Erick Martins Ratamero - Expanding the OME ecosystem for imaging data management | SciPy 2024

OME (Open Microscopy Environment) is a consortium of institutions creating a common data model for microscopy data management

OMERO is a client-server application built around the OME data model, providing:

• Web-based visualization and annotation
• Python API for programmatic access
• User/group management and permissions
• Postgres database for metadata storage
• Immutable original image storage

Bioformats is a core library that can read 100+ proprietary microscopy file formats, making multi-vendor data access possible

Two key developments expanding the ecosystem:

• EasyOMERO: Simplified Python interface providing cleaner, more Pythonic access to OMERO functionality
• OMERO CLI Transfer: Tool for moving data between OMERO servers while preserving metadata and annotations

The OME ecosystem is being adopted broadly:

• Used for petabyte-scale imaging data management
• France’s national bioimaging effort using it for archival
• Integration with bioimage archive formats
• Growing community contributions and plugins

Future developments include:

• Addition of OME-NGFF (Next Generation File Format) specification
• Support for ZAR format
• Enhanced plugin interfaces
• Improved support for very large images (>100k pixels)

System is highly extensible through:

• Python plugins
• Web frontend extensions
• Custom annotation types
• Integration with analysis tools

Original data remains immutable while annotations and metadata are stored separately in database