Abstract

FAIR (Findable, Accessible, Interoperable and Reusable) and "cloud-enabled" data management approaches are essential to effectively deal with the rapid expansion in the volume and complexity of life-science-related data and also meet the need for reliable data and metadata sources able to support the future implementation of Machine Learning and AI methods. This presentation will cover the work of two recently established European initiatives, FAIRplus (www.fairplus.eu) and the European Open Science Cloud-Life (www.EOSC-life.eu) which seek to increase the availability of high quality research data resources and enable their effective reuse within organisations and across the scientific community. Initial guidelines and tools on making data FAIR will be outlined as well as necessary training and approaches for data handlers and scientists. Case studies will outline the challenges of cloud deployment of research data and illustrate the requirements for working within the framework of GDPR and in studies involving sensitive data such as patient derived ‘omics results.