Good Girl, Scientist, Yogi

Anastasiia Prytuliak on materials science, life in Japan, Ukrainian resourcefulness, and building a new data repository

30 Sep 2026 Vladimíra Coufalová

She chose materials science at sixteen because her father had studied it. “I’ve always been a good girl,” says Anastasiia Prytuliak with a laugh. She later pursued research in France and Japan, but after having a child in Japan, she discovered that combining a scientific career with motherhood would not be easy. She began teaching yoga and working as a coach. Today, in a way, she has returned to materials science: at the Heyrovský Institute of the CAS, she is helping to build a data repository designed to help researchers store and find their data so that they do not end up forgotten in a drawer.

You are building a repository for materials science data, and you yourself have a PhD in materials science from Kyiv. What attracted you to the field?

To be honest, I went where my dad had studied. I finished secondary school at sixteen and didn’t really know what I wanted to do. On top of that, I could only apply to one university. So I chose the one my dad had attended. He was an associate professor in materials science.

You then continued your research career in France and Japan. But in Japan, you started teaching yoga and working as a coach. How did that happen?

After I had my child in Japan, I discovered that it wasn’t possible to work part-time as a researcher. The childcare system also meant that I had to pick up my child as early as noon. I had been practising yoga since university, so I started teaching it and also worked as a life coach for foreigners.

Did you find that fulfilling?

It suits my personality better than scientific work. But I’ve always been a “good girl”, so even though I chose materials science because of my father, I was good at what I did. I always got the best grades – and now I’m in the Diamond League on Duolingo.

You no longer work directly in research, but in a way you have returned to materials science. As part of the Open Science II project, you are helping to build a new repository. What exactly are you responsible for?

I’m responsible for developing the DANTEc repository, from gathering requirements from the community to preparing documentation. Later, I’ll also be responsible for running it. Even though science isn’t exactly my “passion”, I had already started working in project management in my previous job in the private sector. At the Heyrovský Institute, what I studied has come together nicely with my work as a project manager. And because I have research experience myself, I understand what researchers need.

Why do researchers need a repository like this in the first place?

One of the key questions is what happens to data once the research is over. When I worked in Japan, I recorded my data in a paper lab notebook in Ukrainian. That notebook is still sitting in the lab there, so I doubt anyone will ever go back to those results. We sometimes have problems transferring knowledge even within a single laboratory. And we hardly ever share unsuccessful research, even though doing so could save others a great deal of time.

That’s why we need to describe and share data in a way that makes them easy to find, access, combine and reuse. With the rise of artificial intelligence, this is becoming even more important, as training models requires large amounts of well-described, interoperable data. DANTEc will also be connected to the wider European research data ecosystem, helping make research data more accessible and reusable across Europe.

Can the repository also be useful for companies?

Definitely. I used to work for one of the largest manufacturers of polymer materials in the Czech Republic, and I know from experience that even large companies can find it difficult to discover exactly what researchers are working on. A company might be looking for someone researching a particular material that is important to its business. A repository could help it find that information, compare available data, and identify potential partners.

Connecting academia and industry is still quite difficult. This could be one way to make collaboration easier.

How do you convince researchers who are not used to storing and sharing data in this way that it is worthwhile?

“We need to describe and share data in a way that makes them easy to find, access, combine and reuse. With the rise of artificial intelligence, this is becoming even more important, as training models requires large amounts of well-described, interoperable data.”

It’s difficult. I think real change will come with the next generation. If working with data in this way becomes standard practice for students, it will become a natural part of research. But even today, there are many people in the MATECH community, which focuses on materials science, who want to get involved.

We don’t want to dictate to researchers how they should work with their data, so we are finding out what they actually need. At the same time, we are trying to make storing data as simple as possible, for example by connecting the repository to electronic lab notebooks or enabling data to be uploaded directly from instruments via an API.

What are the main steps involved in building the repository?

A lot of it is about communicating with researchers. We need to know how they will want to search for data, what information matters to them, and which features they can do without.

A good metadata model is fundamental. Michal Med, the author of the Czech Core Metadata Model for Research Data (CCMM), compares it to a bottle of beer: the data are the beer, while the metadata are the label telling you what’s inside. Without the label, you don’t really know what’s in the bottle.

Then there are the technical and legal aspects. We are building the repository on the Invenio platform and developing the rules for how it will operate and connect to other services. We are trying to set everything up so that storing and finding data is as easy as possible for researchers.

What is your role in all of this?

“We don’t want to dictate to researchers how they should work with their data, so we are finding out what they actually need. At the same time, we are trying to make storing data as simple as possible, for example by connecting the repository to electronic lab notebooks or enabling data to be uploaded directly from instruments via an API.”

My main role is to bridge the needs of researchers and the technical side of the repository. I gather requirements from the community and help translate them into the metadata model and specific features. Together with the Czech National Library of Technology, I am also involved in developing controlled vocabularies.

What does a controlled vocabulary do?

It helps connect different terms that refer to the same thing. One researcher might use the abbreviation “XRD”, another “X-ray diffraction”, and another the Czech term “rentgenová difrakce”. We need the repository to recognise that these all refer to the same method so that it can find the relevant data regardless of which term is used. In DANTEc, we might use “X-ray diffraction” as the preferred term while linking it to the other terms in the vocabulary. This means searches do not have to rely solely on exact word matches but can also take meaning into account.

If you were to return to the lab as a researcher, what would you want from the new repository?

“My main role is to bridge the needs of researchers and the technical side of the repository. I gather requirements from the community and help translate them into the metadata model and specific features.”

First of all, I wouldn’t want to go back to the lab as a researcher. (laughs) But I would want entering data to be easy and to be able to learn how to use the repository quickly. I’d appreciate a short online training session or video that explained not only how to enter data, but also why doing so is useful to me.

As a researcher, it might not even occur to me that well-stored data could help me collaborate with industry or work with artificial intelligence. And of course, I would want to be able to return to my data whenever I needed to.

You have lived in Ukraine, France, Japan, and now the Czech Republic. What do you carry with you from Ukraine, wherever you live?

Everything. I will always be Ukrainian. It is the biggest part of my identity. I think Ukrainians are characterised by a certain flexibility and an ability to make do with what we have. We have never had many resources, so we have had to be creative.

Sometimes people from other countries tell us that something will take years to learn. But we’re used to finding a way. You have nothing, and you have to build a rocket out of it. We’re used to getting the most out of very little.

“As a researcher, it might not even occur to me that well-stored data could help me collaborate with industry or work with artificial intelligence.”

Anastasiia Prytuliak

is originally from Kyiv, where she studied materials engineering and earned her PhD. Eighteen years ago, she moved to Japan to pursue a career in research. At the National Institute for Materials Science (NIMS) in Tsukuba, she worked on advanced materials for energy applications. From 2012 to 2015, she was a postdoctoral researcher with the European Space Agency (ESA) in Grenoble, based at the international research facilities ILL and ESRF, where she specialized in neutron and synchrotron diffraction. She later returned to NIMS, where her research combined experimental work with image analysis and machine learning.

She has lived in the Czech Republic since 2022. Before returning to academia, she worked in research and development for a leading manufacturer of polymer materials. She currently works at the Heyrovský Institute of the CAS as the DANTEc repository manager, drawing on her extensive experience with experimental data, international scientific communication, and interdisciplinary collaboration.

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