Research
Research focus and projects in the field of Data Science & Digital Libraries
The research group Data Science & Digital Libraries develops methods and techniques for the semantic networking of data, information and knowledge and implements them in technologies and services for the different user groups of the TIB.
The research group deals in particular with the following topics:
- Semantic Technologies and Linked Data, Knowledge Representation and Knowledge Management
- Digitisation of society, science and business, data spaces, data value chains
- Big Data, Internet of Things, Data Integration for Industry 4.0
- E-Science, Science Governance, Peer Review, Open Access, Digital Libraries
Application domains are Digital Libraries, Enterprise Data Integration, Industry 4.0, Smart Cities, Digital Humanities.
The extensive and heterogeneous TIB database offers a wide range of application and transfer possibilities for these research projects. The research topics are closely related to TIB services and products.
Projects
- ScienceGraph (05/2019-04/2024)
- CoyPu - Cognitive Economy Intelligence Plattform für die Resilienz wirtschaftlicher Ökosysteme (Laufzeit 10/2021-09/2024)
- NFDI4DataScience National Research Data Infrastructure for Data Science and Artificial Intelligence (Laufzeit 10/2021-09/2026)
- NFDI4Ing – the National Research Data Infrastructure for Engineering Sciences
- CRC 1153 Process chain for the production of hybrid high-performance components through tailored forming
- CRC 1368: Oxygen-free production
- STREAM - Semantic representation, networking and curation of quality-assured material data (08/2019-07/2022)
Open Research Knowledge Graph
The research group develops and operates the Open Research Knowledge Graph (ORKG) service. With the ORKG, we address central challenges of the digitisation of research, such as publication overload, reproducibility crisis and deteriorating peer review. The ORKG enables the semantic, machine- and human-readable description of research contributions in a knowledge graph according to the FAIR principles. As a result, overviews of the state of research on important research problems and comprehensive, partially automated evaluations and analyses of the state of research can be easily realised.
Joint Lab Data Science & Open Knowledge
Some of the research on these topics takes place within the framework of the Joint Lab Data Science & Open Knowledge.
The Joint Lab will be established together with Leibniz Universität Hannover (LUH), the Faculty of Electrical Engineering and Computer Science and the L3S Research Center of LUH.
