The following interview was conducted by Sam Goven, a master’s student in Journalism at KU Leuven, with Dawn Zhuang, BiblioTech Hackathon participant. Dawn is currently the project manager and data coordinator for the research project RegInfra (Regionalizing Infrastructures in Chinese History). Dawn’s team, W@nder, worked with the travelogues collection. You can learn more about the team’s work by having a look at their project poster in the BiblioTech Zenodo community and by visiting their project website.
The BiblioTech Hackathon is a 10-day event organized by KU Leuven Libraries and the Faculty of Arts. Students, researchers, and staff members of KU Leuven worked in multidisciplinary teams with digitized collections from KU Leuven Libraries. The theme of the 2026 edition was travel, which was reflected in the selected datasets: historical postcards and historical travelogues. More information about the hackathon and its results can be found on the BiblioTech 2026 website.
To start off, could you tell us a bit about your academic background? Had you participated in a hackathon before, and what drew you to this one?
I’m currently working as a project manager and data specialist in the research group Regionalizing Infrastructures in Chinese History (RegInfra). My role combines digital methods with humanities research. I graduated from the Master in Digital Humanities three years ago, and that’s when I participated in the first edition of the BiblioTech Hackathon, in 2023.
That experience was a lot of fun, and I learned many new skills. It helped me see how the digital methods I learned during the program could be applied in a real project setting. On top of that, I made new friends throughout the hackathon, which is one of the main reasons I wanted to participate again this time.
On a more personal note, during the previous hackathon I worked with the postcard collection, and I noticed that the dataset was reused this year. I was curious to see how other groups would approach it. This time, I chose to work with the travelogue dataset, since it relates to the same overall theme. In a way, it felt like a continuation of an ongoing project.
Your team won the prize for best visualisation. Could you briefly describe your project?
We chose a small‑data approach and built an interactive map based on it. Starting from the travelogues dataset, we selected a small part of the larger corpus, specifically three volumes of The Book and the Land. We then visualized and mapped the routes described in those texts, as well as the stories that unfold along the way.
The result is an interactive map where users can click on nodes and routes to explore the journeys. Through this interface, they can see extracted illustrations along with their contextual information, which helps connect the visual material to the narratives in the travelogues.
As you mentioned, you had already participated in the first edition of the BiblioTech Hackathon. What were your expectations at the start of this one, and did you feel well equipped for the project?
Because techniques and AI have developed so much in recent years, I expected to learn even more this time, especially since the methodologies have evolved as well. I was also working with a different dataset, so overall I was really looking forward to trying out new approaches and learning new things with a different group of teammates.
At the same time, I did feel well equipped. During the first hackathon, I was still a student and everything felt very new to me. Now I already have some working experience with digital projects, and I can really see how my skill set has grown. I felt more confident this time and was happy to realize that I was able to take on more complex tasks.
At the ‘Meet the Data, Meet the People’ event, you were introduced to the data for the first time. What was the brainstorming process like? Did you feel overwhelmed with ideas, or was it clear early on which direction you wanted to take?
I’d say that during brainstorming you always get little sparks of ideas here and there. In our team, we had people from very different backgrounds, linguists, historians, and AI experts, and everyone just shared what they were thinking. At our first meeting, we didn’t go through the entire dataset yet, and some of the initial ideas turned out to be a bit too ambitious or not very practical in the end.
Still, I think the general direction was already quite clear early on. During the brainstorming phase, we decided fairly quickly that we wanted to work with an interactive map, and in the end that’s exactly what we managed to accomplish. After the weekend and one of the training sessions, we had an in‑person discussion where we exchanged our observations about the dataset and then pinned down a more practical pipeline and timeline to work with.
What’s interesting is that during the brainstorming itself, none of us really knew yet how we were going to do it. And somehow, through discussion and experimentation, it all came together. It’s a bit of a magical experience.
Could you describe your role in the project? Was it in line with what you were expecting?
I’d say it pretty much aligned with my expectations. I see myself as a digital humanities enthusiast, and through my experience I’ve become familiar with a range of tools and platforms that can help achieve different kinds of results. Within the team, I mainly took on a supportive role, contributing from the early exploration of the dataset to deciding which direction we should take.
I also have some experience with web design, so I ended up putting most of my effort into building the final webpage. Overall, I like working on different aspects of a project: trying out new techniques, moving between tasks, and supporting my teammates wherever needed.
Did you face any problems or roadblocks that you had to overcome during the project?
I think the most challenging part was moving from the initial idea to something concrete and practical. Before this project, none of us had experience linking data to a map and making it fully interactive. So while the concept was clear, the question was how we could actually realize it, what tools or platforms we could use, and how to build everything within the limited time we had.
We spent quite a bit of time and energy figuring out how to translate our idea into a realistic workflow and deciding what was feasible within the time constraints. I’d say that phase, moving from the blueprint to an actual work plan, was definitely the toughest part of the project.
Did you face any technical problems along the way, situations where things didn’t work as you had expected?
Initially, we wanted to retrieve the dataset directly from the ManGO platform. I tried running the code within the HPC environment, but I ran into a few issues. I then posted my question to the expert pool in MS Teams, and I received a lot of help.
The support was also very timely, I posted my question in the morning, and by the afternoon there was already a working solution. The expert team really provided solid support, which made a big difference in helping us move forward.
You already mentioned that during your first hackathon you picked up a lot of new skills. Did you have the same experience this time, and how might you use those skills in future projects?
Yes, definitely. I learned a lot from this project as well. For me, working with geo‑referencing and data conversion was completely new, and it’s actually quite relevant to my current work. I can definitely see myself using these skills in future research projects or for creating other visualizations.
Although our project didn’t ultimately rely on the HPC environment, I did participate in the training sessions and did some exploration on my own. I really appreciated the opportunity to work within that environment, especially because future projects I’m involved in will likely have some connection with the HPC. So for me, it was very good practice and a valuable learning experience.
What kind of advice would you give someone who is participating in their first hackathon?
I would say: think bold. There’s a lot of support available, and you’re surrounded by a great team of experts who are there to help you. If you allow yourself to think ambitiously and take a few risks, you’ll be surprised by how much you can accomplish by the end.
Lastly, how would you describe your overall experience?
For me, it was truly inspiring and very enjoyable. And something I didn’t mention earlier is that I really made good friends through the hackathon and learned a great deal from my teammates, as well as from the other groups. That’s a very precious takeaway for me.
