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NOMAD: The FAIR concept for big data-driven materials science

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Abstract

Data are a crucial raw material of this century. The amount of data that have been created in materials science thus far and that continues to be created every day is immense. Without a proper infrastructure that allows for collecting and sharing data, the envisioned success of big data-driven materials science will be hampered. For the field of computational materials science, the NOMAD (Novel Materials Discovery) Center of Excellence (CoE) has changed the scientific culture toward comprehensive and findable, accessible, interoperable, and reusable (FAIR) data, opening new avenues for mining materials science big data. Novel data-analytics concepts and tools turn data into knowledge and help in the prediction of new materials and in the identification of new properties of already known materials.

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Notes

  1. *We note that accessibility in this context not only concerns the data itself, but largely also the hardware at which it is stored, as well as details of the data infrastructure.

  2. †The concept of the NOMAD Repository and Archive was developed in 2014, independently and parallel to the “FAIR Guiding Principles.”10 Interestingly, the substance is practically identical.

  3. ‡The understanding of “interoperable” is somewhat controversial. It may apply when (1) metadata and data use a formal, accessible, shared, and widely accepted language for data representation; (2) the vocabulary of metadata and data follow FAIR principles; (3) metadata and data include qualified references to other (meta) data and to the authors who created the results.

  4. §In the NOMAD CoE, we use the term repurposable, while in the FAIR concept it was termed reusable. Both obviously mean the same in this context.

  5. **The concept of a fourth paradigm was probably first discussed by J. Gray on January 11, 2007, before he went missing in the Pacific Ocean on January 28, 2007.29

  6. ‡‡The Psi-k network represents scientists concerned with ab initio calculations of materials.

  7. §§CECAM is a European organization devoted to the promotion of fundamental research on advanced computational methods and to their application to important problems in frontier areas of science and technology, in physics and chemistry of condensed matter.

  8. ***ETSF, the European Theoretical Spectroscopy Facility, is a knowledge center for theoretical spectroscopy.

  9. ††”Codes” is widely used jargon in the field for scientific software packages.

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Acknowledgments

This work received funding from the EU’s Horizon 2020 Research and Innovation Programme, Grant Agreement No. 676580, the NOMAD Laboratory CoE and No. 740233, ERC: TEC1P. Support from the Einstein Foundation Berlin is appreciated. We thank C. Koch for in-depth discussions and information about transmission electron microscopy, P. Wittenburg for clarification of the FAIR concept, and the whole NOMAD team for the invaluable effort to build the entire NOMAD infrastructure and its services.

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Authors and Affiliations

  1. Humboldt-Universität zu Berlin, and Fritz-Haber-Institut Berlin, Germany

    Claudia Draxl

  2. Fritz-Haber-Institut Berlin, and Humboldt-Universität zu Berlin, Germany

    Matthias Scheffler

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  1. Claudia Draxl
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Correspondence to Claudia Draxl.

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Draxl, C., Scheffler, M. NOMAD: The FAIR concept for big data-driven materials science. MRS Bulletin 43, 676–682 (2018). https://doi.org/10.1557/mrs.2018.208

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