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FAIR4Health, an EU’s funded project, promotes the application of FAIR principles (Findable, Accessible, Interoperable, Reusable) in data derived from publicly funded health research initiatives to share and reuse them in the European Union Health Research community, defining an effective EU-wide strategy for the use of FAIR in Health. This paper analyses how to apply FAIR principles to “trust” in the context of the open-source software development of FAIR4Health. The FAIRification process and TRUST principles are discussed and related. The paper tries to open a new view on the trustworthiness of data access using open-source software. Work performed in the framework of FAIR4Health project, with funding from the European Union’s Horizon 2020 programme under grant agreement number 824666. In addition, work presented in this paper has been partially supported by the Generalitat de Catalunya (2017 SGR 1749).

Due to the nature of health data, its sharing and reuse for research are limited by ethical, legal and technical barriers. The FAIR4Health project facilitated and promoted the application of FAIR principles in health research data, derived from the publicly funded health research initiatives to make them Findable, Accessible, Interoperable, and Reusable (FAIR). To confirm the feasibility of the FAIR4Health solution, we performed two pathfinder case studies to carry out federated machine learning algorithms on FAIRified datasets from five health research organizations. The case studies demonstrated the potential impact of the developed FAIR4Health solution on health outcomes and social care research. Finally, we promoted the FAIRified data to share and reuse in the European Union Health Research community, defining an effective EU-wide strategy for the use of FAIR principles in health research and preparing the ground for a roadmap for health research institutions. This scientific report presents a general overview of the FAIR4Health solution: from the FAIRification workflow design to translate raw data/metadata to FAIR data/metadata in the health research domain to the FAIR4Health demonstrators' performance., This research was financially supported by the European Union’s Horizon 2020 research and innovation programme under the grant agreement No 824666 (project FAIR4Health). Also, this research has been co-supported by the Carlos III National Institute of Health, through the IMPaCT Data project (code IMP/00019), and through the Platform for Dynamization and Innovation of the Spanish National Health System industrial capacities and their effective transfer to the productive sector (code PT20/00088), both co-funded by European Regional Development Fund (FEDER) ‘A way of making Europe’.