Author: Halyna Hyryavets

The foundation of fair and sustainable decision-making is participation — involving people in the processes that shape the land and environment they live in. However, if such processes are not well designed, they can lead to distrust, conflicts, and short-sighted solutions. 

The research team from the Slovak University of Agriculture in Nitra therefore sought a way to capture, analyse, and connect these diverse perspectives. Their goal was to understand soil as a form of social and cultural capital — a space that brings together economic, environmental, and human values. To achieve this, they needed to process extensive datasets reflecting public discussions, attitudes, and values related to land and soil across the European context. 

Solution

To better understand how different stakeholders perceive soil and its value, the team combined data analytics with participatory approaches. During the testing phase, they processed extensive textual data, expert documents, media outputs, and public statements that reflect societal attitudes toward soil and the landscape. 

The team applied text mining methods to process the data, enabling the identification of recurring themes, linguistic patterns, and emotional attitudes related to land use. This approach opens the door to new insights, allowing researchers to derive from data how opinions are formed, where tensions arise, and what values people associate with the landscapes they inhabit. 

The goal of the research is not merely to collect information, but to transform it into actionable insights that help build consensus among the public, experts, and policymakers. 

Use of HPC Infrastructure 

The analysis of such extensive textual data required computational power beyond the capabilities of standard workstations. Therefore, the research team used the computing infrastructure provided by NSCC Slovakia to carry out the data processing. 

In the testing phase, the computations were performed on a supercomputer using 128 core*h in an R environment, enabling parallel processing of large datasets within a short time. This approach significantly reduced the analysis time while allowing the application of complex methodological frameworks typical for social and environmental data — such as modelling relationships between actors, tracking the occurrence of key concepts, and visualizing linguistic patterns. 

Thanks to HPC computing, it was possible to: 

• process extensive text files from various sources without capacity limitations, 

• generate clear and structured data outputs that would take several times longer to produce on standard computers, 

• test the potential of the supercomputer for social science and interdisciplinary research that connects human behaviour, data, and spatial relationships. 

Results

The test computations confirmed that the use of high-performance computing infrastructure enables efficient processing and analysis of extensive textual data originating from various social, environmental, and cultural sources. By applying text mining methods, the team was able to gain insights into key themes and the relationships between different stakeholders involved in land-use decision-making. 

The analysis revealed significant differences in how various groups perceive soil and the landscape — whether in terms of economic, ecological, or value-based priorities. These insights help identify areas where misunderstandings and conflicts arise, while also highlighting shared values that can serve as a foundation for constructive dialogue. 

The research confirmed that the use of HPC infrastructure significantly improves data processing efficiency and enables complex analyses to be carried out in a timeframe that would be unfeasible with standard computing resources. This established a reliable foundation for the main phase of the project, in which the results of the testing stage will be expanded with new data sources and methodological approaches. 

The obtained results represent the first step toward developing a tool capable of linking quantitative data with social contexts — thereby contributing to a deeper understanding of the relationship between people, the landscape, and decisions regarding its use. 

Impact and future: 

The project confirmed that a high-performance computing environment provides significant benefits for social science and environmental research dealing with complex, unstructured data. The combination of social research and computational analytics has created a new approach that can be used to gain a deeper understanding of the relationship between humans, the landscape, and societal change. 

From a methodological perspective, the project serves as a model example of how HPC can support interdisciplinary research that integrates environmental data, text corpora, legislation, and public discourse. Such an approach holds great potential within European initiatives focused on sustainable land management and landscape planning. 

The results thus create a transferable framework that can be applied in both European and national projects — ranging from public policy research and participatory planning to the assessment of the social impacts of environmental decisions. 

Data today can tell stories that we could not have captured just a few years ago. The research team harnessed the computational power of a supercomputer to analyse vast textual datasets in order to better understand how society perceives soil, landscape, and their value. The project demonstrates that the future of soil is hidden in data — and that high-performance computing can support not only scientists but also communities striving to find balance between development and sustainability. 

There’s no reason to be afraid.

You can think of a supercomputer as an extremely powerful machine with thousands of “brains” working together. It’s not sitting in your office or glowing under your desk — it’s housed in a specialized data center, and you control it conveniently through a web browser.

You simply prepare your task and submit it to the system. While the supercomputer gets to work, you can relax and enjoy a cup of coffee. Within minutes or hours, you’ll receive results that would take your laptop weeks to compute — or that it might not be able to handle at all.

Who can it help?

- students processing large amounts of data
- scientists testing new artificial intelligence algorithms
- meteorologists working on weather forecasting
- designers and engineers running simulations and developing new solutions
- doctors and biologists analyzing genomes or medical data
- small innovative companies without their own computing infrastructure

And many other fields are waiting for someone brave enough to explore them.

Why is it important?

We need a new impulse for innovation. We have smart people, bold ideas, and now also a tool that saves time, money, and opens the path to world-class results. The supercomputer is here to accelerate scientific progress and drive economic growth.

The first webinar coming soon

The authors of the guide are preparing a practical webinar designed for complete beginners. We’ll show that access to supercomputing is truly within everyone’s reach — for anyone unafraid to explore new possibilities. The goal is to spark curiosity and break down the barriers between technology and its users.

User Guide

Challenge: Recognizing whether tissue is infected with bacteria is not always straightforward. In the early stages of infection, the differences between healthy and damaged cells often cannot be detected even under a microscope. Although traditional biochemical tests can confirm the presence of bacteria, they are usually time-consuming and require sample collection.

Solution: To identify subtle differences between healthy and infected tissue, the researchers decided to combine experimental measurements with advanced data processing. Raman spectra obtained from different depths and regions of the tissue contained an enormous amount of information that could not be reliably evaluated using conventional visual methods.

The scientists therefore sought to verify whether this method could reliably distinguish healthy tissue from tissue infected with Staphylococcus aureus one of the most common causes of skin and mucous membrane inflammations. At the same time, the researchers focused on monitoring the effectiveness of photodynamic therapy—an experimental treatment based on carbon quantum dots that, when exposed to blue visible light, destroy bacteria without harming healthy cells.

Use of HPC Infrastructure

The team employed a mathematical analysis based on the Euclidean cosine of the squares of the first differentiated values, which enables the comparison of similarities between spectra after their transformation. This method eliminates background interference, highlights chemical changes in the tissue structure, and allows precise identification of differences caused by the presence of bacteria or the effects of treatment.

The computational power of a supercomputer was used to process the extensive datasets. Thanks to parallel data processing, it was possible to rapidly analyze hundreds of measurements from different tissue layers and visualize their similarities in a clear results matrix. Such an approach would be virtually impossible through manual evaluation.

The solution was developed through close collaboration among experts from multiple disciplines—biology, physics, materials research, and computational science. Reconstructed skin tissues were provided by the SK-NETVAL laboratories at the Institute of Experimental Pharmacology and Toxicology of the Centre of Experimental Medicine, Slovak Academy of Sciences (SAS), which also performed the exposure to the tested substances. The photodynamic treatment was applied by the team from the Polymer Institute of SAS, and the Raman data were collected at the Institute of Physics of SAS in cooperation with the Centre for Advanced Material Application.

Results

The analysis of the spectral data revealed significant chemical differences between healthy and infected tissue that can be detected using Raman microscopy. Samples infected with Staphylococcus aureus showed distinct spectral characteristics at all analyzed depths.

The results were particularly interesting in the samples that underwent photodynamic treatment. After the application of carbon quantum dots and subsequent activation with blue light, the chemical spectra closely approached those of healthy tissue. This suggests that the treatment effectively suppresses bacterial infection without damaging the cells themselves.

The applied algorithm proved to be a reliable and fast tool for comparing spectral data. Thanks to its implementation in the HPC environment, it was possible to automatically process large volumes of measurements and evaluate the results objectively, without any subjective interference from the researcher.

Impact and Future Potential

The project has brought new insights into the potential use of light and data analysis in medical diagnostics. It has demonstrated that combining Raman microscopy with computational methods enables not only the identification of bacterial infection in tissue but also the monitoring of treatment effectiveness in real time.

In the future, this approach could be applied in the development of new antibacterial therapies or in preclinical drug testing, where it is essential to quickly and accurately assess structural changes in tissue without invasive procedures. The research team also plans to extend the methodology to other types of bacteria and tissues and to leverage the computing power of the supercomputer for testing advanced artificial intelligence algorithms that could further automate the analysis.

The project is proof that the integration of biomedicine, physics, materials research, and computational science opens new possibilities for disease diagnosis and treatment.
Slovak research teams are thus not only demonstrating their scientific excellence but also contributing to pushing the boundaries of modern medicine.

Challenge: Hydrogen is increasingly seen as the “fuel of the future” — carbon-free, clean, and applicable across industry, energy, and transportation. However, to make it truly accessible, it must be produced more cheaply and efficiently. Traditionally, expensive metals such as platinum have been used for this purpose, but they are not suitable for large-scale deployment. Scientists are therefore searching for new materials capable of catalyzing (accelerating) the reaction through which hydrogen is released from water.

Solution: A team of researchers from the Institute of Chemistry at Pavol Jozef Šafárik University in Košice and the Institute of Materials Research of the Slovak Academy of Sciences focused on molybdenum phosphide (MoP) — an inexpensive and readily available material with the potential to replace costly metals. They studied how MoP performs in different environments — from acidic to alkaline — and why it is able to maintain its efficiency.

The laboratory alone was not enough. The reactions on the catalyst’s surface are extremely fast and occur at the atomic level. To truly understand them, it was necessary to combine experimental research with computational simulations on a supercomputer.

Use of HPC Infrastructure

Collaboration with NSCC Slovakia and the use of a supercomputer enabled the researchers to create computer models of the catalyst and simulate what happens when hydrogen atoms bind to its surface. 

Thanks to HPC, the team was able to:

• uncover the reaction mechanism — how hydrogen atoms behave on the surface of MoP
• verify the stability of the material in different environments
• predict potential improvements to the catalyst even before it is produced in the laboratory.

Impact

The outcome is significant for several reasons:

• MoP is cheaper and more accessible than platinum, which could reduce the cost of hydrogen production.
• The material works across a wide range of environments, meaning it could be deployed in various types of electrolyzers worldwide.
• The combination of experiments and HPC simulations saves both time and costs — allowing researchers to identify the best solutions much faster.

This research shows that HPC is not just for physicists or computer scientists — it can also play a crucial role in advancing green energy. Thanks to the computational power of the supercomputer, Slovak researchers contributed to global knowledge on eco-friendly hydrogen production and paved the way for new technologies that can directly impact energy independence and sustainability.

A study of the mechanism of the hydrogen evolution reaction catalysed by molybdenum phosphide in different media – ScienceDirect