The National Research Data Infrastructure (NFDI) in Germany is a decentralized, consortium-based network that brings together universities, research institutions, and infrastructure providers to collaboratively manage and provide access to research data across disciplines. Organized into disciplinary consortia—each addressing specific scientific domains such as life sciences, humanities, or engineering—the NFDI supports the development of tailored data management solutions aligned with the FAIR principles. While promoting openness, the NFDI also incorporates robust mechanisms to protect sensitive data when full access is not feasible due to legal or ethical constraints. These include the use of de-identified and aggregated data, secure environments for certified users, and controlled access protocols. Metadata repositories further enhance discoverability of restricted datasets under appropriate conditions. To support secure and seamless access, the IAM4NFDI initiative enables federated and decentralized identity management, allowing users from around 400 German research and higher education institutions—and approximately 5,000 international organizations—to access NFDI services via a unified Authentication & Authorization Infrastructure (AAI), with integration pathways to broader frameworks like the European Open Science Cloud (EOSC).
National Research Data Infrastructure (NFDI)
Abstract
Country | Germany |
Start date | 2020 |
Annual Budget | €85M |
Responsible organisation(s) | Government agency |
Target group(s) | Researchers, academic institutions, private sector companies, and the broader scientific community in Switzerland |
Policy instrument type | federated data infrastructure |
The NFDI's development was initiated to address the need for a sustainable infrastructure to manage and provide access to research data across disciplines in Germany, ensuring adherence to the FAIR (Findable, Accessible, Interoperable, Reusable) principles. Prior to the NFDI, Germany had no unified, national-level framework to handle research data. Research data management practices were often fragmented, with many institutions and disciplines adopting their own ad hoc systems.
There was a growing need for a decentralized but well-coordinated system that would address the specific requirements of different scientific disciplines while avoiding silos and duplication of efforts.
To ensure that access to sensitive research data is appropriately managed, granting permissions to authorized individuals while upholding data protection standards.
To establish a secure, federated, and user-friendly Identity and Access Management (IAM) framework.
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