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  • 1
    Online Resource
    Online Resource
    Berlin : Humboldt-Universität zu Berlin
    UID:
    edochu_18452_28987
    Format: 1 Online-Ressource (18 Seiten)
    Content: 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.
    Content: Peer Reviewed
    Note: The article processing charge was funded by the Open Access Publication Fund of Humboldt-Universität zu Berlin. Full list of authors: Luca M. Ghiringhelli, Carsten Baldauf, Tristan Bereau, Sandor Brockhauser, Christian Carbogno, Javad Chamanara, Stefano Cozzini, Stefano Curtarolo, Claudia Draxl, Shyam Dwaraknath, Ádám Fekete, James Kermode, Christoph T. Koch, Markus Kühbach, Alvin Noe Ladines, Patrick Lambrix, Maja-Olivia Himmer, Sergey V. Levchenko, Micael Oliveira, Adam Michalchuk, Ronald E. Miller, Berk Onat, Pasquale Pavone, Giovanni Pizzi, Benjamin Regler, Gian-Marco Rignanese, Jörg Schaarschmidt, Markus Scheidgen, Astrid Schneidewind, Tatyana Sheveleva, Chuanxun Su, Denis Usvyat, Omar Valsson, Christof Wöll & Matthias Scheffler
    In: London : Nature Publ. Group, 2023, 10
    Language: English
    URL: Volltext  (kostenfrei)
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  • 2
    UID:
    gbv_635069660
    Format: Ill., graph. Darst.
    ISSN: 1549-960X
    In: Journal of chemical information and modeling, Washington, DC : American Chemical Society, 2005, 50(2010), 5, Seite 879-889, 1549-960X
    In: volume:50
    In: year:2010
    In: number:5
    In: pages:879-889
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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