Digital image data is a crucial part of biological research, fueling an exponentially growing body of research output. A surge in volume and diversity of bioimage data, owing to the fast developing imaging technologies, has brought to light many challenges including in sharing open image data. Resource owners, research infrastructures as well as grass-roots communities are actively tackling these challenges by developing file formats, ontologies, metadata models, to ensure that shared data is in line with the FAIR principles. However, many of these solutions remain regional and a global coordination effort is necessary to enable seamless image data sharing. This project will lay the foundation for a Global Image Data Ecosystem (GIDE) that connects different biological and biomedical image data resources across the globe to allow metadata and data sharing. GIDE will bring European research infrastructure and image data resource owners together with their counterparts from Australia and Japan to develop the basis of image data sharing. These interactions can then be used as a blueprint to engage with the wider global bioimage data community while strengthening the position of European infrastructures in the landscape. To enable partner resources and research infrastructures to communicate in one language, coordinated technical development towards use of harmonised imaging ontologies and metadata models will be carried out. Proof of concept implementations using harmonised image data and metadata will showcase the project developments and encourage adoption of these recommendations globally. These developments will also lay a crucial and strong foundation to build a future federated image data ecosystem on. Together, global efforts towards GIDE will provide a necessary framework for bioimage data to grow into a democratised resource enabling innovative research in Europe and across the globe.

The recent explosion of next generation sequencing (NGS) data has caught Europe unprepared and led to a critical shortage of computational biology expertise. As NGS methods are expected to become pervasive from basic science to personalised medicine there is an urgent need for highly skilled young scientists trained in both computational biology and experimental wet lab biology. Our network addresses this important problem of the postgenomic era. We aim to provide multi-disciplinary skills for a solid foundation in computational biology and developmental genomics. Developmental genomics is central to understanding of ontogeny and many genetic and congenital anomalies, but was outside the scope of the landmark ENCODE and FANTOM projects. ENCODE highlighted the need for an in vivo vertebrate model that enables high throughput in vivo functional testing of hypotheses generated from genome scale annotation. Zebrafish is an ideal model for extending the scope of genomics to vertebrate development. We aim to comprehensively annotate functional elements, decipher genomic codes of transcription, as well as coding and non-coding gene function during development and enhance zebrafish as an attractive developmental, comparative and disease model. The participants include 7 non-academic members (2 of which are beneficiaries), major zebrafish genomics laboratories, eminent computational biologists and world class genomics technology experts active in FANTOM and ENCODE. The training program involves 15 ESRs, more than 40 intersectoral and interdisciplinary secondments totalling 19 months, 7 training courses and 2 workshops/conferences. The main outcome of this programme is a cohort of researchers with computational, experimental laboratory and transferable skills ready to further their career in academia, public health and the private sector.