Through implementing AI use cases, we are progressively identifying and addressing the challenges of connecting various data spaces, including established ones like the Mobility Data Space as well as those still in development. Specifically, key technological standards and tools to enhance the integration and robustness of these data spaces are being developed and tested in the project.
This funding project aims to demonstrate the potential of FAIR Digital Objects (FDOs) for data exchange between different dataspaces and aims to establish flexible and secure standards for data exchange.
It uses the Eclipse Dataspace Connector (EDC) and brings together expertise from organisations such as the GWDG, IndiScale, Fraunhofer companies, RWTH Aachen University and the German Institute for Standardisation.
MISSION KI is cooperating with the Berlin-based AI start-up Xayn to enable the secure and legally compliant exchange of data between companies in data rooms. Together, they are developing an AI solution that automatically checks whether all EU compliance regulations and industry-specific requirements are adhered to when sharing data.
The system is intended to make it easier for companies to exchange data and thus create the basis for the development of new AI applications. By expanding the available database, learning systems can be optimised and their performance improved. Allianz is supporting the project with data sets and expertise.
Users want to easily find relevant data for AI applications and assess its quality. However, the lack of a search engine spanning across data spaces, data portals, or other data ecosystems poses a challenge for cross-organizational data exchange.
The project develops services for automated creation of standardized, meaningful dataset profiles (EDPS = "Extended Dataset Profile Service") and a publicly accessible, curated search engine ("Landing Page") for existing public and private data spaces and portals. Based on the created profiles, the latter enables quick search and assessment of data quality and usability - both within and across data spaces. Together, the profiles and search engine strengthen the portability of AI training data, promote interoperability between data sources, and create more transparency.
This facilitates the use of data-driven applications and supports compliance with data quality standards. This project is being conducted jointly with project partners beebucket GmbH, nexyo AG, eXXcellent solutions GmbH, and deltaDAO AG, and runs from September 2024 to March 2025.
In this way, we are driving forward the development of a comprehensive data ecosystem and strengthening the basis for the digital competitiveness of the German economy. Small and medium-sized enterprises in particular can benefit from sovereign data exchange in data spaces by gaining access to new data sources and collaborations that are crucial for the development of data- and AI-based business models. With the aim of European connectivity, we work closely with European and international initiatives such as the Data Spaces Support Centre (DSSC) and the International Data Spaces Association (IDSA).
