[Sarah Jones]

Meeting Title: Assessing FAIR Data Policy Implementation in Health Research (Remote Access Instructions) 
 
Meeting Location: Commonwealth A1
 
Collaborative session notes: 
https://docs.google.com/document/d/1HtjHcWzknrmtD2ck99tLXwTgtq3edrK1Gv2NqQeulJE/edit
 
Meeting objectives
– Sharing information on the new FAIR4Health project and the landscape analysis it will conduct to assess FAIR implementation in health research
– Collating feedback on the draft survey and methodology to assess community engagement
– Identifying potential international collaborators who may do similar activities so the European work is set in a broader global context
– Beginning to take stock of the landscape, particularly in terms of ethical challenges and cultural and behavioural barriers for FAIR open data policy implementation in general and in the health research domain in particular.
– Seeking inputs to help guide the development of the FAIRification tool and guidelines for implementing FAIR Open data policy in health and social care research. We hope to deliver/enhance these under the constructs of RDA IG/WG so they benefit from international input and can be adopted globally rather than being only project outputs.
 
 
Meeting agenda
10 mins intro to project and aims for input from others (Eva)
60 mins group activity:
– Elicit feedback on draft survey and methodology to assess community engagement
– Identify what FAIR practices / projects are already in place internationally, specifically in terms of health and social care research
– Seek potential collaborators internationally and explore desire for a formal IG/WG
20 mins – plenary discussion and next steps
 
Short description
Much work has already been done within the European Commission to pursue a FAIR data agenda within the European Open Science Cloud. The EC convened an Expert Group to provide an Action Plan on Turning FAIR Data into Reality, and has funded several projects under the current work programme including FAIR4Health, focused on health and social care research, and an overarching FAIRsFAIR coordination project to support uptake across all disciplines. 
Internationally, many projects have been undertaken to test the applicability of and implement the FAIR data principles in different research domains. In the USA, the Arnold Foundation has supported a very large project convened by the American Geophysical Union to Enable FAIR Data in the Earth Space and Environmental Sciences. In Denmark, a project has investigated the application of FAIR practices across a range of different disciplines, including sensitive health data, and developed a series of case studies and guidance materials to debunk myths. SURF in the Netherlands commissioned an excellent report on FAIR in practice and the Australian National Data Service has been supporting a programme of FAIR activities and funded projects which are due to report soon.
The FAIR4Health vision for 2020 is to foster a vast, open community of EU health research institutions fully engaged in open research data mandates and enhancing their knowledge-based economy and research excellence thanks to the application of the FAIR guiding principles. High-quality health research and routine care data will be shared and reused in a secure, controlled and legally compliant environment in order to accelerate knowledge discovery while reducing bias and enhancing the strength and quality of the scientific evidence. Furthermore, a community of data scientists from both public research institutions and private companies will be attracted to develop advanced analytical solutions able to intercommunicate in order to provide data-driven innovative services that will enable a seamless application of the new evidence raised into the clinical practice. FAIR4Health will contribute significant advances by implementing the FAIR principles under an interdisciplinary approach oriented towards the provision of eHealth services that in turn generate reusable FAIR data.
In terms of health and social care research data, the main concerns about data sharing are related to ethical implications, cultural barriers, information security and patient privacy, given the high level of sensitivity inherent to these datasets. Although FAIR does not imply open data sharing, many people confuse and conflate the concepts. Data sharing agreements that control who can view/use the data, for what purposes and under what conditions are paramount in our field. Furthermore, ethical implications derived from the secondary use of health research datasets such as incidental findings and potential conflict of interests should also be dealt iwith n depth to safeguard the rights of data donors, research organisations and providers of data-driven eHealth services. On the technological side, effective solutions able to guarantee high levels of information security and data anonymization must be put in place to set a trustworthy foundation for the FAIR4Health community to build on. All these aspects will be dealt thoroughly within the FAIR4Health project in order to shape the nature of the FAIRification tool and our guidelines for policy implementation. 
 
Additional links to informative material
Turning FAIR into Reality, European Commission Expert Group Report and Action Plan
AGU Enabling FAIR data project
Danish FAIR across disciplines project
FAIR data advanced use cases: from principles to practice in the Netherlands
ANDS programme on FAIR data
FAIR4Health project summary
FAIR4Health Twitter
 

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