07 April 2020


Whilst substantial progress has been made in developing FAIR assessment frameworks for data and other digital objects, a FAIR assessment framework for data services is still lacking. The publication of the FAIRsFAIR Assessment report on FAIRness of Services marks the first milestone in a task to remedy the situation.

Authored by FAIRsFAIR project partners in the work group "FAIR practices: semantics, interoperability and services", the report presents a survey of the FAIR assessment frameworks currently in use, a proposed set of guiding principles and desiderata for the assessment framework to be developed, and three ‘FAIR service assessment’ case studies. The frameworks currently in use are grouped into the three main areas served: digital objects, data repositories, and data stewardship, processes and organisational maturity. The report also provides a working definition of a data service as an integral component of the FAIR ecosystem.

Comments and suggestions on the contents of the report will inform subsequent work and, ultimately, feed into a FAIR assessment framework for data services that delivers clear direction and value to service providers and the community at large.

Data Service- A Working Definition

In terms of arriving at a definition of data service,  the writers acknowledge that existing models and frameworks such as the FAIR Digital Object model, the Open Archival Information System (OAIS), and the ‘Internet of FAIR Data & Services’ as promoted by GO-FAIR18 will provide valuable starting points. For the purposes of the report Purposethey consider as a data service "any service that acts on at least one component of the ‘holy trinity of data management’: the bit sequence, the metadata and the PID of a digital object. This includes services that bind these components together (e.g. associating metadata with a bit sequence), services that deliver data to the user, services that automatically analyze or transform data, services that aggregate and index metadata, and services that store or replicate data..."

Guiding Principles

With the ultimate goal of its being adopted by the European Open Science Cloud and associated communities, the writers provide a comprehensive list of the necessary features of the assessment framework. These include comprehensiveness in the sense of being applicable to a broad range of functionalities across the data life cycle and across academic disciplines, and inclusivity - relevance to a wide array of service providers including both commercial and public organisations. Crucially it should also be rooted in FAIR data, in that it clearly relates the FAIRness of a service to the FAIRness of the digital object that it acts on - this an explicit connection to the original FAIR Data Principles

To access the report on ZENODO click here.

To provide comments please access the Google doc here. 



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