Setting up an institutional OMERO environment for bioimage data: Perspectives from both facility staff and users

Area of Science:

• Life Sciences
• Biotechnology
• Scientific Computing

Background:

• Core facilities are vital for managing advanced bioimaging instruments and supporting researchers.
• Effective management of large, diverse bioimaging datasets is a significant challenge.
• Ensuring data compliance with FAIR principles (findable, accessible, interoperable, reusable) is crucial for scientific advancement.

Purpose of the Study:

• To detail the successful implementation of the OME Remote Objects system (OMERO) for bioimage research data management (RDM).
• To address the challenges encountered during the adaptation of data handling and storage to a new RDM system.
• To provide insights and recommendations for implementing OMERO in institutional bioimaging facilities.

Main Methods:

• Implementation of the OME Remote Objects system (OMERO) at the Core Facility Cellular Imaging (CFCI).
• Introduction of standardized group-specific naming conventions for bioimaging data.
• Metadata curation using tagging and Key-Value pairs.
• Integration of existing image processing workflows with the OMERO system.

Main Results:

• Successful implementation of OMERO for managing multidimensional bioimaging data.
• Established standardized data handling practices, including naming conventions and metadata curation.
• Demonstrated integration of existing image processing tools with the new RDM system.
• Ensured compliance with FAIR data principles for enhanced data accessibility and reusability.

Conclusions:

• Tailored decisions and structured approaches are key to successful RDM implementation.
• OMERO provides a robust solution for managing complex bioimaging data in core facilities.
• Sharing implementation experiences can guide other institutions in adopting effective RDM strategies.