FAIR Data Publisher
Standardized data exchange with FAIR Digital Objects
The FAIR Data Publisher addresses the issue of data silos and insufficient data interoperability. As an open-source solution based on the FAIR Digital Object (FDO) standard, the software enables systematic data exchange between different data sources and data spaces.
Our Java-based software bundle provides the necessary tools for companies, research organizations, and public institutions to prepare their data assets in accordance with the FAIR principles (Findable, Accessible, Interoperable, Reusable). This creates the technical foundation for more efficient data usage across system and organizational boundaries.
It also helps companies meet regulatory requirements. Through standardized metadata and transparent access rights, it complies with the EU Data Act's requirements for data portability as well as the Data Governance Act’s provisions for the secure sharing of data across organizational boundaries.
Site Overview
The Challenge
Isolated data in an interconnected world
81%
of companies do not share data across organizational boundaries – a vast untapped potential.
(IW-Trends, 2024)
76%
of German companies see data silos as the main barrier to data sharing
(XSphere Industriestudie, 2023)
over 100
competing metadata standards hinder effective data integration
(data.europa.eu (2017), The size and trends of the EU data economy)
FAIR Digital Objects
Standardized containers for seamless data exchange
FDOs go beyond simple metadata by bundling data with essential components – persistent identifiers, rich metadata, and machine-readable structures.
This integration results in secure, digitally processable objects that enable FAIR-compliant data use: making data findable, accessible, interoperable, and reusable.
Below is the structure of a FAIR Digital Object (example of an FDO record based on configuration type 14), which serves as a standardized container for data exchange.
Data
Linked to the actual data bit sequences – it can contain both direct content as well as references to external storage locations – and represents the actual payload of the digital object.
Metadata
Bundles source-specific descriptive information – documenting the content, origin, and context of the digital object – thereby making data findable, interpretable, and scientifically traceable.
FDO metadata can incorporate domain-specific standards such as DataCite, Dublin Core, or DCAT, supporting semantic interoperability across disciplines. Its structured, machine-readable format enables automated search processes and intelligent data services, while support for multiple metadata formats facilitates integration into existing data ecosystems.
Type
Specifies the possible operations on the object – such as "delete_fdo" or other functions – enabling machine processing and automation of workflows.
Persistent Identifiers (PIDs)
Unique, persistent identifiers – similar to ISBN numbers for books – make data globally findable and citable, regardless of where it is stored.
Example: 21.T11967/1a7708f65582256a4538
Profile
Defines the allowed attributes in an FDO record – similar to a schema or data model – and ensures that FDOs within the same family remain structurally consistent and interoperable.
Rights
Contains structured references to rights specifications – governing access and usage conditions as well as licensing information – thus forming the legal basis for permissible data use. These machine-readable rights statements support automated compliance with regulatory requirements and enable fine-grained access control at the data level.
Status
Documents the current state of the object – such as "deleted" or other status information – and thus supports versioning concepts, archiving strategies, and lifecycle management.
The Fair Data Publisher
With the FAIR Data Publisher, we translate the FDO concept into a user-friendly software solution.
Our Java-based, MIT-licensed software bundle enables users to easily generate, publish, and retrieve FAIR Digital Objects from various sources.
The software bundle includes the following components:
Manager Service:
An intuitive web interface that allows FAIR Digital Objects to be easily managed and monitored.
EDC-/AAS-Adapter:
Automatic creation and retrieval of FDOs from sovereign data spaces and Asset Administration Shell (AAS) repositories – ideal for connecting complex data landscapes and integrating heterogeneous standards.
Resolver Service:
Direct access to FAIR Digital Objects via their persistent identifiers (PIDs). This ensures long-term findability and stable use of the data objects.
Distributed FDO Registry:
A distributed registration network (e.g., Handle.net) that ensures FAIR Digital Objects remain globally findable, accessible, and permanently usable.
For additional details, visit: https://fdo-one.org/
Use Case
Predictive Maintenance with FDOs
To demonstrate the practical value of the Fair Data Publisher, we take a closer look at a concrete example from predictive maintenance.
The fictional startup easyFix develops AI-based solutions for predictive maintenance. One central challenge: without high-quality training data on engine and battery loads, the AI model cannot deliver reliable forecasts.
The FAIR Data Publisher enables an optimized data flow in this context:
FDO Request:
easyFix sends a request for FDOs from the EDC offering to the Manager Service.
PID Resolution:
The Manager Service resolves the persistent identifiers (PIDs) and retrieves the handle records.
Metadata Exchange:
Metadata is exchanged between the involved systems.
Data Retrieval:
The actual data records are requested and provided.
ML Usage:
easyFix can use the data directly for machine learning.
Who benefits from this solution?
The FAIR Data Publisher is designed to meet the needs of diverse data-driven stakeholders
Data Space Operators:
Easily implementable, scalable software
Enhanced visibility of data offerings
Data Space Users:
Simplified data access
Standardized exchange methods
SMEs and Large Enterprises:
Access to a wide range of data across organizational boundaries
AI Researchers and Data Scientists:
Access to well-documented, preprocessed, and machine-readable data
Policymakers:
Implementation of interoperable data descriptions
Secure, legally compliant exchange methods
"The use of FDOs makes it possible to unlock new potentials within a globally integrated data space – for example, through the automated exchange of research data, cross-platform production optimization, or the seamless provision of training data for AI applications."
Dr. Sven Bingert
Project Manager at GWDG - Gesellschaft für wissenschaftliche Datenverarbeitung mbH Göttingen
FDOs in Comparison
Clear advantages over alternative data standards
Roadmap
Next Steps
With a successful proof of concept in place, our next step is to strengthen usability and expand product capabilities
Enhanced Scalability:
Expansion of the Handle.net network into a widely adopted FDO registry with enhanced search functionality
Automation:
Development of a software tool that automatically generates FDOs from unstructured data.
Automated FDOs:
Prototype of autonomous FDOs that enable self-management and interaction between FDOs.
User Feedback:
Testing our products with selected data spaces to gather valuable feedback.
Join the ecosystem
Isolated data silos belong to the past. Join the growing FDO community – test our software, connect via the FDO Forum, and collaborate through active working groups.
Project Partners
