ELMI was created in 2001 to establish a unique communication network between European scientists working in the field of light microscopy and the manufacturers of their equipment.
On 2 July 2019, EMBL-EBI announced its launch of the BioImage Archive (press release www.ebi.ac.uk/about/news/press-releases/bioimage-archive-launch).
The Image Data Resource project has worked with EMBL-EBI since its launch in 2015 to demonstrate the feasibility and utility of public bioimage data resources and is an active component of this new initiative. The Image Data Resource project has recently released two new domain-branded resources, Cell-IDR (idr.openmicroscopy.org/cell) and Tissue-IDR (idr.openmicroscopy.org/tissue), that integrate specific datasets and improve user experience and hopefully re-use of the data they hold.
Using funding from the UK Research and Innovation Strategic Priorities Fund, EMBL-EBI is building IT infrastructure to support the BioImage Archive, including a scalable storage architecture (object store), from which Cell-IDR and Tissue-IDR will benefit. These resources are growing too rapidly to be supported by their current storage (NFS) file systems and will therefore be leveraging the BioImage Archive’s object store in the future. As the changes only involve the back-end of the IDRs, they will not affect submission or access to published data. The web-based user interfaces of Cell-IDR and Tissue-IDR will appear unchanged. In the longer-term, we aim to connect the IDRs and the BioImaging Archive so that data can flow seamlessly between these complementary resources. For more information on how these types of resources can work together see Ellenberg et al, Nature Methods, 2018 (PDF, www.nature.com/articles/s41592-018-0195-8).
As the BioImage Archive is being built up over the next few years, users and depositors will experience additional benefits. For instance, integration of the archiving of light-microscopy data and EM data will enable transparent deposition and retrieval of data for correlative imaging modalities such as CLEM and CLXM. It will also enable linking and integration of diverse bioimaging datasets from a variety of modalities and on a range of biological scales.
We look forward to working with the community to make all these resources useful and and in the long-term essential for the community.