FAIR Data Maturity Model: specification and guidelines

Year:	2020
Title:	FAIR Data Maturity Model: specification and guidelines
Abstract:	Establishes a common set of core assessment criteria and maturity levels for evaluating FAIRness.
Objectives:	Develop a common set of core assessment criteria for FAIRness and help organizations determine if data resources meet required quality thresholds.
Methodology:	The Working Group established indicators and maturity levels.
Algorithm Used:	N/A (Specification/Guideline)
Top Model:	RDA FAIR Data Maturity Model
Accuracy:	N/A (Guideline)
Advantages:	Increases coherence and interoperability of existing FAIR assessment frameworks; provides a basis for benchmarking and improvement.7
Drawbacks:	N/A explicitly mentioned.
Source:	https://zenodo.org/records/3909563#.YGRNnq8za70 Edit

Criteria (5)

Name	Description	Definitions
Findability	Establishes a common set of core assessment criteria and maturity levels for evaluating FAIRness. (2020)	Quality dimension from FAIR Data Maturity Model: specification and guidelines (2020) Establishes a common set of core assessment criteria and maturity levels for evaluating FAIRness. (2020)
Accessibility	Establishes a common set of core assessment criteria and maturity levels for evaluating FAIRness. (2020)	Quality dimension from FAIR Data Maturity Model: specification and guidelines (2020) Establishes a common set of core assessment criteria and maturity levels for evaluating FAIRness. (2020)
Interoperability	Establishes a common set of core assessment criteria and maturity levels for evaluating FAIRness. (2020)	Quality dimension from FAIR Data Maturity Model: specification and guidelines (2020) Establishes a common set of core assessment criteria and maturity levels for evaluating FAIRness. (2020)
Reusability	Establishes a common set of core assessment criteria and maturity levels for evaluating FAIRness. (2020)	Quality dimension from FAIR Data Maturity Model: specification and guidelines (2020) Establishes a common set of core assessment criteria and maturity levels for evaluating FAIRness. (2020)
Metadata Consistency	Establishes a common set of core assessment criteria and maturity levels for evaluating FAIRness. (2020)	Quality dimension from FAIR Data Maturity Model: specification and guidelines (2020) Establishes a common set of core assessment criteria and maturity levels for evaluating FAIRness. (2020)