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In this work we present the FAIRsFAIR service assessment framework, a framework for assessing how well research data infrastructure services support FAIR data. The framework focuses on providing guidelines on how services can be made to optimally improve the FAIRness of the data that they are used for. This work was inspired by a combination of literature describing the expectations users have from FAIR data services, and refined by the authors based on feedback from the community gained e.g. through workshops. This framework is the last deliverable of the T2.4 task group in the FAIRsFAIR project, and it will be presented to the European Open Science Cloud (EOSC) where we expect the most direct usage of the framework.

FAIRsFAIR invited providers of data services – and all other interested stakeholders - across the full range of scientific disciplines to participate in a workshop to validate and further develop the FAIR assessment framework for data services. The proposed framework is described in the recently published FAIRsFAIRReport on Basic Framework on FAIRness of Servicesand was introduced to the research community at adedicated webinar. This is the second workshop, after a first workshop in February. The purpose of the workshop, which will be hosted by the authors of the report, is to discuss the six key aspects of the framework with potential users to identify gaps and formulate improvements. Feedback received will be incorporated into a further iteration of the report to be published later in 2021. Why a FAIR Assessment Framework for Data Services? The FAIR assessment framework for data services aims to assist service providers to ensure their data services are ‘FAIR enabling’ and optimally support the FAIRification process. This is important because realizing the full potential of a FAIR ecosystem - in which research outputs can be easily shared and optimally reused - requires looking beyond the FAIRification of data and other digital objects to also consider the infrastructure and services that act on those objects. During the workshop the 3rd iteration of the Assessment Framework was reviewed, it is available here: https://doi.org/10.5281/zenodo.4771937. The recording of the workshop is available onYouTube.

This is an updated version of the initial basic framework on FAIRness of services as presented in detail in: Koers, Hylke, Herterich, Patricia, Hooft, Rob, Gruenpeter, Morane, & Aalto, Tero. (2020). M2.10 Report on basic framework on FAIRness of services (Version 1.0). Zenodo. https://doi.org/10.5281/zenodo.4292598 The initial milestone was based on literature review, interviews and feedback collected at an EOSC-hub week session. A second version (March 2021) incorporated feedback from the report launch webinar (Jan 2021) and workshop (Feb 2021) gathering more detailed feedback on the assessment framework. This current version (iteration 3, May 2021) introduces an update to the overall aspects as Trustworthiness has been split into two aspects for clarification: Transparency and Longevity. Additional changes cover rewording of recommendations as well as deletions of duplicate recommendations. We also clarified FAIR-enablement by highlighting that it covers both augmenting FAIRness of a digital object and facilitating a certain FAIR principle.

This document identifies and evaluates a set of business models for procuring services in EOSC and maps them to the EOSC ecosystem. It identifies open issues requiring more analysis, along with related opportunities and risks. A roadmap for activities beyond the life of the project is presented, including recommendations for key stakeholders.

This presentation is part of the 3rd edition of the Helis Academy FAIR data stewardship (for life sciences) course Day 2, March 18, 2021 https://www.aanmelder.nl/fair-data-stewardship-2021 https://helisacademy.com/en/data-analysis-stewardship Topic: infrastructure for storing and sharing data