Shared Metadata for Data-Centric Materials Science
Abstract
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 what features 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.
Cite
@article{arxiv.2205.14774,
title = {Shared Metadata for Data-Centric Materials Science},
author = {Luca M. Ghiringhelli and Carsten Baldauf and Tristan Bereau and Sandor Brockhauser and Christian Carbogno and Javad Chamanara and Stefano Cozzini and Stefano Curtarolo and Claudia Draxl and Shyam Dwaraknath and Ádám Fekete and James Kermode and Christoph T. Koch and Markus Kühbach and Alvin Noe Ladines and Patrick Lambrix and Maja-Olivia Lenz-Himmer and Sergey Levchenko and Micael Oliveira and Adam Michalchuk and Ron Miller and Berk Onat and Pasquale Pavone and Giovanni Pizzi and Benjamin Regler and Gian-Marco Rignanese and Jörg Schaarschmidt and Markus Scheidgen and Astrid Schneidewind and Tatyana Sheveleva and Chuanxun Su and Denis Usvyat and Omar Valsson and Christof Wöll and Matthias Scheffler},
journal= {arXiv preprint arXiv:2205.14774},
year = {2023}
}