BIA seminar series 2025-2026

The primary goal of this seminar series is to provide a dynamic platform for bioimage analysts, enabling the community to stay up to date with the latest developments in the field and foster community interactions. The seminars are designed to cater to intermediate and advanced analysts, focusing on practical, high-level content that extends beyond basic instruction.

Target Audience

The seminars are tailored for bioimage analysts who have intermediate to advanced knowledge in the field. This includes professionals and academics who are currently practising or researching within the domains of bioimage analysis, microscopy, and related life sciences. Themes are designed to cover relevant aspects and latest “news” of bioimage analysis, ensuring a comprehensive learning experience for intermediate to advanced analysts. Each session may feature one or two talks, depending on the complexity of the topic and the expertise of the speakers. 

The seminar series will concentrate on a topic for three sessions in a row. The seminar will usually be in the last week of the month, but to help engagement of the global community we will not have a fixed day and time. 

Planned topics so far include:

• Image data, file formats, image data management – current state and challenges 

• How to manage and optimize the data flow between the instruments, the users, the analysts, the storage providers? 

• Insight into careers as BioImage Analysts

• Python Libraries for Bioimage Analysis: A deep dive into Python tools that are essential for modern bioimage data processing and analysis. 

• to be continued.....

Registration

Please register for the seminar series here: BIA seminar series. 

The registration will be used to send you the link to the seminar sessions. You will be registered for all upcoming GloBIAS seminar sessions in the future.

Second topic

How to manage and optimize the data flow between the instruments, the users, the analysts, the storage providers? 

Big data infrastructure strategies for image analysis in a core facility

Nicholas Condon, Institute for Molecular Bioscience, UQ, Australia

Wednesday 1 April 2026, 13:00 CE(S)T

Abstract 

Modern bioimaging facilities generate unprecedented data volumes, and the challenge is no longer simply storing these datasets—it is ensuring they can move smoothly from acquisition to analysis to publication in a scalable, transparent and reproducible way. In this talk, I will discuss how our imaging platform at the Institute for Molecular Bioscience, at The University of Queensland (UQ) in Brisbane, Australia has developed and collaborated with the Research Computing Centre on an integrated digital infrastructure that supports the full imaging data lifecycle across storage, virtualised workstations, high-performance compute, and user-facing analysis platforms.

I will outline the principles that underpin effective data flow management in core facilities, including FAIR-aligned data collections, project‑level metadata, and automated provenance tracking. I will also present the virtualised GPU environments and HPC interfaces (such as our Image Processing Portal and Open OnDemand) that democratise access to large-scale processing for users with diverse skillsets and analytical needs.

By combining interoperable systems, controlled analysis environments, and simple web‑based interfaces to complex computational resources, we aim to reduce operational friction, address compliance requirements, and deliver reproducible, high-quality analysis at scale. The lessons learned may assist other facilities seeking to modernise their imaging data pipelines and support a rapidly growing community of data-intensive researchers.

First topic

Image data, file formats, image data management – current state and challenges 

Handling huge imaging data with OME-Zarr 

David Stansby, Kimberly Meechan, Ruaridh Gollifer, University College London, United Kingdom 

Wednesday 3rd December 2025, 1:00 pm/13:00 GMT / UK time 

Abstract 

OME-Zarr is a data storage format designed to enable efficient storage, visualisation, and processing of huge bio-imaging datasets. With this functionality comes additional complexity however, with many different configuration options and tools available to scientists looking to create OME-Zarr data.

To help scientists navigate OME-Zarr, we have written a new digital textbook (https://heftie-textbook.readthedocs.io/) to explain the theory and practice of using OME-Zarr. In this seminar, we’ll give a taster of the textbook content with:

1. A brief overview of how OME-Zarr works

2. A demonstration of how to configure and create new OME-Zarr datasets

3. An example of how to export OME-Zarr data back to other file formats

To finish, we'll give pointers to other useful tools and training resources for working with OME-Zarr.

Large-scale image visualisation, annotation, sharing and management with OME-Zarr and Webknossos

Norman Rzepka, scalable minds GmbH, Potsdam, Germany

Monday 26 January 2026, 4 pm/ 16:00 CET

Abstract 

Managing and analysing large volumetric image datasets has become a central challenge for many research groups and user facilities, as data volumes continue to grow and workflows become increasingly complex. This talk will outline practical solutions for handling such datasets efficiently, with a focus on emerging workflows that streamline data access, processing, and collaboration. I will introduce WEBKNOSSOS as a flexible platform for visualisation, annotation, sharing, and analysis, demonstrating how it supports both individual researchers and large-scale facility operations. In addition, I will discuss the OME-Zarr next-generation file format and its role in enabling scalable, cloud-ready, and interoperable data management across a diverse ecosystem of tools. Together, these technologies illustrate a modern approach to working with high-dimensional image data at scale.

Towards interoperable bioimage analysis at scvale with OME-Zarr 

Virgine Uhlmann, director, BioVisionCenter, Zürich, Switzerland

Monday 23. February 2026 at 2 pm/14:00 CET/ Zürich time (might be subject to changes)

Abstract 

Modern microscopy experiments generate terabytes of data, creating major challenges for processing and analysis. In this talk, I will present our recent efforts to build open-source tools to address these challenges relying on the OME-Zarr format: ngio, a Python library to facilitate interactions with OME-Zarr files, and Fractal, a computational platform for scalable and modular bioimage analysis workflows on HPC infrastructures.