Categories
Interactive HPC Research Supercomputing UCloud Use case

Combining AI and satellite data to explore the upper atmosphere

For researcher Lotte Ansgaard Thomsen at Aalborg University, UCloud has played a central role in the research project UpperAtmosphere, where she combines artificial intelligence, satellite data and physical models to better understand conditions in the upper atmosphere.

Many satellites operate in this part of the atmosphere, where conditions can change quickly due to solar activity. However, traditional physical models do not always capture these rapid changes accurately. To address this, Lotte uses AI to learn patterns from different data sources and improve the physical model.

Lotte Ansgaard Thomsen is an Associate Professor in the Department of Sustainability and Planning at Aalborg University. In her current research project, she investigates how AI can be used to improve the understanding of key variables in the upper atmosphere. This can contribute to more accurate models of the space environment where satellites operate and provide better insight into the conditions that may affect satellite performance, communication systems, and space-based infrastructure.

Combining AI and physical models

A key part of the project is the combination of several different data sources. Satellite measurements, solar activity data and ionospheric data each contribute with important information. When these data sources are used together, the AI model can improve the physical model significantly. According to Lotte, this combination is one of the central insights of the project so far:

“A key insight is combining different data sources really matters. Satellite measurements, solar activity, and ionospheric data each add something unique. When I use them together in AI on top of the physical model, the model improves significantly.”

Using UCloud as the primary platform

Lotte has used UCloud as the primary platform for running the computational work in the project. A large part of this involves training AI models, which requires substantial computing power because the datasets are large and the models need many iterations to find the right architecture. However, UCloud has not only been used for the heavy computations at the end of the process. It has also supported the development and testing of code along the way.

“It gives me a good environment to build the workflow, try things out, and adjust as I go.”

Lotte also uses UCloud in another research project, where large language models are used to work with environmental data. Across both projects, access to computing power has been essential.

“In both projects, we simply could not have done the work without access to this kind of computing power or a similar alternative.”

Access to computing power made results possible faster

When Lotte moved from industry into academia, she was concerned about whether she would have access to enough computing power for her research. Discovering that UCloud existed was therefore an important advantage.

“It was really nice to discover that UCloud existed. Having access to that number of resources has been a big advantage for the project.”

With UCloud, Lotte could access the computing power needed without first having to apply for separate funding. This made it possible to move faster from development to results.

“If I did not have access to UCloud or another free service, and first had to apply for funding just to get compute, it would have been impossible to have results so fast.”

A user-friendly platform for research

According to Lotte, one of the main benefits of UCloud is its user-friendly setup for research and development work.

“First of all, UCloud is really well-suited for development work. It gives me a good environment to build and test my workflow, and for research work, I have found that it has a very user-friendly interface.”

She has used Visual Studio Code, a code editor used for writing, testing and developing code, on UCloud, which gives her a setup similar to the one she uses locally. This makes it easier to move between local development and cloud-based work. Another important advantage has been the possibility to scale up and access more compute when needed.

“It has been very easy to scale up and get more compute when I need it.”

Fast support makes a difference

For Lotte, the support around UCloud has also been an important part of the experience. When working with complex research projects, technical issues can slow down the research process. In her experience, the support team has responded quickly when challenges have occurred.

“If I run into any issues, the team helps almost immediately. That makes a big difference when working on complex projects.”

Lotte has received support from Aalborg University’s local front office, which helps researchers get started with UCloud and provides support when questions or technical issues arise. All Danish universities have a local front office where researchers can get support.

Overall, UCloud has provided Lotte with access to the computing resources, development environment and support needed to work with large datasets, AI models and complex research workflows.

“I think UCloud is a really good solution overall. When people talk about the need for more European cloud alternatives, this is the kind of thing I think of.”

This work was supported by DeiC National HPC (g.a. DeiC-KU-L1-291125). Read more about DeiC’s calls for resources on HPC-platforms: Grants og funding | DeiC.

Categories
Application Call Interactive HPC Research Supercomputing UCloud

H1-2027: National HPC call opens on 21 July 2026

You can now apply for compute time on UCloud. DeiC has opened the second 2026 call for applications for access to Denmark’s national HPC facilities. So if your research needs extra compute resources on UCloud, now is the time to apply.

These calls only open twice a year, so this is a great opportunity to consider applying in this round. Researchers (and PhD students) at Danish universities can apply.

Key dates

  • Call opens: 21 July 2026
  • Call closes: 1 September 2026
  • Resources available: 1 January 2027

Read more and apply via DeiC

Categories
Research Supercomputing UCloud Use case

Danish language model project enters a new phase with stronger national computing power

How do we ensure that the artificial intelligence of the future understands the Danish language, Danish institutions, and Danish society – while handling data within frameworks that we control ourselves?

This question lies at the heart of the research project Danish Foundation Models (DFM), where the University of Southern Denmark, Aarhus University, the University of Copenhagen, and the Alexandra Institute are collaborating to develop open Danish language models. The project has been underway for some time, and researchers have already released the first models, established benchmarks, and initiated collaborations with external partners. Now, the project is entering its next phase.

With access to the new national AI supercomputing facility BITTEN, inaugurated in Sønderborg in May, and accessible through the research platform UCloud, the pace of development can increase significantly.

Culture, norms, and societal understanding are lost

Within just a few years, language models have become a strategic technology. They are already used for text generation, search, decision support, automation, and analysis. However, the most widespread models have been developed by global companies and trained primarily on English and other major languages.

This creates limitations when such models are expected to operate within a Danish context.

“If you look closely at the details, many international models are actually poor at Danish. The way they formulate themselves often resembles English translated into Danish. That is not how we speak or write,” says Professor Peter Schneider-Kamp from the University of Southern Denmark, who leads DFM on behalf of SDU.

The challenge extends beyond language. It also concerns culture, social norms, and an understanding of society.
DFM has, among other things, developed Danish benchmarks that test models on knowledge of Danish culture. Here, even the largest international models often perform poorly.

“They lack an understanding of how Denmark works – our literature, our public institutions, our healthcare system, and our cultural points of reference,” Schneider-Kamp explains.

Denmark cannot remain on the sidelines

The development of AI is moving so rapidly that access to domestic expertise and infrastructure is becoming increasingly important. According to Schneider-Kamp, it is risky to assume that other countries will continue to provide the services and models that Europe needs indefinitely.

“We cannot simply rely on American or Chinese companies to provide the right solutions for us forever. We need to take part in the development ourselves,” he says.

This is not about replicating Silicon Valley at the same scale, but about being able to develop solutions tailored to Danish needs – and doing so on a transparent and responsible foundation.

“We want models where we know what they have been trained on, that comply with GDPR and the AI Act, and that understand the Danish language, Danish culture, and Danish norms,” he says.

UCloud is the backbone

Behind the project lies a less visible, but crucial part of the story: research infrastructure.

DFM is developed to a large extent using UCloud, the national platform for interactive high-performance computing developed by SDU eScience Center together with partners. It provides researchers with access to storage capacity, GPUs, software, and collaboration tools in one integrated environment.

For Peter Schneider-Kamp, UCloud is absolutely central.

“UCloud is our secure environment where we develop models, train models, store data, and evaluate them. It is absolutely central to everything we do,” he says.

The security perspective is essential. When researchers work with large amounts of data – and in some projects also sensitive data – it is critical that the data can be handled within a controlled environment.

“If we receive new datasets from, for example, libraries, media organisations, or other sources, we can store them securely, work directly on them, and maintain control over the data,” he says.

The alternative is often more complex and fragmented solutions where data has to be moved between systems and countries.

New national supercomputer BITTEN

On 5 May 2026, a new national supercomputer was inaugurated in Sønderborg: BITTEN. The facility was established by the University of Southern Denmark in collaboration with Danfoss and Hewlett Packard Enterprise (HPE) and forms part of the Danish research infrastructure for artificial intelligence, advanced computing, and data-intensive research.

The supercomputer is made available through UCloud, allowing researchers and students at universities across Denmark to access it through their existing systems and workflows.

The collaboration combines SDU’s experience in research infrastructure, Danfoss’ expertise in energy-efficient cooling and heating solutions, and HPE’s knowledge of supercomputing and data centre technology.

The facility has also been designed with a strong focus on energy-efficient operation and the reuse of excess heat.

Lack of computing capacity slows down research

For AI research, access to computing power is not a luxury – it is a prerequisite.

Previously, the DFM group regularly experienced bottlenecks when training models.

“Sometimes we have had to wait two, three, four, or even five days to get access to a GPU. Meanwhile, PhD students and postdoctoral researchers are sitting ready with ideas and code but are held back by a lack of resources,” says Peter Schneider-Kamp.

This is precisely where the new capacity can make a difference.

More computing power means faster experiments, larger models, more iterations, and a shorter path from idea to result.

“We hope it will allow us to turn ideas into research results and concrete use cases much faster. We are incredibly excited to gain access to the many additional GPUs,” he says.

More than technology

DFM is therefore about more than software and hardware. The project illustrates how research, digital sovereignty, data security, and innovation are closely connected.

If Denmark wants to use AI in healthcare, the public sector, education, and industry, it requires solutions that can be understood, adapted, and trusted.

With UCloud as its operational backbone and the new national supercomputing capacity of BITTEN, Danish Foundation Models now stands at a point where the work can move from a promising development phase to broader implementation.

The question is no longer only whether Denmark can develop its own language models.

The question is whether we can afford not to.

Categories
Interactive HPC Research Supercomputing UCloud Use case

How UCloud supported large-scale research combining time-use and consumption data to understand socio-economic differences 

 UCloud played an important role in Sofia Topcu Madsen’s research by helping her analyse large-scale time-use and consumption data across seven countries faster and more efficiently, supporting her work to gain insights into how people spend their time and money in everyday life. 

Sofia Topcu Madsen is a former PhD fellow at Aalborg University, Department of Sustainability and Planning. As part of her PhD project, Getting the Data Right, she investigates how people across seven countries in low- and middle-income countries spend time and money on different everyday activities — and how socio-economic factors shape what people are able to do. 

The project looks at countries including Uganda, Kenya, Tanzania, India, Sri Lanka, Argentina and Mongolia. Based on large-scale time-use and consumption data, Sofia analyses activities such as transport and household work and explores how time and money spent on everyday activities vary across different socio-economic groups. 

Working with large datasets 

Sofia’s analyses are based on different types of detailed data. One example is time-use diaries, where participants report what they do throughout the day in 10-minute intervals. For some countries, the datasets are very large. In the Indian dataset alone, Sofia works with around half a million observations. 

This makes the computational work demanding. At first, Sofia tried running the analyses on her own computer, but the datasets were too large and the analyses too time-consuming. 

“On my own computer, the analyses could take several days to run. With UCloud, it became much faster and more manageable,” Sofia explains. 

UCloud gave her access to more computing power, making it possible to run large analyses more efficiently and rerun them when corrections or adjustments were needed. This became important throughout the project, as even small changes in the data setup or model specification could require the analyses to be run again. 

“UCloud has been a huge help. I do not think I would have been able to complete this part of the project in the same way without access to it,” Sofia says. 

Using Stata and R on UCloud 

To conduct the analysis, Sofia used Stata and R on UCloud. Stata and R are tools that researchers use to work with data and carry out statistical analyses. 

In Sofia’s project, the tools were used to run regression analyses, where she examines how different factors may be connected — for example how education, income or gender may relate to the amount of time and money people spend on transport, household work or other everyday activities. 

She used SUR methods, which make it possible to run several related analyses at the same time. This was relevant because the project looks at activities across a full 24-hour day, where time spent on one activity can be connected to time spent on another. Similarly, money spent on products supporting one activity limits money for other products. 

Running several analyses at the same time with large datasets requires a lot of computing power and would have been very time-consuming to do on a normal computer. By using UCloud, Sofia could run the analyses faster and more efficiently, saving her a lot of time. 

Contributing to research on sustainable development 

Sofia’s research is connected to the UN Sustainable Development Goals by exploring how everyday activities can be used as indicators of broader social and economic conditions. 

How people spend their time can tell us something important about everyday life, inequality and opportunities. For example, a joint perspective on time and money spent on transport, household work, or leisure can reveal how resources, responsibilities, and opportunities are distributed across different population groups. 

“Time can also be understood as a resource. Looking at how people spend their time gives us another way to understand poverty, inequality and sustainable development,” Sofia explains. 

A platform that was easy to get started with 

Sofia describes UCloud as easy to access and use, especially once the workflow was in place. She also highlights the support as an important part of the experience. 

“The support has been very effective. I have received quick answers to my questions, and that has been a big help,” she says. 

Sofia received support from Aalborg University’s local Front Office. Each Danish university has its own Front Office, where researchers can get help with access, use and questions related to UCloud. 

Would use UCloud again 

Sofia is now employed at the University of Copenhagen, Department of Food and Resource Economics, and she can see herself using UCloud again in future research. 

“I would definitely use UCloud again,” she says. 

Because UCloud is available to researchers affiliated with Danish universities, Sofia can also continue to use the platform in future research projects at the University of Copenhagen. 

Categories
Interactive HPC Research Supercomputing

New national supercomputing capacity available through UCloud 

A newly inaugurated supercomputing facility expands access to advanced computational resources for researchers and students across Denmark via UCloud. 

A new supercomputing facility has been inaugurated at Alsion in Sønderborg, marking an important expansion of Denmark’s digital research infrastructure. The system, named Bitten, will support research and teaching in areas such as artificial intelligence, data analytics, and advanced computing – and will be accessible to users across the country through UCloud. 

By providing access via UCloud, the system becomes available within a familiar environment already used by thousands of researchers and students. Users can access advanced computing resources directly through a browser-based interface, selecting tools and applications much like in an app store — without needing to manage or understand the underlying infrastructure. This significantly lowers the barrier to entry, making high-performance computing available not only to specialists, but across disciplines. 

The new setup also simplifies the user experience. Infrastructure that was previously distributed across locations is now consolidated in a single data centre, making it easier to navigate and work with computing resources. 

Expanding access to advanced computing 

The addition of new supercomputing capacity increases what researchers can do — and who can do it. By removing technical and practical barriers, the platform enables more researchers and students to work with large datasets, advanced models, and computational methods, accelerating the path from idea to insight, and from research to real-world application. 

Just as importantly, this is made possible within a Danish digital infrastructure where data, software, and computation remain under national control. As reliance on large-scale data and AI continues to grow, questions of data governance, security, and control are becoming increasingly central — not only from a technical perspective, but as a strategic priority for research and innovation. 

“Access to computing power is only part of the equation,” said Professor Claudio Pica, Director of the SDU eScience Center representing the consortium behind UCloud. “It is equally important that researchers can work within a trusted environment where data and workflows remain under national control. UCloud makes it possible to combine advanced computing with that level of trust and transparency.” 

A shared platform for research and innovation 

UCloud is already widely used across Danish universities, supporting a broad range of disciplines and use cases, and now serves more than 23,000 users across research fields. With the addition of new high-performance resources, the platform continues to evolve to meet the growing computational needs of research and education. 

The platform also supports startups and spin-out companies by providing access to advanced AI and data analytics, improving opportunities to develop, test, and scale new solutions. In this way, the infrastructure contributes not only to research, but to innovation and competitiveness more broadly. 

UCloud is developed and operated in close collaboration between the partners in the Interactive HPC Consortium, consisting of the University of Southern Denmark, Aarhus University, and Aalborg University — reflecting a long-term joint effort across Danish universities to build shared digital research infrastructure. 

Part of a broader national effort 

The new supercomputing facility, Bitten, is part of Denmark’s national research infrastructure and reflects ongoing collaboration between universities, industry, and technology providers. Access through UCloud plays a central role in ensuring that this investment benefits a broad user base across the country. 

The facility is also designed with energy efficiency in mind. Developed in collaboration between SDU, Danfoss, and HPE, the system uses advanced liquid cooling with full heat recovery, allowing excess heat to be reused in the local district heating system. This positions the facility as an example of how digital infrastructure can actively support the energy system — turning data centres from energy consumers into integrated, value-adding components of local infrastructure. 

Categories
Application Interactive HPC Research Supercomputing

Introducing RAGFlow: Enabling Smarter Research with AI-Powered Search

A new open-source application is now available on UCloud, designed for students, researchers, and educators working with complex data and artificial intelligence. RAGFlow – short for Retrieval-Augmented Generation – combines powerful language models with your own academic materials, offering an intelligent way to search, explore, and interact with content.

Whether you’re conducting a literature review, developing a teaching assistant, or building a domain-specific chatbot, RAGFlow provides an intuitive pipeline that transforms unstructured documents into a searchable, AI-ready knowledge base. But RAGFlow is more than just question-answering. It supports the creation of custom workflows and intelligent agents, enabling advanced interactions, data processing, and tool integration – all within a flexible and transparent environment.

What can you do with RAGFlow?

RAGFlow helps large language models (LLMs) generate accurate answers based on real data – not just pre-trained knowledge. It’s built to close the gap between raw academic material and useful insight.

RAGFlow is designed with both beginners and advanced users in mind. At its simplest, you can just upload documents and start asking questions. The interface guides you through the basics, so you can get useful results straight away.

As your needs grow, you can delve deeper into advanced features such as custom chunking, retrieval tests, datasets, and programmable workflows. Comprehensive documentation and tutorials are available, allowing you to learn at your own pace and expand your use of the platform over time.

Key Features:
  • Data Ingestion & Chunking:
    Upload PDFs, text files, webpages and more. RAGFlow automatically breaks them into manageable parts.
  • Embedding & Indexing:
    These chunks are converted into vector representations so they can be searched by meaning, not just keywords.
  • Smart Retrieval:
    When you ask a question, the system finds the most relevant information.
  • Contextual Generation:
    An LLM uses this context to generate well-informed responses.
  • Cited Sources:
    All answers come with grounded citations, showing where the information came from — supporting transparency and academic rigour.

This process improves the quality of responses and significantly reduces the risk of hallucinated or misleading answers.

From Search to Workflow: Introducing Agents

Beyond document search, RAGFlow also allows you to build and customise your own AI-powered agents. These agents can search, analyse, and use tools on your behalf – forming a pipeline tailored to your specific research needs.

So, what is an agent?

Think of an agent as a specialised AI assistant. You might create one to retrieve data from a source, another to analyse it, and a third to generate a written summary or report. These agents can be chained together into a programmable pipeline – a step-by-step flow where each agent passes its output to the next.

For example, you could build a research assistant that:

  • Searches for academic papers on a topic
  • Extracts and summarises the most relevant findings
  • Runs basic statistical analysis
  • Outputs the results as a draft report

Unlike typical ‘black-box’ AI tools, which conceal their inner workings, RAGFlow provides full transparency, allowing you to understand exactly how your AI operates. You can inspect, adjust, and understand every stage – from document chunking to embedding, retrieval, and agent reasoning. It’s a flexible and reproducible platform where your agents can be saved, re-run, or even shared with colleagues.

Why use RAGFlow on UCloud?

RAGFlow is available directly on UCloud. This offers several key advantages:

  • Academic Use Cases:
    Build assistants for teaching, research discovery, or even entire knowledge bases for your institute or research centre.
  • No Installation Required:
    Launch RAGFlow on UCloud with everything preconfigured and ready to use.
  • Flexible AI Model Support:
    Choose from models hosted on Hugging Face, Ollama, or take advantage of GPU-accelerated inference with vLLM – all accessible via an API key.
  • Easy Document Management:
    Upload and manage a wide range of formats, including PDFs, scanned documents, spreadsheets, and HTML.
Learn more 

Guides and technical details:
RAGFlow Guide
RAGFlow documentation on UCloud

A recorded tutorial will also be available shortly. Sign up for the newsletter to receive updates on this and other Interactive HPC news.

Categories
Interactive HPC Research Supercomputing Teaching UCloud Use case

UCloud Provides Student Access to Advanced NLP in Teaching 

In the Master’s programme in Cognitive Science at Aarhus University, UCloud plays a central role in teaching Natural Language Processing (NLP). For instructor and PhD student Mina Almasi, the platform is essential in enabling students to work hands-on with complex models – regardless of the limitations of their own computers.

From Theory to Hands-On Learning 

In a white classroom in Nobelparken, Mina stands in front of 15 students. On the screen behind her, lines of Python code appear in neat, symmetrical rows as she explains which code libraries the students need to access.

In her teaching, she uses the Coder Python application in UCloud because the course is based on Python programming. But the choice of platform is not just about software – it is about giving students the opportunity to translate theory into practice.

According to Mina, NLP teaching previously tended to remain at a more theoretical level, due to limited access to both models and the computing power needed to test theories in practice – especially when it came to large language models. With UCloud, students can now work directly with language models (LLMs) and make use of powerful GPUs and CPUs. This allows them to test theories themselves and experiment hands-on with the tools they are learning about.

“We still teach the theory, but now we can also have students use the tools in practice. They can code on their own and gain insight into how a large language model works by working directly with it through UCloud,” she explains.

A Standardised Setup that Democratises the Classroom 

Another advantage of using UCloud in NLP teaching is that the platform ensures equal access for all students, regardless of the computer they own.

“There is a kind of democratisation of the classroom, because you don’t need the latest computer. You can use a five-year-old machine to run very heavy tasks that the newest tools in Natural Language Processing require,” she explains.

At the same time, the standardised setup makes teaching more seamless. All students work with the same standard configuration in UCloud, so any issues that arise are the same for everyone. This creates a shared sense of problem-solving, as challenges can be addressed collectively rather than handled individually by students on their own. As Mina puts it:

“Instead of stopping the lesson to solve individual problems, the problems become collective and an opportunity for learning for everyone. If we have a software issue – for example, a Python library version that is outdated or incompatible – it affects everyone, and we can solve it together.”

Preparing Students for Working Life

For Mina, using UCloud also helps prepare students for the reality that awaits them after graduation. According to her, many of the students who go on to IT positions will likely use cloud computing platforms rather than coding on local machines. In this way, the teaching becomes direct preparation for future job tasks and gives students experience with the technologies they will encounter in practice.

Advice for Other Instructors 

Mina has used UCloud since her bachelor’s degree and finds that the platform makes teaching both smoother and more engaging.

“I recommend that other instructors make use of the platform. You just have to get started – but feel free to ask colleagues for advice on how they use it. Get some inspiration, because UCloud is a fantastic tool. It can do a great many things, but like other systems, it can feel a bit overwhelming at first, so it’s a good idea to get some guidance along the way before you begin.”

Categories
Call Interactive HPC Research Supercomputing UCloud

H2-2026 National HPC Call is open

You can now apply for compute time on UCloud. DeiC has opened the first 2026 call for applications for access to Denmark’s national HPC facilities – and Interactive HPC – UCloud is part of this call.

So if your research needs extra compute resources on UCloud, now is the time to apply. These calls only open twice a year, so this is a great opportunity to consider applying in this round. Researchers (and PhD students) at Danish universities can apply.

Key dates

  • Call opens: 13 January 2026
  • Application deadline: 10 March 2026
  • Resources available from: 1 July 2026

Read more and apply via DeiC

Categories
Application Interactive HPC Research Supercomputing Tutorial Workshop

Workshop 26/2: CVAT – AI-Assisted Labeling

Date: February 26, 2026

Time: 13:15 to 14:30 CET

Location: Online via Zoom

CVAT, Computer Vision Annotation Tool, is an interactive video and image annotation tool, designed to facilitate the annotation of video and image data and accelerate the creation of high-quality datasets for computer vision tasks. CVAT is available on the UCloud platform, in the Application Store.

The webinar will show how to use CVAT on UCloud to:

Label and annotate data with the help of AI and OpenCV tools, including:

  • Use of cvat-cli
  • Run built-in model for detection and auto-annotation
  • Use of GPUS with built in models for faster annotation
  • Adding custom models (e.g. YOLO)

Efficiently manage large visual datasets with MinIO:

  • Allow CVAT to directly pull images from your UCloud MinIO buckets for annotation and export annotated data back, reducing manual imports/exports and ensuring data availability.

Using UCloud allows users to create fully reproducible and secure workflows that leverage high performance computing resources. Those features are often necessary for large dataset and accurate computer vision tasks.

Target audience: Researchers across all Departments, particularly who require high-precision data labeling, AI interested.

Technical Level: Basic to Intermediate

Sign up for the CVAT workshop

Categories
Interactive HPC Research Supercomputing

UCloud and Digital Sovereignty in focus during Ministerial Visit

On 27 October, Minister for Digital Affairs Caroline Stage Olsen visited the University of Southern Denmark (SDU) to learn more about UCloud and the Interactive HPC Consortium. 

The visit aimed to showcase how Danish research contributes to strengthening Denmark’s digital independence and sovereignty. The Department of Mathematics and Computer Science (IMADA) and the SDU eScience Center at the Faculty of Science were pleased to welcome the Minister to SDU.

During her visit, the Minister was introduced to UCloud, an open-source cloud platform operated by the Interactive HPC Consortium. Originally developed by SDU, UCloud has been available since 2019 via the DeiC Interactive HPC service to all researchers in Denmark. Today, the consortium behind UCloud comprises SDU, AU, and AAU, who jointly develop and operate the platform.

The Minister emphasised that digital sovereignty and the development of cloud solutions under Danish control are key priorities for the government:

”This is something we are increasingly discussing – how we can become more independent and strengthen our control over digital infrastructure. That is part of what I am learning about today,” said Caroline Stage Olsen, Minister for Digital Affairs, during her visit.

Building Bridges Between Research and Society

UCloud serves as Denmark’s national platform for interactive high-performance computing (HPC) and is Europe’s most widely used research supercomputing platform. With more than 18,000 users across universities, public authorities, and private companies, it stands as a clear example of how Danish-developed solutions can promote digital self-reliance.

“True digital sovereignty requires public infrastructure you can inspect, control, and improve. UCloud turns sovereignty from a slogan into a living, open-source public good — Europe’s largest research cloud built in Denmark. Investing in open infrastructure like UCloud is how we can secure our digital future,” said Professor Claudio Pica, Head of the SDU eScience Center.

A Responsibility Towards Society

The visit also prompted a broader dialogue about the responsibility of research institutions in an era where digitalisation permeates every aspect of society – from healthcare and education to the energy sector and public services.

The visit concluded with a tour of SDU’s supercomputing facilities, where the Minister was introduced to the advanced infrastructure that supports Interactive HPC – UCloud.

This article is based on an original story published on SDU’s website.