Lifting the treasure trove of materials data
The FAIRmat consortium, led by Claudia Draxl, Professor at the Humboldt-Universität zu Berlin, is one of the projects selected today by the Joint Science Conference (GWK) in a multi-stage competition for the National Research Data Infrastructure (NFDI). The project will receive funding to set up an infrastructure that helps making materials-science data FAIR: Findable, Accessible, Interoperable, and Reusable. This will enable researchers in Germany and beyond to store, share, find, and analyze data over the long term. During the five-year term, a total of 60 PIs from 34 German institutions including the MPI for Polymer Research will work together in the FAIRmat consortium.
Prosperity and lifestyle of our society are very much governed by achievements of condensed-matter physics, chemistry, and materials science, because new products for the energy, environment, health, mobility, and IT sectors, for example, largely rely on improved or even novel materials. The enormous amounts of research data produced every day in this field, therefore, represent the treasure trove of the 21stcentury. This treasure trove is, however, of little value, if these data are not comprehensively characterized and made available. How can we refine this feedstock, in other words, turn data into knowledge and value? For this, a FAIR data infrastructure is a must.
Here is where FAIRmat (“FAIR Data Infrastructure for Condensed-Matter Physics and the Chemical Physics of Solids”) comes in. By building a FAIR research-data infrastructure for the noted fields, the consortium will lift the treasure trove of materials data, and therewith contribute to a disruptive change in the way science and R&D are conducted. It will help the active researches without creating unnecessary bureaucratic burdens. In addition to HU Berlin, the Leibniz-Institut für Kristallzüchtung (IKZ), the Max Planck Institute for Chemical Energy Conversion (MPI CEC), the Fritz Haber Institute of the Max Planck Society (FHI), the Technical University of Munich (TUM), the Karlsruhe Institute of Technology (KIT), and the association FAIR-DI e.V. are involved in the project as co-applicants. Kurt Kremer, director at MPI-P, and Tristan Bereau, former group leader, are involved as deputy leaders in the area of "Theory and Computation".
FAIRmat Deputy Spokesperson Matthias Scheffler from the Fritz Haber Institute of the Max Planck Society explains: “We interpret the acronym FAIR in a forward-looking way: Research data should be Findable and Artificial-Intelligence Ready. This new perspective will advance scientific culture and practice. These envisaged changes will advance the scientific culture and practices. They will not replace scientists, but scientists who use such FAIR infrastructure may replace those who don't."
FAIRmat is a consortium of the National Research Data Infrastructure (NFDI). The NFDI is a nationwide network that is currently being established and funded with up to 90 million EUR per year from 2019 to 2028 by Germany’s federal and state governments to systematically manage scientific and research data.
FAIRmat covers a wide range of research fields in physics and related areas, consequently, basic concepts and measuring techniques, working style, and research data are extremely diverse and heterogeneous. This renders the need for a FAIR data infrastructure as extremely pressing. FAIRmat promotes the efficient sharing of research data (sharing is caring!) and its preparation for reuse and analysis by Artificial Intelligence (AI) tools, enabling a new level, a new quality of science.
For this, FAIRmat follows a bottom-up approach, which is oriented towards the needs of scientists. The consortium is already receiving great support from the community, being well integrated into the Condensed Matter Section of the German Physical Society, the Max Planck Society (e.g., Big-Data Network, CPTS), a large number of universities and institutes as well as various international activities (for example RDA, GO FAIR, EOSC). FAIRmat is based on Claudia Draxl’s and Matthias Scheffler's extensive experience with the world's largest computational materials science data infrastructure, the Novel Materials Discovery (NOMAD) Laboratory, which is online since 2014.
“Naturally, we are now looking for highly motivated researchers from domain sciences and IT who share the enthusiasm for a paradigm shift in the fundamental materials science to strengthen our team and realize the FAIRmat principles together with us”, says Claudia Draxl. You can watch her welcoming video here: https://www.fair-di.eu/fairmat