Geo Data Space Germany is a national geodata space developed by the data analytics institute (dai) and Fraunhofer ISST. It consolidates and harmonizes all relevant geodata—from 3D building data and road networks to cadastral information—into a unified model. This data serves as a foundational infrastructure to support domain-specific data spaces, such as those for the energy sector or disaster management.
In the BoostEDIC M&L project, we are supporting the establishment of a common European data infrastructure for the mobility and logistics sector. The aim of the four-year project is to further develop the European Mobility Data Space (EMDS) and establish a European Digital Infrastructure Consortium (EDIC). We are developing a knowledge hub as a central knowledge platform and drawing up recommendations for interoperable data spaces that enable cross-border data exchange throughout Europe.
The NGDI project is developing the technological and organizational foundations for the next generation of European data spaces. The goal is to enable interoperability between domain-specific data spaces, thereby promoting innovative, cross-industry business models. With the help of semantic web technologies, large language models, and distributed persistent identifier systems, barriers to entry for companies are lowered, enabling sovereign, secure data usage across sector boundaries.
The project optimizes the onboarding of SME as data providers in the Mobility Data Space (MDS) by establishing a data trustee. The focus is on SME in logistics, especially those involved in first- and middle-mile logistics. Standardized interfaces, clear minimum requirements, and a secure data trustee model reduce technical and organizational hurdles and pave the way for data-driven applications.
On behalf of the German Energy Agency (dena), the test field consortium, led by Fraunhofer IEE, is designing and implementing the two defined use cases for energy in a data space. In addition to industry dialogue and knowledge transfer, the test field is a component of the overall project being carried out by dena on behalf of the US Department of Energy (DOE). The focus is on operational data exchange, which is essential for the smart integration of decentralized annexes such as photovoltaics, heat pumps, and charging infrastructures for electric cars. The goal is to network, process, and make available high-quality energy data across sectors in order to drive forward the energy transition.
The aim of the DEPLOYTOUR project is to establish a European Tourism Data Space (ETDS). By providing a trustworthy data space architecture based on guidelines and rules, the exchange of data between actors in the tourism sector is to be promoted in order to create sustainable and innovative developments. Due to the dependence of the tourism sector on other sectors, the ETDS is intended to function as a comprehensive, interoperable data space.
The project aims to further develop existing approaches to data sharing and to promote the intersectoral exchange of geodata. To this end, an optimized data trust model is being developed that makes geodata available for different domains.
As direct business relationships evolve into value creation networks, complex ecosystems with a large number of dynamically changing participants emerge. The participants in the ecosystems have different technical and business dependencies on each other, which, combined with the dynamics, result in a high level of complexity. In this context, data spaces, i.e. multi-sided technological platforms, enable the cross-organizational sharing of data.
The “FDOOne - FAIR Digital Object One” project is all about networking data spaces according to a basic standard that fulfills the FAIR principles. The acronym FAIR stands for Findable, Accessible, Interoperable and Reusable. This approach aims to bring together the highly fragmented digital space of all digital objects. In order to achieve this goal, three project priorities have been agreed: 1. the networking of data spaces, focusing on the transfer of data into secure, trustworthy artificial intelligence (AI) applications, 2. strengthening trust in AI, which primarily includes reproducibility, 3. strengthening the AI ecosystem, in particular by defining and improving framework conditions for companies.
In the “MDSxNRW” project, we are developing and testing an intelligent recommendation engine that recommends a suitable connector for organizations to participate in the Mobility Data Space (MDS). This recommendation is based on company-specific information that is requested in a questionnaire. Based on the user information, detailed instructions for connecting to the MDS are then provided and options for automated connection to the MDS are recommended.
The Opt-In project brings data sovereignty to the world of the "smart home". The focus is on the requirements and needs of citizens to make free decisions about their data. Individuals are empowered to retain control over their data and at the same time encouraged to enable innovative services with their data.
The goal of the project "BuildingTrust" is to develop a modular data trustee for building data that motivates users to provide, maintain and anonymously share (personal) data. The goal is to optimize and accelerate sustainable building through a self-determined data trustee that generates added value for data givers and data takers and creates trust for sharing data.
In the "ScaleDTM" project, we are developing the technical building blocks for realizing decentralized data trustee models. The goal of this two-year individual project is to create a competitive, scalable, and easily extensible data fiduciary architecture to promote collaborative data processing and value creation. Here, we consider not only the exchange of data, but also the fiduciary execution of code as a service provided by the data trustee.
The supply chain law or the monitoring of a CO2 footprint are only two current challenges of the automotive industry. They require cross-company data usage so that end-to-end value chains emerge. In the Catena-X project, an ecosystem for the entire automotive sector is being established, which will be set up in a highly scalable manner from the very beginning. The core element of the network is a shared offering of federated data and services that enables companies to shorten the "time-to-market" of innovative solutions, use resources more efficiently, and increase the transparency and resilience of value creation processes.
"Data governance" in the data ecosystem of the Smart City Solingen. In the "MobiDataSol" project, a data trust model is being developed and tested that enables cross-organizational data exchange as the basis of a data ecosystem to be established in the context of the Smart City at the municipal level. Based on the analysis of the interests and needs of the various actors at the municipal level, a data trust model will be developed and tested in the application area of mobility and environmental data. The project is being carried out by the city of Solingen together with the Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e. V. - represented by the Fraunhofer Institute for Industrial Engineering IAO and the Fraunhofer Institute for Software and Systems Engineering ISST - as well as the University of Stuttgart and the Institute for Energy and Environmental Research (ifeu).
Bauhaus.MobilityLab Erfurt aims to develop an open, service-oriented ecosystem to more effectively link the energy, transport, mobility, environment, and logistics sectors. The core of BML-EcoSys is a high-performance laboratory platform for the providers and users of new (mobile) services to interact from the outset, jointly developing and testing innovative solutions using AI applications.
Industrial data storage and use is becoming more and more important in increasingly digitizing processes. For example, a company-specific approach to centralized and decentralized data management must be found and operational responsibilities must be clearly defined. A functioning data management system is of strategic importance for business processes such as customer service.
In the project "GAIA-X 4 KI" we focus on the development of a Gaia-X-based digital ecosystem for training and validation of AI applications in the automotive domain. The goal of the three-year project is to map relevant automotive applications in a federated system architecture and, based on the results of the project and the developments in Gaia-X, to build a digital ecosystem that will serve as the basis for further projects in the GAIA-X 4 Future Mobility project family.
The potential for optimizing processes with a view to increasing efficiency or for digital services and new business areas is virtually inexhaustible. However, logistics in Germany will only be able to defend or expand its global market leadership if the potential is tapped.
Fraunhofer Institute for Software and Systems Engineering
