The NOMAD laboratory: from data sharing to artificial intelligence

被引:277
作者
Draxl, Claudia [1 ,2 ]
Scheffler, Matthias [1 ,2 ]
机构
[1] Humboldt Univ, IRIS Adlershof, Zum Grossen Windkanal 6, D-12489 Berlin, Germany
[2] Max Planck Gesell, Faradayweg 4-6, D-14195 Berlin, Germany
来源
JOURNAL OF PHYSICS-MATERIALS | 2019年 / 2卷 / 03期
基金
欧洲研究理事会; 欧盟地平线“2020”;
关键词
data science; data repository; data analytics; metadata; computational materials; SCIENCE;
D O I
10.1088/2515-7639/ab13bb
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The Novel Materials Discovery (NOMAD) Laboratory is a user-driven platform for sharing and exploiting computational materials science data. It accounts for the various aspects of data being a crucial raw material and most relevant to accelerate materials research and engineering. NOMAD, with the NOMAD Repository, and its code-independent and normalized form, the NOMAD Archive, comprises the worldwide largest data collection of this field. Based on its findable accessible, interoperable, reusable data infrastructure, various services are offered, comprising advanced visualization, the NOMAD Encyclopedia, and artificial-intelligence tools. The latter are realized in the NOMAD Analytics Toolkit. Prerequisite for all this is the NOMAD metadata, a unique and thorough description of the data, that are produced by all important computer codes of the community. Uploaded data are tagged by a persistent identifier, and users can also request a digital object identifier to make data citable. Developments and advancements of parsers and metadata are organized jointly with users and code developers. In this work, we review the NOMAD concept and implementation, highlight its orthogonality to and synergistic interplay with other data collections, and provide an outlook regarding ongoing and future developments.
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页数:9
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