Overview of the progress

The FAIR4Health project has 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). First of all, to achieve the FAIR4Health purpose, and due to the nature of health data, FAIR4Health consortium has performed a comprehensive analysis of the legal, ethical and technical requirements for the health data sharing and reuse for research (WP2). Besides, we have gathered the technical specifications and requirements to be met during the development stage, providing the technical solution to the FAIR guiding principles and the design of technological architecture (WP3). To confirm the feasibility of the FAIR4Health solution implemented (WP4), we have carried out two pathfinder case studies to carry out federated machine learning algorithms on FAIRified datasets from five health research organizations (WP5). The case studies demonstrated the potential impact of the developed FAIR4Health solution on health outcomes and social care research. Likewise, we have 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 to offer access to certified FAIR datasets. In addition, we have received support from the Horizon Results Booster (HRB) program for: (i) Portfolio Dissemination & Exploitation Strategy, and (ii) Business Plan Development. Both services were completed with successful outcomes and deliverables and with great collaboration with HRB experts (WP6). The description of the exploitable results and how they can/will be exploited are included in the deliverable D6.3 ‘Business model & marketing strategy for products/services derived from FAIR data reuse in health domains’. We have carried out a proper communication and cooperation between all its partners, holding regular meetings and strengthening the collaboration to meet the objectives of the project and guaranteeing the scientific quality of the results (WP1). FAIR4Health consortium has developed several outreach strategies directed towards maximising the impact of FAIR4Health project at large, producing and publishing material for scientific dissemination at conferences, congresses, workshops, as well as training materials for FAIR4Health solution (WP7). Furthermore, from a transversal point of view throughout the project, we have followed up to ensure compliance with the ethical requirements set out in the project (WP8). [A diagrama about the Work Packages (WP) interactions are available here: https://www.fair4health.eu/en/project]

Key software outputs

The FAIR4Health project offers to the health research scientific community the following software outputs:

• The fully open-source software developed in the project, that can be downloaded using the GitHub repository (under Apache 2.0 license): https://github.com/fair4health, including:
• The Data Curation Tool, the first FAIRification tool involved in the process. Available at https://github.com/fair4health/data-curation-tool. Video tutorial at https://www.youtube.com/watch?v=9FfG-sH4RXE. Manual at https://osf.io/tv3fw/.
• The Data Privacy Tool, the second FAIRification tool involved in the process. Available at https://github.com/fair4health/data-privacy-tool. Video tutorial at https://www.youtube.com/watch?v=sWzUv1RNSvI. Manual at https://osf.io/ywhrj/.
• The FAIR4Health platform, to support the execution of machine learning algorithms. Available at https://github.com/fair4health/f4h-portal-ui (interface) and https://github.com/fair4health/f4h-portal-backend (backend).
• These 2 tools have been published in the bio.tools repository (https://bio.tools/) anchored within ELIXIR, the European Infrastructure for Biological Information, under the GNU General Public Licence v3.0 (GPL-3.0). Data Curation Tool. https://bio.tools/fair4health_data_curation_tool. Data Privacy Tool. https://bio.tools/fair4health_data_privacy_tool.
• The FAIR4Health platform deployed and valitated in the context of the project: http://portal.fair4health.eu/

Other kind of key outputs

1. FAIRification Workflow (doi.org/10.1055/s-0040-1713684), to provide a conceptual blueprint for how sensitive, protected patient health information can be made available for medical research in a secure and compliant manner.

2. FAIR4Health Open Community (https://www.fair4health.eu/en/membership).

3. HL7 ‘FAIRness for FHIR’ project (confluence.hl7.org/pages/viewpage.action?pageId=91991234), to develop a new HL7 FHIR Implementation Guide called FHIR4FAIR (build.fhir.org/ig/HL7/fhir-for-fair).

4. Research Data Alliance (RDA) working group (WG) on Raising FAIRness in health data and Health Research Performing Organisations (HRPOs), drafting guidelines to implement FAIR data policies in HRPOs (rd-alliance.org/groups/raising-fairness-health-data-and-health-research-performing-organisations-hrpos).

5. New European Federation for Medical Informatics (EFMI) WG “FAIR Data” (efmi.org/workinggroups/fair-fair-data-in-health-research-performing-organizations-hrpos).

6. Working item proposal for Standardization Technical Committee 251 (CEN TC/251).

7. Publication of FAIR4Health metadata in OpenAIRE (https://explore.openaire.eu/search/other?pid=10.5281%2Fzenodo.6401048), Digital CSIC (doi.org/10.20350/digitalCSIC/14571), Zenodo (doi.org/10.5281/zenodo.6401048) and GitHub (github.com/fair4health/metadata).

8. Scientific publications at JCR journals, and chapters in books:

• From Raw Data to FAIR Data: The FAIRification Workflow for Health Research (http://doi.org/10.1055/s-0040-1713684). Methods of Information in Medicine.
• The Challenge of the Effective Implementation of FAIR Principles in Biomedical Research (http://doi.org/10.1055/s-0040-1721726). Methods of Information in Medicine.
• Security and Privacy when Applying FAIR Principles to Genomic Information (http://doi.org/10.3233/SHTI200690). Studies in Health Technology and Informatics.
• FAIR4Health: Findable, Accessible, Interoperable and Reusable data to foster Health Research (http://doi.org/10.12688/openreseurope.14349.1). Open Research Europe.
• Applying the FAIR4Health Solution to Identify Multimorbidity Patterns and their Association with Mortality through a Frequent Pattern Growth Association Algorithm: Validation Study (https://doi.org/10.3390/ijerph19042040). International Journal of Environmental Research and Public Health.