The universities and non-university institutions participating in NFDIxCS, including the German Society of Informatics (GI), are spread over 16 locations in Germany. The University of Bayreuth will focus its research contributions primarily on the topics of “Semantic Aspects” and “Metadata and Protocols”, which complement each other very well. In particular, metadata schemes are to be developed to make information, software and other artefacts easier to find and reuse. Of central importance for the joint work in the NFDIxCS network are the FAIR principles: Scientific data should be findable, accessible, interoperable and re-usable. “In our network, we want to work towards the full implementation of the FAIR principles in the field of Computer Science. Reusable data objects should not only contain subject-specific data from Computer Science and the associated metadata, but also include, for example, more general data relevant for the technical processing and application of information,” says Prof. Dr. Agnes Koschmider.
The research work in the new alliance is designed from the outset for interdisciplinary networking: Computer Science, together with other scientific disciplines, is to advance the application of innovative methods and technologies in the fields of Big Data, Artificial Intelligence and Machine Learning. In addition, other disciplines should be able to benefit from the expertise and subject-specific experience of the "Computer Science community" – for example, with regard to scientific publication and communication systems, system architectures or standards for the compatibility of research data.
The overall objective of NFDIxCS is to build an organizational and technical infrastructure that bundles the already existing services in the field of scientific data management for Computer Science and further develops them with sustainability in mind. “In all activities within our network, we want to support young researchers and strengthen the competences in the society as a whole for a methodically reflective handling of research data. In this respect, NFDIxCS will also initiate required cultural changes so that we can responsibly exploit the great opportunities of digitization and machine learning,” says Koschmider.
Further information on NFDIxCS:
National Research Data Infrastructure for and with Computer Science
https://nfdixcs.org/
