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 the cooperative AI is that it should be possible for users without knowledge in the field of artificial intelligence (AI) 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 to provide explanation components and to create 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).

Learn more about KompAKI »

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.

To learn more about the FROCKG project visit the project website »

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 (1) companies (in domains including Industry 4.0, bio-medicine, finance, law) of all sizes and even (2) 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: (F1) representation, (F2) construction and maintenance, (F3) operation and (F4) 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.

To learn more about the KnowGraphs project visit the project website »

Visit the project website for a complete partner list »

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.

To learn more about the Diesel project please visit the project website »

DIESEL partners contribute new dataset to QALD2017 challenge »