FAIRmat: A Treasure Box of Material Data
FAU is involved with two projects in the FAIRmat project, which was approved on Friday, 2 July 2021 by the Joint Science Conference (GWK) in a multi-stage competition of the National Research Data Infrastructure (NFDI). The project will receive funding to build an infrastructure that makes it possible to make materials science data FAIR: findable, accessible, interoperable and re-purposable. This will enable researchers in Germany and beyond to store, share, find and analyse data over the long term. During the five-year term, a total of 60 project leaders from 34 German institutions will work together in the FAIRmat consortium.
The findings from condensed matter physics, chemistry and materials science have a decisive impact on the wealth and lifestyle of our society: new products and goods in the fields of energy, environment, health, mobility and IT depend on improved or even novel materials. The enormous amounts of research data produced daily in these scientific fields are therefore a treasure of the 21st century. However, this treasure is worth little if the data is not comprehensively described and made available. How can we refine this raw material, i.e. turn the data into knowledge and value? For this, a FAIR data infrastructure is a must.
This is where FAIRmat (“FAIR Data Infrastructure for Condensed-Matter Physics and the Chemical Physics of Solids”) comes in. By setting up a FAIR research data infrastructure for the above-mentioned fields, the consortium aims to recover the treasure of material data and thus contribute to a fundamental change in science and research. FAIRmat’s deputy spokesperson Matthias Scheffler from the Fritz Haber Institute of the Max Planck Society explains: “We interpret the acronym FAIR in a future-oriented way: Research data should be discoverable (Findable) and ready for Artificial Intelligence (Artificial-Intelligence Ready). This new perspective will advance scientific culture and practice. It will not replace scientists – but researchers who use such a FAIR infrastructure can replace those who don’t.”
FAU is active in the FAIRmat consortium with two projects. Prof. Heiko B. Weber and Dr. Michael Krieger from the Department of Applied Physics, together with Heinz Junkes from the Fritz Haber Institute in Berlin, are developing a universal and easy-to-configure software environment for measurement data acquisition and documentation. “In our field of research, measurement set-ups with numerous special measurement devices are often required – each adapted to the experimental problem,” explains Prof. Weber. “This diversity requires adaptable and easy-to-configure software for experiment control and data acquisition.” But it’s not just about the raw data. The experiment description including all settings of the laboratory equipment used, the so-called metadata, is also necessary. This is the only way to document the experiment completely and FAIR, and the valuable measurement data can also be used by other scientists. “We have already been using prototype software for experiment control with uniform and documented data output developed by us for years,” says Dr Krieger. “In the FAIRmat project, we will bring this successful concept together with the open-source Experimental Physics and Industrial Control System (EPICS), which will take over the recording of data and metadata, storage, archiving and provision of research data in accordance with the standards to be developed in FAIRmat.”
In the second sub-project at FAU, Prof. Christoph Brabec from the Chair of Materials Science, who also heads high-throughput photovoltaic research at the Helmholtz Institute Erlangen – Nuremberg as Director of the Jülich Research Centre, will test, apply and further develop FAIRmat data collection in the field of semiconductors for optoelectronic applications in practice together with Dr. Thomas Unold from the Helmholtz Zentrum Berlin. Prof. Brabec: “The goal is to build up a material encyclopaedia by means of automated and, in future, autonomous laboratories. With the help of the FAIR principle in data and metadata processing, optimisation algorithms of machine learning can directly access the data and suggest and also execute new experiments or tests in real time. Using optoelectronics as an example, the aim is to discover and research highly efficient, cost-effective and non-toxic semiconductors with optimal properties for devices and systems for the generation and conversion of renewable energy.”
The FAIRmat consortium is part of the National Research Data Infrastructure (NFDI). The NFDI is a nationwide network currently being set up and funded by the federal and state governments with up to 90 million euros per year from 2019 to 2028 to systematically manage research data.
FAIRmat covers a broad spectrum of research areas in physics and related fields, and the basic concepts and measurement techniques, working methods and research data are correspondingly diverse and heterogeneous. Here, the need for a FAIR data infrastructure is extremely urgent. FAIRmat promotes the efficient sharing of research data (sharing is caring!) and its preparation for reuse and analysis by artificial intelligence (AI) tools. In this way, FAIRmat enables a new level and quality of science.
In doing so, the consortium is pursuing a bottom-up approach that is oriented towards the needs of scientists and is already receiving great support from the community. For example, FAIRmat is just as well integrated into the Condensed Matter Section of the German Physical Society as it is into the Max Planck Society (e.g. Big Data Network, CPTS), and into a large number of universities and institutes as well as international activities.
“Of course, we are now looking for highly motivated scientists from domain sciences and IT who share our enthusiasm for a paradigm shift in fundamental materials science to join our team and realise the FAIRmat principles together,” says FAIRmat’s spokesperson Claudia Draxl.
To learn more about FAIRmat, visit https://www.fair-di.eu/fairmat
To become part of the FAIRmat team, visit: https://nomad-lab.eu/career To learn more about the NFDI, visit ww.dfg.de/nfdi