Generating FAIR research data in experimental tribology

Generating FAIR research data in experimental tribology

Abstract Solutions for the generation of FAIR (Findable, Accessible, Interoperable, and Reusable) data and metadata in experimental tribology are currently lacking. Nonetheless, FAIR data production is a promising path for implementing scalable data science techniques in tribology, which can lead to...

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Bibliographic Details
Main Authors: Nikolay T. Garabedian, Paul J. Schreiber, Nico Brandt, Philipp Zschumme, Ines L. Blatter, Antje Dollmann, Christian Haug, Daniel Kümmel, Yulong Li, Franziska Meyer, Carina E. Morstein, Julia S. Rau, Manfred Weber, Johannes Schneider, Peter Gumbsch, Michael Selzer, Christian Greiner
Format: Article
Language:English
Published: Nature Portfolio 2022-06-01
Series:Scientific Data
Online Access:https://doi.org/10.1038/s41597-022-01429-9

Internet

https://doi.org/10.1038/s41597-022-01429-9

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