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FAIR Data Maturity Model. Specification and Guidelines

FAIR Data Maturity Model Working Group


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    <dct:title>FAIR Data Maturity Model. Specification and Guidelines</dct:title>
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    <dcat:keyword>RDA</dcat:keyword>
    <dcat:keyword>Recommendations</dcat:keyword>
    <dcat:keyword>FAIR data</dcat:keyword>
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    <dct:description>&lt;p&gt;Findability, Accessibility, Interoperability and Reusability &amp;ndash; the FAIR principles &amp;ndash; intend to define a minimal set of related but independent and separable guiding principles and practices that enable both machines and humans to find, access, interoperate and re-use data and metadata. The FAIR principles were defined in 2016 in an article by Mark Wilkinson et. al1. FORCE112 and GO FAIR3 provide further information on the principles. The principles have to be considered as inspiring concepts but not strict rules. This means that they may lead to diverse interpretations and ambiguity.&lt;/p&gt; &lt;p&gt;To remedy the proliferation of FAIRness measurements based on different interpretations of the principles, the RDA Working Group &amp;ldquo;FAIR data maturity model&amp;rdquo; established in January 2019 aims to develop a common set of core assessment criteria for FAIRness, as an RDA Recommendation. In the course of 2019 and the first half of 2020, the WG established a set of indicators and maturity levels for those indicators.&lt;/p&gt; &lt;p&gt;As a result of the work, a first set of guidelines and a checklist related to the implementation of the indicators were produced, with the objective to further align the guidelines for evaluating FAIRness with the needs of the community.&lt;/p&gt;</dct:description>
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