Measuring maturity of data

2018.06 FAIR Data Maturity Model

When is this action of interest to you?

This action aims to develop a self-assessment methodology that any public sector or research organisation can use in order to measure the maturity level of its datasets, projects or data infrastructures from the following perspectives:
a) data findability, i.e. how well an organisation describes the data it generates or manages with rich metadata and globally unique persistent identifiers;
b) data accessibility, i.e. how well an organisation allows its data/metadata to be retrieved;
c) data interoperability, i.e. how well an organisation ensures that the precise format and meaning of exchanged and shared data/metadata is preserved and understood;
d) data reusability, i.e. how well an organisation releases metadata with a clear and accessible data usage licence.

What is this action about?

Findability, Accessibility, Interoperability and Reusability – the FAIR principles introduced in 2014 - intend to define a minimal set of community-agreed guiding principles and practices that allow both machines and humans to find, access, interoperate and re-use data. Although the FAIR principles were initially applied to research data, their coverage has been extended to data produced or managed by the public sector.

The aspirational nature of the FAIR principles and their rapid adoption at international level has led to an ambiguity and a wide range of interpretations of FAIRness since the principles do not strictly define how to achieve a state of FAIRness but rather they describe a continuum of features, attributes and behaviours that move data closer to that goal. As a result, a number of incompatible methodologies to assess FAIRness has been developed already and relevant work is in under way by various groups.

What are the objectives?

The main objective of the Action is to develop a common set of core assessment criteria for FAIRness, which will be accompanied by a generic and expandable self-assessment model for measuring the implementation level of the FAIR principles. The Action improves the interoperability of existing and emerging assessment methodologies for FAIR, allows the combination and comparison of their results and increases the homogeneity of the FAIR metric tools.

What are the benefits?

The Action will provide an instrument with a three-fold nature to data producers, data service owners and policy makers:

Descriptive, i.e. it will describe the as-is FAIR-related maturity level of digital objects
Prescriptive, i.e. it will provide guidance to improve the implementation of the FAIR data principles through recommendations
Comparative, i.e. it will allow a benchmark based comparison amongst peers

What has been achieved?

Establishment of a new Research Data Alliance Working Group entitled “FAIR Data maturity model”
Two deliverables were published: “Literature review and design methodology” and “FAIR data maturity model - early version”

What are the next steps?

The Action has entered the execution phase, which includes the next steps:

Definition of a systematic, effective and efficient design methodology that will lead to results that are rigorous and both theoretically founded and empirically validated
Development of all components with regard to the structure and the body of the FAIR assessment criteria and the maturity model
Verification and validation of the assessment criteria and the model based on a well-defined testing methodology
Definition of concrete indicators for the four FAIR principles and their categorisation into essential or optional criteria
Achieving consensus within the RDA group and finalising the maturity model
Testing the model with actual data-sets and trying to cover various disciplines that will give an indication of the interoperability requirements and eventual updating of the core criteria for FAIRness