Making BioImage Data FAIR on a Global Scale: OME’s Bio-Formats, OME-TIFF, OMERO, & IDR

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Image Data Analysis, Management and Visualisation
Jason R. Swedlow (1)
1. Centre for Gene Regulation & Expression, University of Dundee
Abstract text

Despite significant advances in biological imaging and analysis, major informatics challenges remain unsolved: file formats are proprietary, storage and analysis facilities are lacking, as are standards for sharing image data and results. The Open Microscopy Environment (OME; is an open-source software framework which aims to address these challenges. OME releases specifications and software for managing image datasets and integrating them with other scientific data. OME’s Bio-Formats and OMERO are used in 1000’s of labs worldwide to enable discovery with imaging. OME-TIFF is an open, metadata-rich, multi-dimensional, multi-resolution data format for modern bioimaging that has been widely adopted across the bioimaging community.


We have used Bio-Formats and OMERO to build solutions for sharing and publishing imaging data. The Image Data Resource (IDR; includes >260 TBytes of image data linked to >100 independent studies from genetic, RNAi, chemical, localisation and geographic high content screens, super-resolution microscopy, single cell profiling, light sheet microscopy of developing organisms and tissues, and digital pathology. Datasets range from several GBs to tens of TBs. Wherever possible, we have integrated image data with all relevant experimental, imaging and analytic metadata. These annotations make it possible to re-use IDR data, and to connect independent imaging datasets by molecular perturbations and phenotypes.


We have built cloud-based analysis tool portals to catalyse the re-use of published imaging data. These include notebooks and Docker containers that package well-known tools like ImageJ/Fiji, CellProfiler and Ilastik, making it easy to view and interact with IDR data.  We are also developing new data formats based on Zarr, N5 and other cloud-competent binary vessels to improve adoption of modern cloud technologies in bioimaging.