The RDA FAIR Data Maturity Model Working Group is pleased to announce the public comment period for the FAIR Data Maturity Model specification and guidelines, as part of the process to propose an RDA Recommendation in mid-2020. The document is available for public review until 13 May 2020.
The work of the FAIR Data Maturity Model Working Group started in early 2019. Its objective is to bring together stakeholders from different scientific and research disciplines, the industry and public sector, who are active and/or interested in the FAIR principles and in particular in assessment criteria and methodologies for evaluating their real-life uptake and implementation level of the FAIR principles.
It was noted that there were several evaluation approaches and assessment frameworks, often using questionnaires that asked different questions due to their own interpretation of the FAIR principles. Because of these differences, it was difficult to compare the results of those approaches.
“The EOSC FAIR Working Group is tasked to provide the EOSC Executive Board with recommendations on a framework to assess FAIR data. In a landscape in which many teams are working on FAIR data assessment, the RDA Data Maturity Model WG is performing the essential and difficult task of reaching international agreement on data FAIRness criteria,” says Françoise Genova, Chair of the EOSC FAIR Working Group Metrics and Certification Task Force.
As part of the FAIR Data Maturity Model, the working group defined a set of indicators for various aspects of the FAIR principles, priorities for those indicators and a mechanism for assigning maturity levels to the evaluation of FAIRness based on the indicators. These components of the FAIR Data Maturity Model are described in the document that is now open for public comment as a proposed RDA Recommendation.
The indicators have been identified through an extensive period of consultation and testing with the working group members and beyond.
Rather than being yet another evaluation approach, the FAIR Data Maturity Model aims to establish common ground for evaluation approaches so that their results can be made comparable. It is not meant as a “how to”, but instead as a way to normalise assessment.
The model proposes the set of indicators, priorities and maturity levels for the evaluation of FAIRness on a general level. In practical application of the model, thematic communities can adapt the model to their specific needs and their expectations about FAIRness of the data resources they produce and manage.
“FAIRsFAIR project partners working on FAIR Certification played a significant role in reviewing the core FAIR criteria developed by the RDA FAIR Data Maturity Model WG. In addition, FAIRsFAIR used the outcomes of the WG (landscape analysis and criteria) as a basis to develop metrics for evaluating research data objects from selected European members of the network of Trustworthy Digital Repositories (TDRs)” Anusuriya Devaraju, PANGAEA Data Publisher for Earth & Environmental Science, MARUM - University of Bremen.
The model may be used during the development of Research Data Management Plans before any data resources have been produced to specify the level of FAIRness that the resources are expected to achieve. It can also be used after the production of data resources to test what the achieved level of the resources is. Data producers, i.e. researchers, and data publishers can use the model to determine where their practices could be improved to achieve a higher level of FAIRness, while project managers and funding agencies can use the model to determine whether the data resources achieve a pre-defined, expected level of FAIRness.
Application of the model in assessment approaches can then lead to increased coherence and interoperability of existing or emerging FAIR assessment frameworks, ensuring the combination and compatibility of their results in a meaningful way.
“The main benefits from the FAIRsFAIR perspective are that the RDA FAIR Data Maturity Model WG is clarifying FAIR into indicators so we can move from expressions of principles to testable statements. The next steps for us are to consider how the outcomes of the group can be translated into repository practices that allow us to assess FAIR at deposit, curate for FAIRness as part of our quality control, and communicate FAIRness to data users. i.e. to enable FAIR”. Hervé L'Hours, Repository & Preservation Manager, UK Data Archive.
To continue the work on the model and its implementation after the publication of the RDA Recommendation, the working group is investigating the option to establish an RDA maintenance working group.