caching

Cache policies shall support configurable:

Expiration
Invalidation
Size limits
Scope
Encryption

Observability Module

The Observability Module shall provide system visibility.

Metrics may include:

Request volume
Query latency
Error rates
Connector health
Cache performance
Node health
Resource utilization
Network activity

The architecture shall support integrations with observability systems.

Configuration Module

The Configuration Module shall manage system configuration.

Supported mechanisms may include:

Environment variables
Configuration files
Encrypted configuration
Versioned configuration
Configuration validation
Secrets references

Distributed Node Module

OpenDataLedger shall support multiple independent nodes.

Nodes may operate as:

Independent installations
Federated installations
Peer-to-peer networks
Organizational clusters
Edge nodes

The core architecture shall not require a single centralized service.

Geographic Routing Module

The Geographic Routing Module shall route supported operations according to:

Latency
Availability
Data residency
Jurisdiction
Cost
Node health
Capacity
Data locality

Data Residency Module

Policies may require data processing or storage to remain within:

A country
A state
A region
A legal jurisdiction
A specific organization

Routing and federation decisions shall respect applicable residency policies.

Offline-First Module

The Offline-First Module shall support:

Local encrypted replicas
Local query execution
Offline workflows
Queued writes
Conflict resolution
Automatic synchronization

Multi-Tenant Module

The Multi-Tenant Module shall support:

Tenant isolation
Tenant-specific schemas
Tenant-specific encryption keys
Tenant-specific policies
Tenant-specific quotas
Tenant-specific audit records
Tenant-specific connectors

Data Classification Module

Data may be classified according to configurable categories such as:

Public
Internal
Confidential
Restricted
Sensitive
Regulated

Classification may automatically trigger:

Encryption
Access controls
Retention policies
Residency policies
Export restrictions

Data Usage Policy Module

Dataset owners shall be able to define:

Who may access data
Permitted uses
Export permissions
Transformation permissions
Derivative-data permissions
Access duration

Data Retention Module

The Data Retention Module shall support:

Retention policies
Automated expiration
Archival
Deletion workflows
Legal holds
Retention exceptions
Cold storage

Schema Evolution Module

The Schema Evolution Module shall detect and manage:

Added fields
Removed fields
Renamed fields
Type changes
New relationships
Deprecated fields

Capabilities shall include:

Compatibility checks
Migration recommendations
Versioned schemas
Migration workflows
Rollback support

API Versioning Module

API versioning shall support:

Versioned endpoints
Versioned schemas
Versioned GraphQL interfaces
Deprecation notices
Compatibility testing
Migration documentation

Documentation Module

The Documentation Module shall automatically generate documentation from supported schemas and APIs.

Documentation may include:

Endpoints
Parameters
Schemas
Relationships
Examples
Authentication requirements
Permissions
Query costs
Provenance

API Discovery Module

The API Discovery Module shall provide searchable discovery of:

APIs
Endpoints
Schemas
Connectors
Datasets
Events
Documentation

SDK Generation Module

The SDK Generation Module may generate client libraries for:

JavaScript
TypeScript
Python
Go
Rust
Java
C#
PHP
Dart
Flutter

Generated SDKs may include:

Typed models
Authentication
Encryption utilities
Query builders
API clients
WebSocket clients

Export and Import Module

Supported formats may include:

JSON
CSV
Parquet
SQL
GraphQL
API responses
Dataset packages

Exports may preserve:

Schema
Metadata
Provenance
Version information
Integrity information

Infrastructure Module

OpenDataLedger shall support deployment across:

Local infrastructure
Servers
Containers
Kubernetes
Edge infrastructure
Private clouds
Public clouds

Infrastructure configuration may support declarative deployment.

Infrastructure as Code Module

Supported configuration systems may include:

YAML
JSON
Terraform
Declarative configuration systems

Scaling Module

The Scaling Module shall support:

Load balancing
API replicas
Query workers
Read replicas
Distributed caches
Automatic scaling
Capacity-aware routing

Read and Write Routing Module

The system may automatically route:

Writes to primary systems
Reads to replicas
Analytical queries to appropriate analytical systems

Routing decisions shall respect consistency and policy requirements.

Distributed Query Compiler Module

The Distributed Query Compiler shall generate execution plans based on:

Source location
Data volume
Query cost
Node capacity
Network latency
Permissions
Residency requirements
Data locality

Parallel Query Module

Supported query workloads may be distributed across:

CPU resources
GPU resources
Database replicas
Cluster nodes
Edge nodes

Self-Healing Infrastructure Module

Distributed deployments may support:

Failure detection
Automatic failover
Node replacement
Load redistribution
Health checks
Recovery workflows
Replica management

Immutable Storage Module

Optional immutable storage capabilities shall support:

Append-only records
Versioned writes
Cryptographic integrity
Historical reconstruction
Legal retention
Scientific reproducibility

Core Security Gateway Controls

The core gateway shall provide protections against applicable threats including:

SQL injection
NoSQL injection
GraphQL abuse
Excessive request sizes
Excessive connections
Unauthorized access
Anomalous requests
Invalid payloads

Security controls shall be configurable and must not replace secure database configuration.

Optional Plugin Modules

OpenDataLedger shall provide a plugin architecture for capabilities that are not required by the core system.

Plugins shall be independently installable, configurable, replaceable, and removable where practical.

Plugins shall not require modification of the core engine.

Visual Query Builder Plugin

The Visual Query Builder Plugin may provide a block-based interface for constructing:

Select operations
Filters
Searches
Sorts
Joins
Groups
Aggregations
Transformations
Validation
Encryption
Publishing
Triggers
Routing
Caching
Export operations

The plugin may generate:

SQL
GraphQL
REST requests
JSON query definitions
JavaScript
TypeScript
Python
Go
Rust

Explorer Interface Plugin

The Explorer Interface Plugin may provide:

Dataset browsing
Schema exploration
Guided workflows
Visual queries
Interactive documentation
Dataset discovery

Developer Playground Plugin

The Developer Playground Plugin may provide:

REST exploration
GraphQL exploration
WebSocket testing
Schema browsing
Query editing
Mock data
API documentation
Encryption testing

Learning System Plugin

The Learning System Plugin may provide:

Interactive tutorials
Database lessons
API lessons
Query exercises
Schema exercises
Security tutorials
Governance tutorials
Example projects
Educational datasets
Interactive documentation
Beginner challenges
Developer challenges

Collaboration Plugin

The Collaboration Plugin may provide:

Query sharing
API definition sharing
Schema sharing
Connector sharing
Dashboard sharing
Workflow sharing
Notebook sharing
Transformation sharing
Validation rule sharing
Comments
Annotations
Bookmarks
Version history
Publishing
Forking
Remixing

AI Query Assistant Plugin

The AI Query Assistant Plugin may convert natural language into:

SQL
GraphQL
REST requests
Transformations
Query plans
Visual workflows

AI-generated operations shall remain subject to authentication, authorization, policy, and human approval requirements.

AI Data Modeler Plugin

The AI Data Modeler Plugin may analyze schemas and suggest:

Relationships
Indexes
Constraints
Normalization
Denormalization
Field mappings
Schema improvements
Data types
Entity relationships
ER diagrams

AI Query Optimization Plugin

The AI Query Optimization Plugin may:

Detect slow queries
Analyze query plans
Suggest indexes
Detect inefficient joins
Identify unnecessary fields
Recommend caching
Recommend partitioning
Recommend schema changes
Rewrite inefficient queries
Compare execution strategies

Autonomous Data Agent Plugin

The Autonomous Data Agent Plugin may monitor:

Data quality
Query performance
Schema changes
Connector health
Cache performance
Node health
Security events
Data drift

Automated actions shall remain subject to configured policies and approval controls.

Natural Language API Testing Plugin

The Natural Language API Testing Plugin may generate tests for:

Endpoints
Invalid input
Authentication failures
Rate limits
Injection resistance
Large payloads
Concurrent requests
Schema validation
Permission enforcement

Synthetic Data Plugin

The Synthetic Data Plugin may generate data based on:

Schemas
Relationships
Constraints
Data types
Statistical distributions

Synthetic data may support:

Development
Testing
Education
Demonstrations
AI development
Privacy-preserving experimentation

Privacy-Preserving Computation Plugin

Optional privacy modules may support:

Differential privacy
Secure multi-party computation
Tokenization
Privacy-preserving aggregation
Zero-knowledge techniques
Encrypted computation

Differential Privacy Plugin

The Differential Privacy Plugin may provide:

Noise injection
Privacy budgets
Query limits
Aggregation thresholds
Re-identification protections

Secure Multi-Party Computation Plugin

The Secure Multi-Party Computation Plugin may enable supported computations between organizations without directly exchanging underlying datasets.

Potential applications include:

Collaborative analytics
Research
Financial analysis
Statistical studies
Cross-organizational reporting

Data Quality Plugin

The Data Quality Plugin may measure:

Completeness
Accuracy
Consistency
Validity
Uniqueness
Timeliness
Freshness
Schema conformity

Predictive Analytics Plugin

The Predictive Analytics Plugin may identify:

Trends
Correlations
Outliers
Anomalies
Forecasts
Data drift

Data Lineage Visualization Plugin

The Data Lineage Visualization Plugin may display:

Sources
Transformations
Queries
Datasets
APIs
Destinations

Dashboard Plugin

The Dashboard Plugin may provide:

Tables
Charts
Maps
Heatmaps
Metrics
Filters
Interactive queries
Real-time data

Notebook Plugin

The Notebook Plugin may combine:

SQL
GraphQL
REST
Python
Query results
Charts
Documentation

Notebook content may be versioned and associated with provenance information.

Data Storytelling Plugin

The Data Storytelling Plugin may combine:

Narrative
Charts
Tables
Maps
Query results
Interactive filters
Provenance information

Storyboard Plugin

The Storyboard Plugin may create interactive presentations containing:

Data visualizations
Text
Charts
Maps
Filters
Query results
Embedded dashboards

Business Glossary Plugin

The Business Glossary Plugin may map human terminology to technical data structures.

Example mappings may include:

Customer to customer records
Revenue to defined financial calculations
Order to transaction records

Glossary definitions may be associated with schemas, datasets, policies, and provenance.

Data Stewardship Plugin

The Data Stewardship Plugin may provide:

Dataset owners
Data stewards
Security reviewers
Compliance reviewers
Technical maintainers
Review workflows
Approval workflows
Change requests
Audit history

Civic Data Plugin

The Civic Data Plugin may provide:

Public dataset catalogs
Transparency portals
Public APIs
Public data exports
Provenance records
Digital signatures
Cross-agency federation

Humanitarian Data Plugin

The Humanitarian Data Plugin may provide:

Offline operation
Low-bandwidth synchronization
Local replicas
Portable deployments
Encrypted communications
Federated nodes

Mock Database Plugin

The Mock Database Plugin may generate temporary databases for:

Development
Testing
Demonstrations
Education
API prototyping

Public API Publishing Plugin

The Public API Publishing Plugin may publish selected data through:

REST APIs
GraphQL
WebSockets
Downloadable datasets
Public catalogs

Publication shall remain subject to configured access, privacy, security, and data usage policies.

Distributed Storage Plugin

The Distributed Storage Plugin may support:

IPFS
Arweave
Filecoin
MinIO
Other distributed storage systems

External Ledger Plugin

The External Ledger Plugin may publish cryptographic proofs or audit records to compatible external ledger systems.

Blockchain infrastructure shall remain optional and shall not be required by the core platform.

Spatial Data Plugin

The Spatial Data Plugin may provide:

Geographic data exploration
Spatial queries
Geographic visualization
Three-dimensional data visualization
AR interfaces
VR interfaces
Spatial computing interfaces

Autonomous Governance Plugin

The Autonomous Governance Plugin may analyze:

Access patterns
Security risks
Data classifications
Policy violations
Retention requirements

Automated enforcement shall remain subject to administrator-defined limits and policies.

AI Transparency Plugin

The AI Transparency Plugin may provide:

Model identification
Data provenance
Source identification
Confidence indicators
Transformation records
Explainability information
Potential bias indicators
Human review requirements

Self-Auditing Endpoint Plugin

The Self-Auditing Endpoint Plugin may evaluate:

Security
Performance
Availability
Policy compliance
Schema compatibility
Error rates

The plugin may generate health reports and alerts.

Intent-Based Query Plugin

The Intent-Based Query Plugin may allow users to describe desired outcomes rather than implementation-specific queries.

The plugin may determine:

Relevant data sources
Schema mappings
Query strategy
Transformations
Aggregations
Output format

Semantic Data Layer Plugin

The Semantic Data Layer Plugin may associate:

Business concepts
Dataset fields
Relationships
Definitions
Policies
Provenance

This allows applications to interact with data based on semantic meaning rather than database-specific terminology.

Data Discovery Plugin

The Data Discovery Plugin may search connected systems for:

Datasets
Tables
Collections
Fields
APIs
Schemas
Business terms
Data owners
Provenance

Data Marketplace Plugin

The Data Marketplace Plugin may provide:

Dataset definitions
Connectors
API templates
Query templates
Visual workflows
Dashboards
Plugins
Educational datasets

Marketplace resources may be published, forked, remixed, and versioned.

Plugin Security Requirements

Plugins shall operate under defined security boundaries.

Plugin capabilities may include:

WebAssembly execution
Sandboxed Python
Isolated processes
Containerized execution
Capability-based execution

Plugins shall declare required permissions before activation.

Plugin permissions may control access to:

Network resources
Files
Databases
Encryption keys
Credentials
APIs
System resources

Plugin Capability Declaration

Plugins shall declare supported capabilities including:

Required permissions
Supported interfaces
Supported protocols
Supported data formats
Required dependencies
Security requirements
Configuration requirements

The core system shall validate plugin compatibility before activation where practical.

Vendor-Neutral Architecture

OpenDataLedger shall avoid requiring a single provider for:

Cloud infrastructure
Databases
AI services
Authentication
Storage
Monitoring
Encryption
Networking

Components shall be replaceable through adapters, interfaces, or plugins.

Human-in-the-Loop Governance

High-impact operations may require explicit human approval.

Approval gates may apply to:

Data deletion
Policy changes
Schema migrations
Public publication
Access escalation
Automated AI actions
Infrastructure changes

Administrators shall be able to define which operations require approval.

Specification Branding License (SBL)

Standard

Fully AGPL-3.0+ compliant system
Copyleft enforced for network deployments
- Required attribution to Roxanne Ardary
- Required attribution to roxanneardary.com

Optional

Specification Branding License (SBL)
Attribution-free commercial deployment
Pricing based on scale, usage, and deployment scope
https://roxanneardary.com/opendataledger/

License and Notice Requirements

OpenDataLedger is released under the GNU Affero General Public License v3.0 or later (AGPL-3.0+).

By contributing to this project, you agree that your contributions will also be released under this license.

Please note the following:

All contributions must comply with the AGPL-3.0+ terms.
Under Section 7 of the license, all redistributions, forks, and derivative works must preserve attribution to Roxanne Ardary and roxanneardary.com.
OpenDataLedger specifications are free to use with attribution. A Specification Branding License can be negotiated upon request.
The project’s notice.md file tracks attribution requirements and contributor acknowledgments.
Any update that adds new contributors or modifies attribution should also update notice.md.
When submitting a pull request, ensure that any new files maintain the attribution headers where applicable.
Network-deployed versions of this software must also remain fully AGPL-3.0+ compliant, including exposure of source code modifications when applicable under the license.

For full legal details, please refer to the AGPL-3.0+ license and the project’s notice.md file.

Notice – OpenDataLedger

Attribution Requirement: Under Section 7 of the AGPL 3.0+ license, all redistributions, forks, and derivative works, including network-deployed versions of this project, must provide attribution to Roxanne Ardary and roxanneardary.com.

Contributors

This file tracks contributors and their specific contributions to the project.

Roxanne Ardary, roxanneardary.com – March 13, 2026
Created the repository for OpenDataLedger. Developed the initial open-source universal encrypted data ledger and zero-trust API engine that automatically generates REST, GraphQL, and WebSocket APIs for any database with AI-driven query optimization and append-only cryptographic auditing.
[Add other contributors here] – [Date]
[Describe contribution in one sentence]

License – OpenDataLedger

This repository is licensed under the GNU Affero General Public License v3.0 or later (AGPL-3.0+).

Key Points

You are free to use, modify, and distribute the code.
All redistributions, forks, and derivative works or network-deployed versions must also be licensed under AGPL-3.0+ and provide attribution to Roxanne Ardary and roxanneardary.com as required under Section 7 of the license.
The software is provided “as is,” without warranty of any kind.

For the full license text, see GNU AGPL-3.0 License.