Connecting at GloBIAS Kobe

This article was written by Eric Hidari, Senior Bioinformatician at the Wellcome Sanger Institute in the UK.

Why would one attend an academic conference? In the past, I attended them without thinking much about the reason – being in academia, it feels like part of the job to learn, present, and network in such situations. Never have I truly felt a sense of “connection” until I attended the GloBIAS 2025 bioimage analysis conference in RIKEN BDR, Kobe, Japan. To connect is the main reason I signed up for GloBIAS Kobe; luckily for me and all the participants with the same goal, the organising committee has seemingly sensed the idea and provided plentiful opportunities for us to connect. So one may ask, what is the difference this time from the past conferences I attended? Does “networking” have the same meaning? In the following, I will break down my experience of “connections” at GloBIAS Kobe, and therefore how this conference felt unique to me.

Connecting to each other

I have followed the president of GloBIAS, Kota Miura, through Twitter (X) back in the days when I was a research student, analysing fluorescence images of dementia-related protein aggregates. However, it appeared to me at that time that bioimage analysis is merely a necessary step of my research, even though it took a significant proportion of research time. There was very little guidance from my immediate circle, and I never thought about attending a conference just for the topic of bioimage analysis.

Fast-forward to 5 years later, as a core facility bioinformatician and software developer, I had already left active academic research and image analysis behind a couple of years ago. It was on X again that I learned about the first GloBIAS conference in 2025. “A good opportunity to finally meet Kota in person!” I said to myself. Reading through the conference agenda, I found out about the “Taggathon”, curating bioimage analysis tools and workflows (more on this in the next session); talks from academics and core facility research developers alike; software demonstration in the open area; and many networking events. This conference felt very different and friendly. By intuition, I signed myself up for the Taggathon and talks.

It turns out my hunch could not have been more accurate. GloBIAS 2025 Kobe genuinely felt like a community gathering, rather than a typical academic conference. Connecting to many bio-image analysts across the globe, who work in isolation and share similar experiences – lack of guidance, unaware of what other image analysts are doing, being under-appreciated (sometimes under-funded too) for providing highly technical services, it is almost therapeutic to learn that we are not alone in facing the problems we have.

Besides gaining knowledge about new software and platforms that are potentially useful for future work, I got to know the people in the team that developed them and heard about their stories. This is important because they provide the depth and context of what makes these tools unique. napari is a tool I discovered during the conference, and after hearing the talks and watching the demo, I really wish I had known it when doing my PhD research, when I struggled with improvising custom glue scripts between python and ImageJ. After I came back from Kobe, I immediately recommended it to my colleagues who are doing image analysis. Another example is hearing from the main author of MorphoLibJ, David Legland, talking about his consideration of measuring object morphology from a mathematical point of view. A plugin like this is so universal that I took its performance for granted, yet it contains certain assumptions, even something as simple as the definition of the “centroid”, that are necessary for us image analysts to know because it may impact how we interpret the data. This turned out to be immediately useful as weeks later I was faced with the exact same centroid definition problem in a project. After the conference seminars, I was given a tour around the microscopy facility within RIKEN BDR. As a microscopist myself, seeing the engineering behind data collection is always a fascinating experience. I was particularly impressed by an example showing that new image analysis algorithm has resulted in a simplified experimental process, which increased the throughput of the assay.

Meeting Kota himself was an unforgettable experience. His charm, leadership, and over a decade’s dedication to the community were evident throughout the conference. He would dress in Haori with a few other organisers, drink Japanese sake, make jokes about conference training school while filling the time when there was a powerpoint presentation technical issue. He would come personally and express appreciation to a member just for taking on a task voluntarily. I had a genuinely enjoyable time when working directly with him during the Taggathon.

My favourite anecdote, however, is that I got to meet the author of the Microscopy Nightmare video series in person. Check it out, it is really clever (or shall I use a different word?)

Connecting knowledge

The “Taggathon”, likely a word coined by Kota Miura, is a signature event for past NEUBIAS (the European predecessor to GloBIAS) conferences. Although it is the first time I heard about the word, the concept of curating software for bioimage analysis is not unfamiliar to me. I work in the same research campus as the European Bioinformatics Institute, which hosts a large number of online resources curated through decades of hard work. Yet, the target of Taggathon, the website biii.eu, standing for Bio-Image Informatics Index, goes beyond my understanding of a typical software depository. It contains datasets, software and training materials, and within the software category, it contains component (individual tool), workflow, and collections. It is a digital encyclopaedia to connect knowledge for bioimage analysis, and to guide new and experienced researchers alike. It is definitely on the list of items I wish I had when I started my research career.

Now comes to the Taggathon itself. Unlike the hackathon I attended before, when I faced the code editors for a good chunk of the day, we spent quite some time in nicely-paced presentations about analysis software and workflows of diverse categories, as well as the discussions that followed. These really helped us to get into the “curation” mode. As a curator, we are not just filling out the metadata; rather, we incorporated our individual experience of using the software into the description, like telling a story. Since nobody here had been in the Taggathon before, Kota had been patiently explaining the process to us and setting up the expectations. As soon as I found myself finally getting to the task of curation, I was running out of time. Nevertheless, I was amazed by how much my teammates had achieved. As a whole, we added 26 new entries, made 11 edits, and modified 1 each of training material and dataset. Feeling that I had not made enough progress on the curation, I put myself up for presenting our Taggathon results to the GloBIAS Kobe seminar audience. To me, it was an amazing experience. Not only did my teammates support me in preparing the report, but the audience’s warm reaction to our hard work was truly satisfying. Together with the other 2 hackathons, we demonstrated the liveliness of knowledge generating and connecting in real time, beyond a mere snapshot of past work.

As with many fields these days in computational science, we naturally started to discuss the impact of artificial intelligence. Intuitively, AI is going to replace the position of human curator. But is that an accurate depiction of the bioimage analysis software landscape? We did not think so. Without using the software on real samples and datasets, it is difficult to define and compare software in terms of their scope and usefulness. However, large language model-based AI could be relevant in at least 2 ways. First, it could help a curator to fill out mundane metadata such as software name, language, license, etc, and let the curator focus on fields that require human intellectual input. Second, the curation itself is a major step towards making the platform AI-ready. In other words, an AI agent could effectively interact with biii.eu and give suggestions to human users of what tools to use, or conduct bioimage analysis autonomously, based on the curated information. Just as we witnessed PDB leading to AlphaFold, high-quality human curated data is a pre-requisite to building a practically useful AI agent system.

Connecting within oneself

I believe the particular aspect that makes GloBIAS Kobe unique is that it focuses on not just what we do, as in a typical academic conference, but how we do it. The emphasis on the research journey is encouraging us to reflect and discuss the problems and challenges we are having. As academics, we tend to spend effort on polishing our results and making them shiny before publication. But what about the tools we create and use, the approach we take to make the research possible? Are there any improvements we can make to reduce the frictions in research? I can relate to many of these aspects as a research IT professional, ranging from high performance computing, data management, software development to communicating with academic users. I was particularly glad to contribute by bringing the software installation solution from my research institute to the conference Open-Source Software Lounge session, and promoted open and reproducible research software according to FAIR (Findable, Accessible, Interoperable, Reusable) principles. GloBIAS, as a community that goes beyond the conference itself, helps us highlight the values we created as engineering and process achievements, and provides a network of support.

During the conference, it became clear to me the diversity of interests that bioimage analysis is intersecting with, from science, software engineering, to academic services. For me personally, it reflects the career journey I have experienced. I can vividly feel the connection of concepts and ideas within myself, among my past career experiences. A major concept that I have been shaping in my mind, and gained many inspirations during the conference, is research engineering. While almost all modern day research projects require software to perform certain tasks, it is usually not in the best interest of the scientists to spend their time learning software engineering skills and principles. As a result, custom and bespoke software that is difficult to adopt elsewhere prevails in the academic software landscape. From the Taggathon and platforms like biii.eu, we highlight the issue rather than provide a solution.

The proposed role of research engineer within a scientific project is a parallel yet highly complementary pathway with research scientists. With the right tooling, support and deep engagement, they could make efficient use of available resources, optimise research process and therefore benefit all parties in research. In addition to software, the AI boom has provided application opportunities in other aspects of research, such as idea gathering, learning and operational tasks, where research engineers could further utilise their technical proficiency to test and tailor new AI tools for the project. I am hoping to work on establishing research engineer as a more defined career path, by collaborating with like-minded people, who have diverse perspectives and experiences. Owing to this GloBIAS Kobe, outreaching opportunities now seem much clearer to me.

To conclude

Thanks to the organisers of GloBIAS Kobe, and thanks to the great hospitality of RIKEN BDR, the city Kobe and the country Japan. I cannot stress enough how much fun I had with all the social and cultural elements carefully offered by the conference staff. When I went up to the mountain overseeing the city (Rokko mountain), witnessing that all the above took place at a tiny dot on an artificial island, it was a humbling yet encouraging experience. It reminds me of how much of the world is yet to be explored, and how much we could potentially achieve.

For all the friends I met in Kobe, I hope our paths will cross again; for future readers, if you are interested in GloBIAS, please come and join our journey.

Eric Hidari

Senior Bioinformatician

Human Genetics Informatics

Wellcome Sanger Institute

Hinxton, Cambridgeshire, CB10 1SA

U.K.

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