AI-Enabled Scientific Imaging and Research Data Management Platform

The project supported the development of a specialized digital platform for scientific and industrial users who work with microscopy images and related research data. Such workflows involve complex visual records, multiple observation levels, and collaborative review across research teams.

The platform was designed to bring these activities into a structured digital environment, with technical implementation undertaken through a partner-led delivery model.

Centralized Microscopy Data Management

The platform provided a structured environment for creating, classifying, and locating research records.

Key capabilities included:

• Unique identification codes for individual items
• Classification of microscopy records and related information
• Support for images captured at different magnification levels
• A consolidated interface for accessing images, details, and documentation

Image Annotation and Visual Documentation

Interactive annotation tools helped researchers highlight and communicate findings directly within visual records.

The implementation supported:

• Drawing lines and boxes on images to identify areas of interest
• Attaching contextual observations to the relevant record
• Reviewing marked images alongside associated information
• More consistent communication of image-specific findings

Hierarchical Data and Advanced Visualization

The application supported relationships between complex records and the use of additional visual references.

Capabilities included:

• Parent–child structures for records containing related sub-items
• Visual indicators for items requiring attention
• References to 3D video and contextual URLs
• Navigation between related data and associated visual content

Collaborative Review and Approval

The platform consolidated activities previously difficult to coordinate across separate files and tools.

The workflow included:

• Comments associated with images and data records
• Administrative approval and rejection of submitted items
• Review of record details and supporting images within the application
• Resolution of issues through a shared review process

Activity Tracking and Traceability

Recorded actions provided visibility into the progress and history of research information.

Features included:

• Logs of activities and record changes
• Historical context for the progression of individual items
• Improved visibility into review and administrative actions
• A more traceable basis for collaboration and quality control

The published functionality included controls relevant to the governance of scientific data workflows:

• Administrative approval and rejection of submitted content
• Activity logs recording changes to data items
• Traceability of review and modification activity
• Structured data classification and record relationships
• A controlled workflow for documenting and reviewing observations