Introduction - FAIR data, systems and analysis

Paul Groth; Michel Dumontier

doi:10.3233/DS-200029

Introduction - FAIR data, systems and analysis

Paul Groth
, Michel Dumontier

Elsevier Labs

Research output: Contribution to journal › Review article › peer-review

4 Scopus citations

Abstract

The FAIR principles outline key attributes to make digital resources more Findable, Accessible, Interoperable, and Reusable. Globally endorsed and widely adopted, there is now a pressing need to enable the establishment of an Internet of FAIR Data and Services, to demonstrate how these can be used to generate new insights, and to assess the overall value for FAIR across different sectors. Realizing the value of the FAIR principles will require a combination of scientific, technical, social, legal, and ethical advances for the production, sharing, discovery, assessment, and reuse of data. This special issue highlights research and software that is making FAIR data and services a reality.

Original language	English
Pages (from-to)	1-2
Number of pages	2
Journal	Data Science
Volume	3
Issue number	1
DOIs	https://doi.org/10.3233/DS-200029
State	Published - Jun 12 2020

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Introduction - FAIR data, systems and analysis

Abstract

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