● Aktuálne projekty
| ViWAS – Virtual Worlds Skills Academy | |
| Akadémia zručností virtuálnych svetov | |
| Program: Horizont Európa | Duration: 1. 5. 2026 – 30. 4. 2030 |
| Project leader: Ing. Tran Viet PhD. | Evidence number: 101298981 |
| ENSURE – ENvironmentally SUstainable digital services and practices for REsearch infrastructures | |
| Environmentálne udržateľné digitálne služby a postupy pre výskumné infraštruktúry | |
| Program: Horizont Európa | Duration: 1. 9. 2026 – 31. 8. 2029 |
| Project leader: doc. Ing. Hluchý Ladislav CSc. | Evidence number: 101292847 |
| EOSC Beyond – EOSC Beyond: advancing innovation and collaboration for research | |
| EOSC Beyond: pokrok v inováciách a spolupráci v oblasti výskumu | |
| Program: Horizont Európa | Duration: 1. 4. 2024 – 31. 3. 2027 |
| Project leader: Ing. Tran Viet PhD. | Evidence number: 101131875 |
| FLUID-AI – FAIR Liquidity Unifying Interoperable Data and AI | |
| FAIR likvidita zjednocujúca interoperabilné dáta a umelú inteligenciu | |
| Program: Horizont Európa | Duration: 1. 10. 2026 – 30. 9. 2029 |
| Project leader: Ing. Tran Viet PhD. | Evidence number: 101292610 |
| GenAI4Earth – Generative Artificial Intelligence for Earth System | |
| Generatívna umelá inteligencia pre systém Zeme | |
| Program: Horizont Európa | Duration: 1. 9. 2026 – 31. 8. 2029 |
| Project leader: Ing. Tran Viet PhD. | Evidence number: 101293266 |
| EOSC-ARENA – AI Research Enhancement through Networked Agents | |
| Vylepšnie výskumu umelej inteligencie sieťovými agentami | |
| Program: Horizont Európa | Duration: 1. 6. 2026 – 31. 5. 2029 |
| Project leader: Ing. Tran Viet PhD. | Evidence number: 101292597 |
| SIESTA – Secure Interactive Environments for SensiTive data Analytics | |
| Zabezpečené interaktívne prostredia pre analýzu citlivých údajov | |
| Program: Horizont Európa | Duration: 1. 1. 2024 – 31. 12. 2026 |
| Project leader: Ing. Tran Viet PhD. | Evidence number: 101131957 |
● Ukončené projekty
There are currently no finished Horizon Europe projects at this institute.
● Anotácie aktuálnych projektov
| ViWAS – Virtual Worlds Skills Academy | |
| Akadémia zručností virtuálnych svetov | |
| Annotation: The rapid evolution of immersive digital technologies such as virtual reality (VR), augmented reality (AR), and extended reality (XR) has led to the emergence of Virtual Worlds (VWs) as transformative tools across sectors. However, the education and training landscape has yet to fully respond to the growing demand for specialized VW-related skills. The Virtual Worlds Skills Academy (ViWAS) aims to bridge this skills gap by developing a comprehensive, future-proof competence and training ecosystem that equips learners, educators, and professionals with the necessary capabilities to thrive in and shape the VWs economy. ViWAS is a pioneering educational initiative that combines the power of RenDanHeYi (2021) organisational model with the agility of the franchise system in an educational context. ViWAS has a cloud-enterprise-like modern structure and aims to prepare the future developers, teachers, architects, designers, and users of VWs through a fundamentally new approach to education that relies on AGILE structures, design thinking, and an entrepreneurial mindset. It will contribute to the EU’s digital transformation by upskilling and reskilling the workforce in the fast-growing field of VW. By fostering collaboration between education providers, industry, and policymakers, ViWAS will pave the way for inclusive, innovative, and sustainable digital learning environments across Europe. ViWAS is focusing on teaching and learning skills for, about and with VWs, developing a network of learning centres that can rapidly adapt to the dynamic evolution of VW, placing the learner at the centre of the educational process and fostering an entrepreneurial spirit and design thinking approach at every level | |
| ENSURE – ENvironmentally SUstainable digital services and practices for REsearch infrastructures | |
| Environmentálne udržateľné digitálne služby a postupy pre výskumné infraštruktúry | |
| Annotation: The digital transformation of science depends on large-scale Research Infrastructures (RIs) that generate, process, and store unprecedented volumes of data. However, their environmental footprint is rapidly increasing, raising concerns about energy and water use, carbon emissions, and sustainability. ENSURE addresses this challenge by operationalising the 4M cycle (Measure, Model, Monitor, Moderate) to reduce the environmental footprint of digital RIs while safeguarding scientific excellence. ENSURE will develop new technologies that combine environmental metrics, reference datasets, benchmarks, and advanced monitoring tools into a coherent framework. Harmonised indicators, aligned with international standards and EU legislation, will provide a trusted basis for impact assessment and reporting. Digital twins of data centres and GenAI methods will enable predictive modelling and the filling of data gaps related to digital infrastructure operations. Workload managers will integrate sustainability into scheduling and resource allocation, while certification and reporting frameworks will ensure transparency, comparability, and accountability across RIs. The consortium unites major ESFRI Landmarks (HL-LHC, SKA, European XFEL), pan-European digital infrastructure providers (EGI), life science domain communities (WeNMR, VIP), leading research universities, and sustainability experts. This unique composition ensures scientific relevance, technical excellence, and broad uptake across disciplines from physics, astronomy, life sciences, and medical imaging to the whole RI landscape. By embedding environmental sustainability into the daily operation of digital RIs, ENSURE will contribute directly to the European Green Deal and climate neutrality objectives. The project’s outcomes will not only lower the environmental footprint of research infrastructures but also position Europe as a global leader in sustainable digital science. | |
| EOSC Beyond – EOSC Beyond: advancing innovation and collaboration for research | |
| EOSC Beyond: pokrok v inováciách a spolupráci v oblasti výskumu | |
| Annotation: EOSC Beyond overall objective is to advance Open Science and innovation in research in the context of the European Open Science Cloud (EOSC) by providing new EOSC Core capabilities allowing scientific applications to find, compose and access multiple Open Science resources and offer them as integrated capabilities to researchers. To do so, EOSC Beyond supports a new concept of EOSC: a federated and integrated network of Nodes operated at different levels, national, regional, international and thematic, to serve the specific scientific missions of their stakeholders. Further specific objectives of the project are to accelerate ‘time to product’ of new scientific applications with software adapters, enable Open Science with machine composability and dynamic deployment of shared resources, support innovation in EOSC with a testing and integration environment, and align the EOSC Core architecture and specifications to integrate with European dataspaces. The project extends the state of the art of the EOSC Core and adopts a co-design methodology, including requirements elicitation, software development and validation in collaboration with different use cases from EOSC national and regional initiatives (e-Infra CZ, Czechia, NFDI, Germany, and NI4OS, South East Europe region), thematic research infrastructures from Social Sciences and Humanities (CESSDA), Life Sciences (CNB-CSIC and Instruct-ERIC), Environmental Science (ENES and LifeWatch), and Health and Food (METROFood-RI). EOSC Beyond builds on the capacities of prospective EOSC Nodes and partners with multi-annual experience in developing solutions for large-scale federated digital infrastructures and aligns with the technical architecture and requirements of data spaces from different business sectors. Ultimately, EOSC Beyond supports Open Science in modern, data-intensive, and multidisciplinary research, facilitating resource discovery, access, and reuse across scientific communities, organisations, and countries. | |
| FLUID-AI – FAIR Liquidity Unifying Interoperable Data and AI | |
| FAIR likvidita zjednocujúca interoperabilné dáta a umelú inteligenciu | |
| Annotation: The FLUID-AI project introduces a new approach to address the lack of interoperability between data, AI/ML models and solutions within the EOSC. We introduce the concept of Data and Models Liquidity, building on and extending the FAIR principles to address the unique demands of AI-ready data and models. While the FAIR principles have improved data management, they fall short in supporting AI applications, which require data that are not only FAIR but also structured, annotated, and optimized for seamless integration into AI/ML workflows. FLUID-AI identifies and addresses 3 major gaps within the EOSC ecosystem. First, we establish a collaborative Competence Centre (CC) to provide coordinated support, training, and resources, ensuring researchers and operators are equipped with the skills needed to leverage AI/ML tools effectively. Secondly, we promote unified data and models integration, implementing semantical and technical interoperability to enable effortless reuse and combination across platforms and scientific disciplines. Thirdly, we deliver accessible and intuitive platforms, reducing technical complexity so researchers can focus on scientific discover. The project is organized in 3 different action pillars corresponding to the identified gaps. Together with 8 real-world use cases from representative Research Infrastructures would allow us to demonstrate the FLUID-AI impact, validating the project’s solutions, ensuring they are scalable, reproducible, and aligned with real-world research needs. By promoting cross-disciplinary collaboration, standardization, and open science principles, FLUID-AI aims to transform the EOSC into a dynamic, AI-ready ecosystem. The project outcomes include the novel Data and Models Liquidity concept and framework, innovative tools and platforms, comprehensive guidelines, and a blueprint for trustworthy AI-ready repositories. All together will empower researchers to leverage the full potential of AI-driven scientific discovery. | |
| GenAI4Earth – Generative Artificial Intelligence for Earth System | |
| Generatívna umelá inteligencia pre systém Zeme | |
| Annotation: Generative Artificial Intelligence (GenAI) is rapidly advancing, offering novel ways to exploit multi-disciplinary data and generate new knowledge for science. In Earth System Science (ESS), GenAI is emerging as a transformative technology, enabling a paradigm shift in understanding, predicting, and managing complex socio-environmental systems by cross-using diverse yet fragmented data sources (satellite and in-situ observations, models, experiments, texts). GenAI4Earth will go beyond the state of the art by designing, deploying, and operating trustworthy, reusable GenAI services within the EOSC ecosystem, advancing discovery on Earth–climate–environment– life interactions in co-design with user communities and research infrastructures at national and European levels. Aligned with GenAI4EU and Apply AI initiatives, the project builds on FAIR data, models, and workflows, integrating them into EOSC (AI4EOSC, EOSC Nodes such as Data Terra and NFDI) to foster standards, best practices, and confidence in AI-enabled dataspaces and foundation models. Concretely, GenAI4Earth will: • Develop GenAI tools to enhance FAIRness, machine-actionability, AI-readiness, and provenance of ESS data and services; • Implement AI-powered interfaces for seamless discovery, access, and cross-domain integration; • Demonstrate pilots in urban resilience, agro-environmental monitoring, and seismology through topical AI foundation models; • Promote responsible AI with reproducibility, explainability, transparency, and frugal computing; • Build capacity via training and engagement to ensure broad uptake of GenAI-enabled workflows. The consortium mobilises expertise across AI, data science, Earth systems, computing infrastructures, and ethics to co-design interoperable, reproducible, and impactful services. | |
| EOSC-ARENA – AI Research Enhancement through Networked Agents | |
| Vylepšnie výskumu umelej inteligencie sieťovými agentami | |
| Annotation: The EOSC-ARENA (AI Research Enhancement through Networked Agents) will deliver a sovereign, generative and agentic Artificial Intelligence (AI) environment integrated with the European Open Science Cloud (EOSC). This AI environment will serve as a scientific assistant supporting the full research lifecycle, from literature review and hypothesis generation to analysis, reporting, and provenance capture. The project responds to pressing needs in the use of smart algorithms and AI/ML services in scientific research, fostering trust, transparency, and European technological sovereignty. The project focuses on building an advanced, scalable, multi-agent system and a marketplace for Generative AI (GenAI) agents and services. It will provide federated training and inference, secure generation with augmented search and integrations based on the Model Context Protocol. The EOSC-ARENA system will be deployed on EU e- infrastructures and interoperable with EOSC EU nodes. Twelve real-life use cases from different scientific domains are selected to co- design, implement, and assess the effectiveness of the project solutions. At the same time, we will provide community engagement, skills development and guidance for responsible, human-centric AI that aligns with EU values and the Research Integrity Framework. Main outcomes include an EOSC-ready platform release with agent execution and marketplace, open-source components, machine-actionable APIs and provenance mechanisms. Equally important will be policy guidance and training assets to accelerate trustworthy AI adoption. The project targets demonstrators integrated with EOSC services and contributes directly to the EOSC and its strategic research and innovation agenda by strengthening interoperability, FAIRness and sustainability of AI in European research. | |
| SIESTA – Secure Interactive Environments for SensiTive data Analytics | |
| Zabezpečené interaktívne prostredia pre analýzu citlivých údajov | |
| Annotation: The FAIR principles provide a framework for enabling proper access and reusability of scientific data, and implementing them is a key goal of the European Open Science Cloud (EOSC). However, providing access to sensitive or confidential data while preserving privacy/confidentiality and usability for researchers is still an open question. Existing solutions like safe rooms, safe pods, or data safe havens are often challenging for the development of reproducible research and seem counter-intuitive when dealing with open science and FAIR principles. The SIESTA project aims to provide a set of tools, services, and methodologies for the effective sharing of sensitive data in the EOSC, following a cloud-based model and approach. SIESTA will provide user-friendly tools with the aim of fostering the uptake of sensitive data sharing and processing in the EOSC. The project will deliver trusted cloud-based environments for the management and sharing of sensitive data that are built in a reproducible way, together with a set of services and tools to ease the secure sharing of sensitive data in the EOSC through state-of-the-art anonymization techniques. The overall objective is to enhance the EOSC Exchange services by delivering a set of cloud-based trusted environments for the analysis of sensitive data in the EOSC demonstrating the feasibility of the FAIR principles over them. | |
● Anotácie ukončených projektov
There are currently no finished Horizon Europe projects at this institute.