Call: SwafS-04-2018: Encouraging the reuse of research data generated by publically funded research projects
There is a heightened policy interest in engaging society in research from the European Commission to all research fields.
SwafS (Science with and for Scoiety) is a transversal topic at EU level focusing on the evolution and interplay between science and society, including co-design with citizens, stakeholders and end-users.
FAIR4Health will be developed under the frame of the Strategic Orientation 1: Accelerating and catalysing processes of institutional change. This Strategic orientation will contribute to the Responsible Research and Innovation pillars: public engagement, science education, ethics, gender equality and open access; through institutional governance changes in RFPOs.
In the specific topic SwafS-04-2018, the challenge posed by the EC is the need to adopt actions to make FAIR all data and metadata derived from publicly funded research. This is make the data comply to be Findable, Accessible, Interoperable and Reusable.
The scope of this call could be summarized in these 4 points:
- To support the FAIRification of data, stressing on data quality (certification), their interoperability and reproducibility of research
- To generate pathfinder use cases to demonstrate how data sharing and re-use can generate a groundbreaking innovative product, service, or treatment
- To generate a prototype of such innovative product, service, or treatment
- To include at least 10 different EU countries in the consortium
This call has 2 main expected impacts:
- To increase the visibility of the Commission's open FAIR data policy through dedicated communication activities, and networking of relevant actors including industry.
- To generate a beneficial impact for science, the economy and society by means of:
- Increasing the reproducibility of research.
- Cross-fertilisation of interdisciplinary research.
- Boosting citizen science.
- Generating added value for innovative companies (including SMEs and start-ups) in the EU Digital Single Market.
This call also poses its own KPIs that should be monitored throughout the project:
- Increase in the use of FAIR data in the domains identified by the project
- Contribution of the use cases to the development of services based on innovative data sharing and reuse.
Use of FAIR data in health
We can find examples in the literature rising from the academic domain, such as the FAIR guide for data providers in human genomic data, in bottom-up initiatives such as the GO FAIR Implementation Networks for a practical implementation of the EOSC and the Research Data Alliance which embraces several Working Groups and Interest Groups for promoting the use of FAIR data in health. Besides, top-down initiatives are also entering into stage like the “Data for better health”, which is being driven by the Belgian government.
As it can be seen in the figure above, according to a PubMed search done in February 2019, FAIR data in health is gaining momentum since the publication in 2016 of the FAIR data guiding principles by the FORCE11 community, and it is foreseen to keep on growing in the coming years.
Improving Health Research in EU through FAIR Data
FAIR4Health is coordinated by Prof. Carlos L. Parra-Calderón, head of the Technological Innovation Unit at Virgen del Rocio University Hospital as part of the Andalusian Health Service in Spain.
The consortium accounts for 17 partners from 11 EU and non-EU countries. There is a strong representation from both southern and central Europe, and it includes non-EU countries such as Switzerland, Serbia and Turkey.
FAIR4Health brings together expertise from different domains (health research, data managers, medical informatics, software developers, standards and lawyers) all of them key stakeholders to address the challenges posed by the project.
In this link you can find the full list of participants.
The overall objective of FAIR4Health is to facilitate and encourage the EU health research community to FAIRify, share and reuse their datasets derived from publicly funded research initiatives.
- Specific Objective 1. To design and implement an effective outreach strategy at EU level based on trust building and shared benefit
- Specific Objective 2. To produce a set of guidelines to inform a number of Research Data Alliance recommendations in order to set the foundations for a FAIR data certification roadmap to guarantee high quality of data
- Specific Objective 3. To develop and validate intuitive, user-centered technological tools to enable the translation from raw (meta)data to FAIR (meta)data and support the FAIRification workflow, i.e., the FAIR4Health Platform and Agents
- Specific Objective 4. To demonstrate the potential impact in terms of health outcomes and health research that the implementation of such FAIR data strategy will have through the development and validation of 2 pathfinder case studies.
Besides the coordination, the Andalusian Health Service will lead the dissemination and outreach of the project, which receives inputs from the other work packages to inform the development of this strategy. Work package 2 is being led by Eva Méndez and her team from the University Carlos III of Madrid, and their role is to perform a comprehensive analysis of all the barriers and challenges that must be overcome to implement a FAIR data policy in the health research domain. The work package 3 is being led by Catherine Chronaki from Health Level 7, and its objective is to define all the technical requirements needed to develop the FAIR4Health platform and agents, task that will be led by Manuel Pérez and his team at Atos in work package 4. Once the technological tools are ready, Christian Lovis from University of Geneve will lead the development of the use cases demonstrators in work package 5. Finally, the sustainability and economic assessment of the project will be led by Gokçe Banu from Software R&D Consultancy within the work package 6.
Health researchers will be the main contributors in the FAIRification tasks. In turn, they will be able to browse and access to FAIRified datasets from their peers, always in compliance with the data owners’ policies in terms of licences, approval from local ethical board, regulatory framework, etc. For this purpose, FAIR4Health will define a clear workflow for the implementation of such FAIR data policy including all these details. Within the project, this workflow will be needed to successfully develop the use cases proposed.
But the project goes beyond the health research domain and also addresses the beneficial impact that such FAIR data strategy may have in health outcomes. For this purpose, data scientists will be able to develop innovative eHealth services built upon Privacy Preserving Distributed Data Mining approaches that could be applied over the FAIRified datasets without the need of hosting them outside the dataset owner’s facilities. These services will be available for the healthcare providers that request them in the context of the EU Digital Single Market.
In summary, there is a triple win behind this community:
- Health researchers could access larger datasets and accelerate the discovery of knowledge while avoiding bias due to local datasets
- eHealth services providers could develop and exploit innovative services in the EU Digital Single Market
- Healthcare providers could have access to this eHealth services portfolio that will allow them to improve their quality of care and, therefore, closing the cycle of a Learning Healthcare System based on FAIR.