GAIA-X
⭐ Good Practice Description:
GAIA-X expects to encourage cloud-sceptic European organisations (particularly SMEs) to take advantage of cloud, while maintaining control of their data, and to foster the creation of an open digital innovation ecosystem in which data can be collected and shared securely, while adhering to European privacy regulation.
Success Factors:
| Governance and Organizational Structure | From a governance standpoint GAIA-X is organized in two tiers of governance and into different |
|---|---|
| Data Governance | From a data governance perspective, GAIA-X expands on the archetypes and processes developed by International Data Space to deliver secure federated identity, sovereign data services, easy access to the providers, integration of existing standards, establishment of compliance framework. |
Stakeholders
-
Federal Ministry for Economic Affairs and Energy (Germany) (Germany) -
Public Sector, Academia and Industry (Germany)
Strategic Goals
- To win back sovereignty over European citizen and company data, by ensuring that data does not leave European soil unintentionally.
- To reduce dependency and risk of lock-in by enabling service and data portability.
Solutions Developed / Used
GAIA-X plans to connect decentralised infrastructure services such cloud and edge into a homogeneous, user-friendly system. It is planned as a peer-to-peer network in which GAIA-X certified organisations – known as “nodes” – can rent server capacity to each other. It is also intended to offer machine learning and artificial intelligence as a service to organisations, especially to the SMB segment through standardised APIs.
Description
Start Date
Project Focus
- Broker
- Regulator
Geographical Scope
- European
Keywords
- Edge
- Federation
Cloud Delivery Model
- IaaS
- PaaS
- SaaS
Cloud Deployment Model
- Hybrid
Project Life-Cycle Stage
- Operational Deployment
Industry
- Manufacturing
- Public Administration
- Utilities
Industry
- Mobility
- Small and Medium Enterprises (SMEs)
Technology
- Artificial Intelligence / Machine Learning
- Big Data
- Edge Computing
- Internet of Things (IoT)