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This template should be used to implement the majority of the services, there might be exceptions that are not known yet.
The following table gives an overview which services are required.
List of Essential Services for the Distributed Data Market Ecosystem
| Service Name | Description |
|---|---|
| User Management (with Authentication Federation & Identity Mapping) | Manages user authentication, registration, and profile management across distributed instances. Uses Azure AD B2C to provide federated login (Microsoft, Google, corporate SSO). Each user’s identity is mapped to a unique internal ID, ensuring they can be recognized across different ecosystem services without requiring a new login. |
| Role & Rights Management | Defines and enforces access control, user roles, and permissions across instances for data usage and monetization. |
| Consent & Privacy Management | Allows users to manage data-sharing permissions, revoke consent, and ensure compliance with GDPR, EU Data Act, and similar regulations. |
| Data Marketplace | Enables data providers (OEMs, fleet managers) to list, sell, and manage datasets while allowing buyers to search, preview, and purchase data. |
| API Gateway & Management | Provides a secure API layer for communication between distributed instances. Ensures authentication and standardization using Azure API Management. |
| Data Storage & Processing | A scalable, globally distributed database for storing metadata, logs, and access control settings. Uses Azure Cosmos DB and Azure Functions for event-driven processing. |
| Search & Discovery (Global Registry) | Provides a federated registry for discovering datasets, services, and API endpoints across distributed instances. Supports metadata tagging for easy filtering. |
| Monetization & Billing | Handles subscription models, pay-per-use pricing, and revenue-sharing among participants. Uses Azure Payment Connector for transactions. |
| Security & Authentication | Ensures secure access using OAuth 2.0, OpenID Connect, and multi-factor authentication (MFA). Protects against unauthorized access and fraud. |
| Data Anonymization & Compliance | Automatically anonymizes sensitive user data before sharing, ensuring compliance with data privacy laws. Uses Azure Purview for governance. |
| Service Orchestration | Manages workflows for data ingestion, user onboarding, and API integrations using Azure Logic Apps or Azure Event Grid. |
| Logging & Monitoring | Provides real-time monitoring and logging of ecosystem activities, including API requests, user transactions, and data access logs. Uses Azure Monitor & Log Analytics. |
| Incident & Violation Handling | Detects anomalies, data breaches, or regulatory violations and alerts operators. Provides remediation workflows. |
| Regional Compliance Management | Ensures that different jurisdictions comply with data residency laws (e.g., GDPR, CCPA) by routing requests to appropriate data centers. |
| Data Aggregation & Insights | Aggregates data from multiple sources and provides insights using Azure Synapse Analytics and Power BI for visualization. |
| Edge Processing | Handles real-time data processing closer to the source for low-latency applications (e.g., connected vehicles, fleet monitoring). Uses Azure IoT Edge. |
| Developer Portal | A hub for developers to access API documentation, sample datasets, and testing environments for building applications. |
| Customer Support & Help Desk | Provides technical assistance, user guides, and ticketing support for all ecosystem participants. |
| Distributed Node Management | Manages the lifecycle of distributed instances, allowing operators (OEMs, data collectors) to onboard, configure, and maintain their nodes. |
| Capability Registration & Node Discovery | A global registry where distributed instances register their capabilities (e.g., data types available, APIs, supported regions). |
| Instance Health & Load Balancing | Ensures each instance is healthy, load-balanced, and available, using Azure Front Door to route traffic efficiently across distributed nodes. |
As for all µ-service based architectures it is important to cut the services in a way that on one hand the
size of the service stays maintainable but on the other hand that they are not too simple (too many services).
Workflows
A concept called orchestration makes out of the services a workflow. For example, if a user from the type of a
data collector is onboarding the orchestrator will ask to onboard a data source as well. These workflows
will be described in here.
Overview
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