Networking at the Technical University of Liberec: Professor David Lukáš on the Importance of Open Science and Long-term Research Data Preservation

We were honoured to welcome Professor David Lukáš, Rector Emeritus of the Technical University of Liberec, who is a renowned expert in the physical principles of polymer nanofibre formation. After the event, we had the opportunity to speak with him about his views on open science and the importance of long-term research data preservation. Professor Lukáš emphasized that such data are crucial not only for scientific advancement but also for innovation in research. In the interview, he shared his thoughts on the future of scientific work and the challenges of data management in a rapidly evolving scientific landscape. Let his insights inspire you!

As an expert in nanofibers and an experienced academic, what do you see as the importance of open science in the context of contemporary research? Do you believe that data sharing among scientists accelerates scientific progress?

I'm even convinced of it. There are disciplines that are far more data dependent than what we do. Just to give you an idea of what we do - in addition to basic research on so-called electro-hydrodynamic instabilities, we are involved in the application and fabrication of nanofibers. The applications are in the field of biology and medicine. The data generated here are in the form of images or micrographs, which are obtained either from electron microscopy or from confocal and fluorescence microscopy. For example, we measure fibre diameters, fibre orientation and pore size. Once the nanofibrous material has interacted with the cells, it is useful to characterize some features of the cell population, such as its density. So storing these images is very, very useful. We are trying to do it on our own, but image data has huge memory requirements, so we usually can't do it in full.

In the past, you mentioned that correct analysis often occurs after some time, and data needs long-term preservation. How crucial is data storage for future analyses, and how does it impact scientific research in your field?

You know, during my academic work I have encountered several situations where it was necessary or very useful to use data from another author. One example is when we started working on the theory of electrospinning, where polymer nanofibers form under an electric field. One of the key pieces of information for our work was the so-called critical value of the electric field that causes nanofibers to start forming from the polymer surface. Similar experiments were carried out in 1914 by our compatriot John Green in the United States. This Honza did a great experimental work during which he measured a quantity called electrostatic field strength (which is difficult to detect) through hydrostatic pressure. We only had his graphs, not the raw data. And since we were doing something similar, but with a new theoretical approach than our predecessors, we needed to compare his results with ours. We zoomed in on his graphs, scaled them, and found that our theory agreed with his measurements. That's when I realized how important it is to keep data. Because often when you propose a new theory, you search the literature for data that you can use to compare with your theoretical predictions. This is key to scientific progress - theorists are not always skilled experimenters, and this is how they can benefit from other scientists' experiments, as long as their data is available and properly preserved.

How do you perceive the role of universities in promoting open access to scientific data and in training researchers in research data management?

I think events like today’s are essential. Universities and research institutes have two main functions. One is basic research, not intended for commercial use, which can’t be patented. The other involves commissioned work for private entities or work where researchers intend to file patents. It’s crucial to find a balance between open access and protecting results. Discussions at the university level are key to deciding which data should be shared and which require protection. Financial costs associated with data preservation must also be considered. I believe universities can play a pivotal role in collaboration with the Ministry of Education, even convincing the minister of the need for investments in this area. If funds can be obtained to build data repositories, ideally at the national level, that would be ideal. I think we are moving toward the need for robust infrastructure to support scientific activity across institutions.

What do you see as the main challenges in today’s research data management, not only for individual researchers but also for entire research teams and institutions?

Challenge – a somewhat philosophical term that gets used a lot. And there are indeed many challenges. Economic aspects, as I’ve mentioned, are one. But another is the way we think about what such large data repositories can actually serve and how they can benefit us.

My estimate, though possibly inaccurate, is that these repositories could be an ideal resource for training what we now call artificial intelligence. Human researchers can no longer efficiently search and process data from repositories of this scale. Here, artificial intelligence could significantly help – both in training and in making these results accessible back to people.

The very last question concerns the EOSC initiative, which develops a data infrastructure and promotes the long-term preservation and sharing of scientific data Do you think it is important that scientists and researchers have access to this service?

The answer is very simple - undoubtedly yes. Dot.

But I would like to go back to the previous question. As I was thinking about this interview, an analogy came to my mind. I was reminded of a quote by Isaac Newton, who said: "If I have seen further [than others], it is by standing on the shoulders of giants.“ You know, this is my personal opinion, and I may be mistaken, but I don't think it's true anymore in the way Newton described it. Today's science is structured a little differently. I feel that nowadays most scientists, including us, are more like dwarfs standing on a huge pyramid of other dwarfs and we can only see a little bit further from there. It seems to me that science today faces huge peaks that we have to climb over gradually, i.e., like climbers through many camps. We do this by gradually accumulating small work, mostly also over data for which we often don't even have a strong enough theory. That's why I think that at this stage in the evolution of science, huge data repositories, as part of the scientific pyramid outlined above, are extremely important.