FAIR-DI e.V.
FAIRmat
NOMAD Laboratory
NOMAD CoE

FAIRmat Proposal

FAIRmat will continue to raise awareness & acceptance of a FAIR research-data infrastructure in Germany, Europe, and beyond.

Abstract

Scientific data are a significant raw material of the 21st century. To exploit their value, a FAIR Findable, Accessible, Interoperable, and Re-purposable – data infrastructure (DI) is a must. Making data Findable and AI Ready (an alternative interpretation of the acronym) will change the way how science is done today. For the wider field of condensed-matter physics and the chemical physics of solids, FAIRmat sets out to make this happen. Integrating synthesis, experiment, theory, computations, and applications, it will substantially further the basic physical sciences, reaching out to chemistry, engineering, industry, and society.

Why are FAIRmat’s research data so important? Simply speaking, the prosperity and lifestyle of our society are very much governed by achievements of this field as new products from the energy, environment, health, mobility, IT sectors, etc. very much rely on improved or even novel materials. Examples are solid-state lighting, touch screens, batteries, implants, and many more. Boosted by the US Materials Genome Initiative (MGI), an enormous amount of data on materials (basic and applied science and engineering) has been produced in recent years. These data are largely kept on local servers, but their characterization is typically incomplete. Without an efficient DI, the data are neither easily accessible nor re-usable.

In this NFDI project, FAIRmat will 

  • create a federated FAIR DI for materials data with a central hub, the FAIRmat Portal;
  • advance and develop metadata schemas and ontologies;
  • enable efficient exchange of the FAIR research data, ensuring that the FAIRmat DI will advance basic science of condensed-matter and materials physics with very little burden for active researchers and also be of great value for engineering;
  • convince scientists to also share data they consider useless for their present purpose-oriented research;
  • reach out within and beyond its community providing advice, training, and user support.

FAIRmat represents a broad community of numerous researchers from universities and leading institutions in Germany. It builds on extensive experience with the worldwide biggest data infrastructure in computational materials science, the Novel Materials Discovery (NOMAD) Laboratory and the association FAIR-DI e.V. FAIRmat aims at covering the full breadth of the Condensed Matter Section of the German Physical Society (DPG) with its 12 divisions, and is further supported by the Chemistry, Physics, and Technology Section of the Max Planck Society, the Bunsen Society for Physical Chemistry, and more. FAIRmat is fully embedded internationally, e.g., in the Research Data Alliance, the European Open Science Cloud, GO FAIR, etc. and has signed Memoranda of Understanding with leading institutions worldwide, for example NIST (USA), Shanghai University (China), and CSC (Finland). FAIRmat will continue to raise awareness and acceptance of a FAIR research-data infrastructure in Germany, Europe, and beyond.


FAIRmat's Structure

Below are the objectives of FAIRmat's Areas.
An overview of all Areas, Tasks, and their leaders can be found here: FAIRmat's structure.