Shared metadata for data-centric materials science

Sci Data 10 (2023)
Author

Ghiringhelli, Baldauf, Bereau, Brockhauser, Carbogno, Chamanara, Cozzini, Curtarolo, Draxl, Dwaraknath, Fekete, Kermode, Koch, Kühbach, Ladines, Lambrix, Himmer, Levchenko, Oliveira, Michalchuk, Miller, Onat, Pavone, Pizzi, Regler, Rignanese, Schaarschmidt, Scheidgen, Schneidewind, Sheveleva, Su, Usvyat, Valsson, Wöll, Scheffler

Published

2023-09-14

Doi



The expansive production of data in materials science, their widespread sharing and repurposing requires educated support and stewardship. In order to ensure that this need helps rather than hinders scientific work, the implementation of the FAIR-data principles ( Findable, Accessible, Interoperable, and Reusable ) must not be too narrow. Besides, the wider materials-science community ought to agree on the strategies to tackle the challenges that are specific to its data, both from computations and experiments. In this paper, we present the result of the discussions held at the workshop on “Shared Metadata and Data Formats for Big-Data Driven Materials Science”. We start from an operative definition of metadata, and the features that  a FAIR-compliant metadata schema should have. We will mainly focus on computational materials-science data and propose a constructive approach for the FAIRification of the (meta)data related to ground-state and excited-states calculations, potential-energy sampling, and generalized workflows. Finally, challenges with the FAIRification of experimental (meta)data and materials-science ontologies are presented together with an outlook of how to meet them.

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This paper presents an operative definition of metadata, and the features that a FAIR-compliant metadata schema should have, and proposes a constructive approach for the FAIRification of the (meta)data related to ground-state and excited-states calculations, potential-energy sampling, and generalized workflows.

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 @article{Ghiringhelli_2023, title={Shared metadata for data-centric materials science}, volume={10}, ISSN={2052-4463}, url={http://dx.doi.org/10.1038/s41597-023-02501-8}, DOI={10.1038/s41597-023-02501-8}, number={1}, journal={Scientific Data}, publisher={Springer Science and Business Media LLC}, author={Ghiringhelli, Luca M. and Baldauf, Carsten and Bereau, Tristan and Brockhauser, Sandor and Carbogno, Christian and Chamanara, Javad and Cozzini, Stefano and Curtarolo, Stefano and Draxl, Claudia and Dwaraknath, Shyam and Fekete, Ádám and Kermode, James and Koch, Christoph T. and Kühbach, Markus and Ladines, Alvin Noe and Lambrix, Patrick and Himmer, Maja-Olivia and Levchenko, Sergey V. and Oliveira, Micael and Michalchuk, Adam and Miller, Ronald E. and Onat, Berk and Pavone, Pasquale and Pizzi, Giovanni and Regler, Benjamin and Rignanese, Gian-Marco and Schaarschmidt, Jörg and Scheidgen, Markus and Schneidewind, Astrid and Sheveleva, Tatyana and Su, Chuanxun and Usvyat, Denis and Valsson, Omar and Wöll, Christof and Scheffler, Matthias}, year={2023}, month=sep }
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