Toward bioimage data science with a data-management-centric approach to microscopy

Session

Poster Session

Authors

Tom Boissonnet (1)

Affiliations

1. Heinrich Heine Universität

Keywords

Data management, image analysis, OMERO

Abstract text

The size and quantity of microscopy data, and the variety of acquisition techniques have significantly increased in recent decades. However, research data management (RDM) practices struggle to keep pace. Currently, data is often stored on personal computers and external hard drives, with sparse annotations, and experimental metadata frequently remains unlinked. Additionally, the specificity of research fields complicates the establishment of standards. In response to these challenges, various initiatives have emerged. Ours, named I3D:bio [1] (Information Infrastructure for BioImage Data), is focused on facilitating the deployment of OMERO [2] servers, the most widely used solution for managing microscopy images [3]. Leveraging a team situated across four microscopy facilities in Germany, we ground our expertise in the daily application of data management, providing support to our local research communities.

Based on the feedback gathered from our external use cases, where we assist in the deployment of OMERO servers, and drawing from interactions with individual researchers, as well as our own experiences, we have published a set of training materials [4]. These materials are designed for researchers new to data management and are intended to be utilized by core facilities as a means of support in disseminating our insights into the effective use of data management with OMERO. Furthermore, the experiences we accumulate aid us in identifying areas for improvement within OMERO, and we actively contribute to the open-source repositories of OMERO.web, its plugins, and other scripts used by the community.

For this presentation, I will showcase functional data management workflows. As a first example, I will demonstrate the effectiveness of data organization within OMERO. This enhances the visibility and comprehension of a project’s data and significantly reduces the burden of structuring data through an intuitive tagging strategy. As a second example, I will showcase how OMERO creates a collaborative environment for the exchange of data and results during bioimage data analysis. By providing APIs to various popular analysis tools, OMERO facilitates seamless collaboration. This demonstration aims to inspire the audience to embrace a data management-centric approach to microscopy data, fostering a more productive and collaborative scientific community committed to FAIR bioimage data science.

References

[1] https://www.i3dbio.de

[2] Allan, C., Burel, JM., Moore, J. et al. OMERO: flexible, model-driven data management for experimental biology. Nat Methods 9, 245–253 (2012). https://doi.org/10.1038/nmeth.1896

[3] Schmidt C., Hanne J., Moore J. et al. Research data management for bioimaging: the 2021 NFDI4BIOIMAGE community survey. F1000Research 2022, 11:638 https://doi.org/10.12688/f1000research.121714.2

[4] Schmidt C., Bortolomeazzi M., Boissonnet T. et al. I3D:bio's OMERO training material: Re-usable, adjustable, multi-purpose slides for local user training. 10.5281/zenodo.8323587