FAIR data enabling new horizons for materials research

被引：143

作者：

Scheffler, Matthias ^{[1
,2
,3
]}

Aeschlimann, Martin ^{[4
,5
]}

Albrecht, Martin ^{[6
]}

Bereau, Tristan ^{[7
]}

Bungartz, Hans-Joachim ^{[8
]}

Felser, Claudia ^{[9
]}

Greiner, Mark ^{[10
]}

Gross, Axel ^{[11
,12
]}

Koch, Christoph T. ^{[1
,2
]}

Kremer, Kurt ^{[7
]}

Nagel, Wolfgang E. ^{[13
]}

Scheidgen, Markus ^{[1
,2
]}

Woell, Christof ^{[14
]}

Draxl, Claudia ^{[1
,2
,3
]}

机构：

[1] Humboldt Univ, Phys Dept, Berlin, Germany

[2] Humboldt Univ, IRIS Adlershof, Berlin, Germany

[3] Max Planck Gesell, NOMAD Lab, Fritz Haber Inst, Berlin, Germany

[4] Univ Kaiserslautern, Dept Phys, Kaiserslautern, Germany

[5] Univ Kaiserslautern, Res Ctr OPTIMAS, Kaiserslautern, Germany

[6] Leibniz Inst Kristallzuchtung, Berlin, Germany

[7] Max Planck Inst Polymer Res, Mainz, Germany

[8] Tech Univ Munich, Dept Informat, Munich, Germany

[9] Max Planck Inst Chem Phys Solids, Dresden, Germany

[10] Max Planck Inst Chem Energy Convers, Mulheim, Germany

[11] Ulm Univ, Inst Theoret Chem, Ulm, Germany

[12] Helmholtz Inst Ulm, Ulm, Germany

[13] Tech Univ Dresden, Comp Sci Dept, Dresden, Germany

[14] Karlsruhe Inst Technol, Inst Funct Interfaces, Karlsruhe, Germany

来源：

NATURE | 2022年 / 604卷 / 7907期

关键词：

D O I：

10.1038/s41586-022-04501-x

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

The prosperity and lifestyle of our society are very much governed by achievements in condensed matter physics, chemistry and materials science, because new products for sectors such as energy, the environment, health, mobility and information technology (IT) rely largely on improved or even new materials. Examples include solid-state lighting, touchscreens, batteries, implants, drug delivery and many more. The enormous amount of research data produced every day in these fields represents a gold mine of the twenty-first century. This gold mine is, however, of little value if these data are not comprehensively characterized and made available. How can we refine this feedstock; that is, turn data into knowledge and value? For this, a FAIR (findable, accessible, interoperable and reusable) data infrastructure is a must. Only then can data be readily shared and explored using data analytics and artificial intelligence (Al) methods. Making data 'findable and AI ready' (a forward-looking interpretation of the acronym) will change the way in which science is carried out today. In this Perspective, we discuss how we can prepare to make this happen for the field of materials science.

引用

页码：635 / 642

页数：8

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