Results of an Analysis of Existing FAIR Assessment Tools

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FAIR Data Maturity Model WG

Group co-chairs: Edit HerczogVassilios PeristerasKeith Russell

Supporting Output title:  Results of an Analysis of Existing FAIR Assessment Tools

Authors: FAIR Data Maturity Model WG

DOI: 10.15497/RDA00035

Citation:  TBC

Note: More information on the development of this document can be found in the WG's github repository.



This document is a first output of the FAIR Data Maturity Model WG. As a landscaping exercise, the editorial team of the WG analysed current and existing approaches related to FAIR self-assessment tools. The analysis was made based on publicly available documentation and an online survey. Questions and options stemming from theses different approaches were classified according to the FAIR principles/facets. Comments were collected and incorporated. This resulted in five slide decks, combined in this pdf document, that make up this preliminary analysis.




Review period start: 
Monday, 27 May, 2019 to Thursday, 27 June, 2019
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  • Emilie Lerigoleur's picture

    Author: Emilie Lerigoleur

    Date: 15 Jun, 2019

    This is a very nice initiative to compare and analyze these existing FAIR assesment tools.

    Few comments:

    - it will be interesting to describe the target audience in the background

    - please explain the first term "IRI"

    - what does it mean "X4" page 10?

    - the question page 27 "Are standard vocabularies..." is truncated!

    - the question page 29 "Please provide the URL..." is truncated!

    - it appeared to be quite difficult to find an answer to the following question page 34: " Granularity of data entities in dataset is appropriate in Respect of Meta-Data Granularity"

    - the question page 35 "Does the researcher provide..." is truncated!

    Next step is to identify core elements without duplicates for the evaluation of FAIRness, isn't it? I hope the maximum of the core common metrics will be automatically measured by machine as far as possible to ease the FAIRness assesment process.


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