Eight NFDI Consortia with RWTH Participation Receive Financing
The Joint Science Conference (GWK) has approved funding for ten consortia to establish a National Research Data Infrastructure (NFDI), including eight with participation from RWTH Aachen University.
In science, professional digital research management is becoming increasingly important. For this reason, standards in data management are currently being established for the entire German science system within the National Research Data Infrastructure (NFDI).
A digital, regionally distributed and interconnected scientific repository of research data will be set up to provide long-term data storage, backup and accessibility in the long term. The NFDI will be developed by users of research data and by infrastructure institutions working together in consortia.
The following eight consortia with RWTH participation were selected to receive funding:
- NFDI-MatWerk (National Research Data Infrastructure for Materials Science & Engineering): This consortium has a focus on materials science and materials engineering. This research field is highly interdisciplinary, combining physics, chemistry, mechanics, and electrical engineering.
- NFDI4Earth: Among other topics, this consortium is concerned with planetary evolution and its influence on climate change research. It is dedicated to meeting the digital needs of researchers in Earth system science.
- NFDI4Microbiota: This consortium addresses microbiomes such as bacteria, viruses, and biomass, and seeks to democratize cross-cutting data access to microbiota data. Microbiota, individual microbial species, and viruses have a powerful impact on many aspects of human life, from individual health to climate change. In the face of broader global issues, understanding of ecosystems must improve in order to effectively address any challenges posed by human activities. The current COVID-19 pandemic serves as an example, demonstrating how viral infection can impact all aspects of human life.
- DAPHNE4NFDI (Data from Photon and Neuron Experiments): This consortium aims to improve collaborations between research centers and users. Access to state-of-the-art analytical instruments is provided by publicly funded X-ray and neutron facilities. This makes it possible to advance research in a wide range of scientific disciplines such as medicine, physics, biology, chemistry, engineering, materials science, and cultural heritage.
- PUNCH4NFDI (Particles, Universe, Nuclei and Hadrons for the NFDI): This consortium was formed from two formerly separate consortia, PAHN-PaN and ASTRO@NFFDI, after in-depth discussions on common and complementary strengths. It addresses the fields of particle, astro and nuclear physics in the context of major international projects. The goal of PUNCH4NFDI is to build a decentralized, cross-community scientific data platform following FAIR data principles and to integrate it into the NFDI.
- NFDI4DataScience: this consortium aims to establish a community-driven research data infrastructure for the data science and artificial intelligence community within computer science. To advance the state of the art in several areas, including natural language processing, machine learning, and information retrieval, data has become key, especially in the area of artificial intelligence and the growth of deep and transfer learning.
- MaRDI (Mathematical Research Data Initiative): This consortium aims to implement the FAIR data principles across the entire field of mathematics and its applications. Mathematical research data is now vast and complex, thanks to the rapid unfolding of mathematics in data science and the ever-increasing power of computers. In addition, the successful application of mathematics in interdisciplinary research has made the data very diverse and widespread in the scientific community.
- FAIRmat (FAIR Data Infrastructure for Condensed-Matter Physics and the Chemical Physics of Solids): This consortium focuses on materials science research. It represents an open science approach in materials science, striving to make all data freely available. FAIRmat represents the interests of experimental and theoretical condensed matter physics. This also includes, for example, the chemical physics of solids, synthesis, and high-performance computing.