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What are the FAIR Principles?


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identifier: RX.X

version: v1.0

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Reading Time

10 minutes

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Background Information

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No

Intended Audience

Principal Investigators

Data Managers

Data Scientists


Introduction

The goal of this section is to go over each of the principles for FAIR data management as described by Wilkinson and coworkers in their Nature Springer Scientific Data manuscript published in 2016. Owing to the success of the principles, now endorsed by funding agencies (IMI, Wellcome Trust to name only two), but also by the G20 and by industry leaders, it is essential to remind the reader about those.

The FAIR Guiding Principles

doi: 10.1038/sdata.2016.18

### F. To be Findable:

>F1. (meta)data are assigned a **globally unique and persistent identifier**
>
>F2. data are described with **rich metadata** (defined by R1 below)
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>F3. metadata clearly and explicitly include the identifier of the data it describes
>
>F4. (meta)data are registered or **indexed in a searchable resource**

### A. To be Accessible:

>A1. (meta)data are retrievable by their identifier using **a standardized communications protocol**

>A1.1 the protocol is **open, free, and universally implementable**
>
>A1.2 the protocol allows for an authentication and authorization procedure, where necessary
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>A2. **metadata are accessible**, even when the data are no longer available

### I. To be Interoperable:

>I1. (meta)data use a **formal, accessible, shared, and broadly applicable language for knowledge representation**.
>
>I2. (meta)data use **vocabularies that follow FAIR principles**
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>I3. (meta)data include **qualified references** to other (meta)data

### R. To be Reusable:

>R1. meta(data) are richly described with a **plurality of accurate and relevant attributes**
>
>R1.1. (meta)data are released with a **clear and accessible data usage license**
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>R1.2. (meta)data are associated with **detailed provenance**
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>R1.3. (meta)data meet domain-relevant **community standards**

The FAIR principles and FAIRplus.

The principles will be the organizing principle for the FAIRplus Cookbook. While the book itself can be search in many different ways and its content exposed through a number of angles, personas and facets, the main Table of Content organizes a number of atomic recipes around of the principles and their associated sub themes.

FAIRplus Recipe & FAIR principles

FINDABILITY

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Search Engine Optimitization

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Open Archive Deposition

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Annotation

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ACCESSIBILITY

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Access condition

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License selection

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Standards

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INTEROPERABILITY

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Metadata Standards

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Open Syntax

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Ontology

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REUSABILITY

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Standards

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Ontology

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SMART API

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Conclusions:

This section should be seen as a refresher for any one unclear about the FAIR principles. Now that key background information has been provided, shining a light on an number of ethical issues driving both the development and implementation of the FAIR principles in the context of Life Science data as well as learning about the overall FAIRification process represent a natural progression in the content of the FAIR Cookbook.

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Reference:

  1. Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016). https://doi.org/10.1038/sdata.2016.18
  2. Wilkinson, M.D., Dumontier, M., Jan Aalbersberg, I. et al. Addendum: The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 6, 6 (2019). https://doi.org/10.1038/s41597-019-0009-6

Authors:

Name Affiliation orcid CrediT role
Philippe Rocca-Serra University of Oxford, Data Readiness Group 0000-0001-9853-5668 Writing - Original Draft
Susanna Assunta Sansone University of Oxford, Data Readiness Group 0000-0001-5306-5690 Writing - Original Draft
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