At the beginning of October, another EOSC CZ Networking meeting occurred in Ostrava. On this occasion, we spoke with Professor Jan Platoš, the newly appointed Vice-Rector for Science, Research, and Doctoral Studies at VŠB – Technical University of Ostrava. In the interview, he explains why proper data management is key to high-quality research, how the university is nurturing a new generation of data stewards, and why open science must be a natural part of modern academic work.
Research in time series and data streams is very close to real-world needs – typically in predicting electricity, gas, or other commodity consumption. Predictive models have wide applications in industry, for instance, in predictive quality control or maintenance, where they help detect potential problems before they occur.
The quality of data is crucial. You cannot achieve accurate results if data are not managed or stored. Transparent data management allows methods to be compared, their benefits evaluated, and experiments replicated – which is the foundation of trustworthy science.
The biggest challenge is awareness and user-friendliness. Researchers need to understand why these principles exist, how to apply them, and – most importantly – how they can benefit their research. To ensure widespread adoption, tools for storing and sharing data must be as user-friendly and straightforward as possible, which unfortunately is still not the case.
“The quality of data is crucial. You cannot achieve accurate results if data are not managed or stored.”
At the university, we are gradually building a comprehensive open science support system – we organise training, educate, and newly employ data stewards who assist researchers in managing their data. We aim to make the principles of open science accessible not only to experienced researchers but also to doctoral students through our Ph.D. Academy. We are also preparing a summer school for data stewards and other training activities to expand this area further.
The ideal scenario is that open science principles and proper data management become integral to every researcher’s daily routine. I don’t think we are lagging in this regard. Thanks to the activities we are implementing and those we are preparing, we are keeping pace with developments across Europe. We aim for the next generation of researchers to regard these principles as a natural part of scientific practice.
“The ideal scenario is that open science principles and proper data management become integral to every researcher’s daily routine.”
These meetings are extremely valuable. They help share experiences, establish collaborations, and spread examples of good practice. In the future, I would like to see an even wider range of participants involved so that the principles of open science and responsible data management can spread even faster throughout the academic community.
The rise of artificial intelligence and generative models is definitely the reason. They represent a giant leap forward – the availability of data and tools has opened up opportunities for new applications and more precise algorithms that were not possible just a few years ago.
has been Vice-Rector for Science, Research, and Doctoral Studies at VŠB – Technical University of Ostrava since 2025. His research focuses on adaptive algorithms, data stream analysis, and concept drift in data models. His work bridges theory and practice, developing intelligent systems applicable in energy management, digital media, and intelligent networks. He also employs evolutionary and nature-inspired algorithms to improve feature selection, classification, and time-series prediction.
On 7 October 2025, the EOSC CZ initiative organised a regional networking meeting at the VSB – Technical University of Ostrava (VSB-TUO), bringing together representatives from three Silesian universities – the Silesian University in Opava (SU), the University of Ostrava (OU), and VSB-TUO.
Helena Reichlová, head of the Dioscuri Center for Spin-Caloritronics and Magnonics at the Institute of Physics of the Czech Academy of Sciences, discusses the challenges and opportunities of modern experimental research. She talks about the importance of international collaboration, interdisciplinary teams, and sharing scientific data.
