More than 90 postgraduate students participated in the Advanced Microscopy and Imaging Autumn 2024 subject at the University of Technology Sydney. As part of their assessment, students performed a fluorescence microscopy experiment and acquired imaging data during practical classes. This resulting data provided a rich dataset that might be a valuable resource for developing future teaching tools or research data. Yet, the data generated by students could be lost due to a lack of structured data management and centralized repository storage, which impacts its potential for reuse.
To overcome the loss of students’ imaging data, this research aimed to aggregate and centralize these data in alignment with FAIR data principles [ 1]. This was achieved by organizing and uploading data with its associated metadata and microscope methods to OMERO, an open-source repository for managing biological imaging data [ 2]. A standardized naming convention and centralized experimental, image and microscope metadata management were further developed to ensure consistency and facilitate data findability and reusability. This approach allowed over 5000 images to be aggregated, corresponding to data from 16 different student groups. Each group performed a pilot drug discovery experiment using one of four potential anti-cancer therapeutic agents with different experimental variables such as drug concentration, fluorophores and imaging parameters. A comparison of search time in seconds of randomly chosen images revealed a reduction in search time following naming and centralization of datasets in OMERO.
This research also aimed to aggregate the imaging data to perform a reproducible image analysis pipeline using FIJI, an open-source image analysis software [ 3], to demonstrate the potential for reusing students’ imaging data.