Driving research & innovation

Read all about our groundbreaking research projects below »

Current research projects


KIRA: AI methods for optimized control of electric traction drives

The market for electrically powered vehicles is steadily growing and will play a central role in reaching climate neutrality. However, the limited range of electric vehicles remains a major obstacle for many customers. In addition to the use of increasingly large, resource-intensive batteries, the efficient use of the available energy is an alternative way to increase this range.

The KIRA project aims to improve the operation of electric traction drives through the use of AI-based methods. To this end, the project consortium is working towards developing innovative control and activation concepts that will lead to an increase in efficiency, an increase in power density, a reduction in noise development, and an increase in torque accuracy.

As part of the KIRA project, metaphacts will focus on the formal representation of domain-specific knowledge using knowledge graphs for improved model building. Knowledge graphs allow for explicit knowledge representation at a conceptual level and provide the basis for the development of components needed to deliver explainable AI. metaphacts develops hybrid approaches for the integration of ML-based methodologies with knowledge representation.

This project is funded by the German Federal Ministry of Economics and Technology (BMWi).

IIDI - Intelligent information services for domain-specific Web portals

Obtaining relevant information on technological and market developments quickly and in a targeted manner is becoming an increasingly important success factor for companies and their technology and innovation management (TIM). However, dynamic technological change coupled with an exponentially growing flood of information is presenting companies with major challenges. For example, employees in most innovation-related jobs spend five to ten hours a week researching relevant information.


The main goal of the IIDI research project is to develop specialized, reusable and extensible functional digital services that can be modularly orchestrated as needed and can support, e.g., data aggregation, preprocessing, or semantic text analysis. These information services will be enriched with ML processes and can integrated into Web portals to deliver relevant information to end users in a timely manner. As an application area, the IIDI research project will focus on the domain of hydrogen technology for smart city portals.


metaphacts has a leading role in the IIDI project as a technology and integration partner. The metaphactory platform is central to the overall architecture of the solution to be developed and piloted.


This project is funded by the German Federal Ministry of Education and Research (BMBF).


KompAKI: Competence center for work and artificial intelligence

Artificial Intelligence (AI) is increasingly being used in software applications and has the potential to revolutionize the way we work. However, research regarding the impact of new technology on the workplace is often performed after said technology has already been developed and implemented. In KompAKI (Kompetenzzentrum für Arbeit und künstliche Intelligenz im Rhein-Main-Gebiet), the research consortium is researching new potential for human-centered AI applications and their business models.

The knowledge gained at the Competence Center will be validated in pilot projects with partner companies mainly from the production sector. All project results will be made available to the regional working world and university education through various information and transfer formats during the project period.

metaphacts is involved in central issues within the joint project, focusing on "cooperative artificial intelligence". The main characteristics of cooperative AI is that it should be possible for users without knowledge in the field of artificial intelligence to train learning systems ("Automated AI"), but also that learning systems can explain themselves ("Explainable AI") and adapt through interaction with the user ("Interactive AI"). Specifically, metaphacts' goal is to develop methods for cooperative AI using knowledge graphs that provide explanation components and support the creation of new interfaces for non-expert users to interact with knowledge-based intelligent systems.

This project is funded by the German Federal Ministry of Education and Research (BMBF).


FROCKG: Fact checking for large enterprise Knowledge Graphs

Enterprise Knowledge Graphs underpin business-critical decisions, thereby influencing financial markets, the economic environment, and many more aspects of our lives. Determining the veracity of the facts in these Enterprise Knowledge Graphs is hence mission-critical. Together with partners from industry and academia, in FROCKG we aim at building a framework to enable companies to ensure they are basing business decisions on reliable and true data. For this, we are developing accurate and time-efficient approaches to quantify and provide evidence for how true or untrue facts in Enterprise Knowledge Graphs are likely to be. A prototype of this framework will be integrated in commercial solutions and deployed in three use cases: finances, cultural heritage and linked open data.

This project is funded by the German Federal Ministry of Education and Research and the Eurostars EU project.


Knowgraphs: Building scalable Knowledge Graphs

metaphacts is an associated partner in the KnowGraphs research project. The main goal of KnowGraphs is to scale Knowledge Graphs to be accessible to a wide audience of users across multiple domains including companies of all sizes in domains such as Industry 4.0, bio-medicine, finance, law, as well as end users (e.g., through personal assistants and web search). Addressing this goal demands a mix of works from the theoretical foundations to the exploitation and economic repercussions of Knowledge Graphs.

KnowGraphs focuses on addressing four of the facets of Knowledge Graph management: representation, construction and maintenance, operation and exploitation. The project will address these pillars by researching and developing novel methods, models and frameworks using a cross-disciplinary mix of methods from Web Science, Data Science, Knowledge Representation, Knowledge Engineering, Big Data, data law, and business innovation. The results will be applied across sectors, i.e., in domains including personalized medicine, Industry 4.0, question answering, personal assistants and Web search.

This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 860801.

Past research projects


Diesel: Distributed search in large enterprise data

DIESEL, a project run by metaphacts in collaboration with Zazuko and AKSW and funded by EUROSTARS-2 / EUREKA, aims at leveraging the advantages of Linked Data technologies to design and deliver a scalable semantic search engine for large enterprises.

The system will help enterprises connect, understand and find the information they need within a short time, by integrating and querying disparate data sources as a service. Using rich interfaces, the system will capture end-user information needs and allow users to extend their results with similar concepts. The results of these global searches will be displayed as comprehensive, targeted answers.

The aim of the research project is to reduce the time needed for global searches in the enterprise and enhance efficiency, reduce costs and improve the decision making process by reducing information noise and overload.


Geiser: From sensor data to internet-based geo services

GEISER is a collaboration project funded by the German Federal Ministry for Economic Affairs and Energy (BMWi) as part of the Smart Service World innovation program. Together with partners from industry and academia, in GEISER we're building an open, service-based cloud platform for the acquisition, transformation, storage, integration, quality assurance, and efficient processing of sensor based geo data. Use cases addressed in the project include data-driven geomarketing for small and medium-sized businesses and retailers, smart routing services, technician operational planning, and smart search for parking spaces. As a consortium member, metaphacts will focus on designing and implementing scalable backend services for the storage, retrieval, and processing of semantic geo data, by combining state-of-the-art semantic data management with Big Data technologies for scale-out and GPU acceleration.

To learn more about the Geiser project download our project brochure (available in German only).

To learn more about data-driven geomarketing please visit our use case page »

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