FAIRmat - A Proposed Consortium of the German Research-Data Infrastructure (NFDI)
Spokesperson: Claudia Draxl (Humboldt-Universität zu Berlin)
Deputy: Matthias Scheffler (FHI Berlin)
PARTICIPATION IN THE NFDI
Recommended by the Council for Information Infrastructures (RfII), an urgently needed sustainable infrastructure for provision, interlinkage, maintenance, and options for reuse of research data shall be created in Germany in the coming years. The needs and implementation of this National Research Data Infrastructure (NFDI), will be defined and realized by consortia from a wide variety of scientific disciplines.
The consortium FAIRmat represents the interests of experimental, theoretical, and computational condensed-matter physics and materials science. This also includes, for example, chemical physics of solids, catalysis, functional materials, synthesis, and more. For the structure of the consortium see here. As a first step, an Extended Abstract was submitted to the DFG on March 29, 2019. The binding Letter of Intent was submitted on July 4, 2019. The proposal was successfully submitted on October 15, 2019. In December 2019, the NFDI Evaluation Colloquium took place.
As a next step in the application process, the consortia will be notified of review results and will be given an opportunity to respond in January 2020.
BECOME A PART OF FAIRMAT
Colleagues are invited to contribute their expertise and actively shape the necessary data infrastructures. If you would like to become part of FAIRmat, please register here. This list and this map of Germany shows you our supporting institutions and their location throughout Germany. Listed are the institutions of active participants (blue), as well as the institutions (red), computing and data centers (dark red), and joint research projects (green), which have confirmed their support or cooparation through a statement of their director or president. The area for registered users is here.
Our approach and most important principle is to design the infrastructure of this field from bottom up and without bureaucratic hurdles. To this end, we will involve our colleagues in order to implement their needs make research studies more efficient, and to achieve a comprehensive acceptance of the project. The aim of FAIRmat is to improve, expand, and interlink existing infrastructures for the further development of these scientific disciplines and - where necessary - to create new infrastructures. Cooperation between universities and other research institutions as well as industry shall be strengthened.
FAIRmat, representing the materials science pillars of the association FAIR-DI (FAIR Data Infrastructure for Physics, Chemistry, Materials Science, and Astronomy e.V.), has already extensive practical experience and also follows FAIR-DI's mission statement:
Scientific data are a significant raw material of the 21st century. To exploit its value, a proper infrastructure that makes it Findable, Accessible, Interoperable, and Re-purposable – FAIR – is a must. For the fields of computational and experimental materials science, chemistry, and astronomy, FAIRDI sets out to make this happen. This enabling of extensive data sharing and collaborations in data-driven sciences (including artificial intelligence tools) will advance basic science and engineering, reaching out to industry and society.
FAIRmat covers the following areas:
- AREA A: Synthesis - Martin Albrecht (Leibniz Institute for Crystal Growth Berlin) & Claudia Felser (Max Planck Institute for Chemical Physics of Solids)
- AREA B: Experimental Materials Science - Mark Greiner (Max Planck Institute for Chemical Energy Conversion) & Christoph Koch (Humboldt-Universität zu Berlin)
- AREA C: Computational Materials Science - Matthias Scheffler (Fritz-Haber-Institut) & Kurt Kremer (Max Planck Institute for Polymer research) / Tristan Bereau (Max Planck Institute for Polymer Research)
- AREA D: Digital Infrastructure - Hans-Joachim Bungartz (Technical University of Munich) & Wolfgang Nagel (Centre for Information Services and High Performance Computing (ZIH))
- AREA E: Use Case Demonstrators - Christof Wöll (Karlsruhe Institute of Technology) & Axel Groß (Ulm University)
- AREA F: User Support, Training & Outreach - Matthias Scheffler (FAIR-DI e.V. ) & Martin Aeschlimann (TU Kaiserslautern)
- AREA G: Administration & Coordination - Claudia Draxl & Matthias Scheffler (both FAIR-DI e.V.)