FDO Connect
Development of a service architecture for data exchange with FAIR Digital Objects
As part of the initiative MISSION KI - National Initiative for Artificial Intelligence and Data Economy, a modular, distributed software architecture based on FAIR Digital Objects (FDOs) is being developed. The aim is to improve the utilisation of cross-sector data spaces for AI applications. The architecture is intended to enable the publishing, linking and retrieval of structured, machine-readable data objects. The project thus creates a technological basis for trustworthy, reusable data infrastructures to promote a data economy oriented towards the common good. DFKI is responsible for the robotics use case within the domain integration work package. It is developing a standardised FDO profile for robotics research data, converting exemplary field test data into FDOs and integrating them into domain-specific databases. In addition, tools for bidirectional data exchange and comprehensive documentation of the methods and findings for broad reuse in the robotics context are being developed.
| Duration: | 14.04.2025 till 30.09.2025 |
| Donee: | German Research Center for Artificial Intelligence GmbH |
| Sponsor: | MISSION KI — National Initiative for Artificial Intelligence and Data Economy is a project of acatech — National Academy of Science and Engineering, funded by the Federal Ministry for Digital and Transport Affairs (BMDV). |
| Partner: |
AMI Advanced Machine Intelligence |
| Application Field: | Data management |
Project details
As part of MISSION AI – National Initiative for Artificial Intelligence and Data Economy, a distributed software architecture based on FAIR Digital Objects (FDOs) is being developed. The aim is to provide a trustworthy, open infrastructure that enables cross-sector and cross-domain data exchange for AI applications. The project focuses on four interrelated work packages: the development of an FDO service architecture (WP1), the development of a tool for the automated conversion of unstructured data into FDOs (WP2), practical implementation in several use cases (WP3), and the legal and economic evaluation of the solution (WP4). The use cases from various socially relevant domains – including digital medicine, quantum computing, complex systems, industrial battery manufacturing and robotics – demonstrate the added value of FDOs for data-driven AI applications. In addition, WP4 provides recommendations for action for the broad, legally compliant and economically viable use of the developed architecture.
The German Research Centre for Artificial Intelligence (DFKI) is responsible for implementing the robotics use case. The aim is to apply the developed FDO technology to real research data from robotic systems. For this purpose, a specific FDO profile for robotics data is created and applied to data sets from field experiments. These are converted, published in a structured manner and integrated into a domain-specific database. In addition, DFKI is developing software components that enable automated data exchange between the FDO architecture and robotics databases. The accompanying documentation of the methods and results promotes transferability to other scenarios within robotics and beyond.