It starts with a simple but far-reaching question:
How can digital technologies transform learning?

The L3S begins its work in 2001 as the Learning Lab Lower Saxony, researching digital learning technologies. Its research focuses on new forms of technology-enhanced learning and teaching, collaborative learning environments, and ways of tailoring content to individual learners. To support this work, the L3S provides an excellent research and collaboration infrastructure. From the outset, the L3S has an international outlook, working with renowned partners such as Stanford University and KTH Royal Institute of Technology in Stockholm.

Learning requires new ways of communicating, accessing knowledge and collaborating. This is why the L3S soon broadens its research to include internet technologies, the Semantic Web and digital libraries, as well as mobile and distributed systems. It combines fundamental research and technological development with practical applications. At the same time, its international profile grows through European research networks and partnerships with organisations from academia, industry and education.

What remains?

Designing digital technologies to support people in learning and working remains one of the L3S’s core areas of research to this day.

The internet is growing rapidly – and so is the amount of information it contains. A new question comes to the fore: How can people find exactly what they are looking for in this growing body of knowledge?

Conventional search engines are increasingly reaching their limits. The L3S therefore explores methods that go beyond recognising words to take into account the context and meaning of information. The vision of the Semantic Web emerges: content should be described in ways that machines can understand, linked to other content and, as a result, made easier to find.

At the same time, the L3S develops new approaches to personalised and adaptive information systems. Search results should be more closely tailored to users’ interests and needs.

The research extends beyond web content. The L3S investigates distributed information infrastructures, networks and security, as well as how different data sources can be intelligently connected.

What remains?

The idea that information should not merely be collected, but structured, linked and made understandable in its context, becomes an important foundation for later research into knowledge graphs and AI.

The Web is no longer simply a channel for information. People communicate, work and conduct research on it. The Web itself thus becomes an object of research.

With Web Science, the L3S turns its attention to the interplay between technology and people. Research addresses communication and networking, personalisation and information retrieval, as well as the social, economic and legal dimensions of the digital world. The Web is developing into a global space for knowledge, where users not only consume information but also create and share content themselves.

Research is becoming increasingly interdisciplinary. Computer science meets the social sciences, economics and law. Questions of data protection, security and the responsible use of data are gaining importance – for example, in the Europe-wide linking of medical data.

At the same time, the L3S begins to explore the potential of large and complex datasets for new applications. In medicine, early data-driven approaches emerge that will later become an important part of AI research.

What remains?

The insight that digital technologies are never merely technical systems. They operate within social contexts and therefore need to be researched and shaped through interdisciplinary approaches.

More and more data is being generated and collected. The challenge is changing: it is no longer enough simply to access information. The real challenge is to turn data into new knowledge.

Data science, machine learning and data-intensive applications are becoming increasingly important at the L3S. Large and diverse datasets are analysed, combined and used to gain new insights.

Medicine, mobility, industrial production and society are emerging as key areas of data-driven research. At the same time, data protection, security and social responsibility remain integral to this work.

What remains?

Years of research into the Web, semantics and data management lay the foundations for a new generation of data-driven and learning systems.

Artificial intelligence is evolving from a research field into a key technology. At the L3S, researchers from different disciplines are exploring how AI can be applied to real-world challenges.

Machine learning and deep learning are opening up new possibilities in medicine, mobility and industrial production. AI systems can interpret images and sensor data, identify patterns, make predictions and support people in complex decision-making.

At the same time, AI itself is becoming the subject of critical research. How can bias and discrimination be detected? How can AI systems be made transparent and fair? And how can their performance be combined with reliability and social responsibility?

During this period, the L3S works with partners from academia and industry to develop an AI ecosystem for industrial production (IIP-Ecosphere). As a partner in the new Centre for Digital Innovations Lower Saxony, the L3S becomes an important contributor to digitalisation research in the state. With the International Leibniz Future Laboratory for Artificial Intelligence, the L3S expands its international AI research in personalised medicine. At the same time, its technical infrastructure grows: high-performance computers make it possible to process ever larger volumes of data and train increasingly complex models.

Energy-efficient AI is also becoming increasingly important. In applications such as autonomous driving, AI systems need to process vast amounts of sensor data in real time while remaining reliable and energy-efficient.

What remains?

At the L3S, AI is not understood as an isolated technology, but as a combination of data, knowledge, people and real-world applications that address societal challenges.

Generative AI and large language models mark the beginning of a new phase. Machines can no longer just analyse data: they can understand language, draw on knowledge and support people with complex tasks.

The L3S is exploring how these systems can become both powerful and trustworthy. It combines its longstanding expertise in data management, the Semantic Web and knowledge graphs with modern AI methods.

One example is scientific search. ORKG Ask combines large language models with structured scientific knowledge. Researchers can ask questions in natural language and receive answers linked to sources and structured information.

In medicine, AI, knowledge graphs and causal methods are being brought together. In mobility, the focus is on safe and energy-efficient AI systems. And with quantum computing, the L3S is exploring another technology that could open up new possibilities for data-intensive applications in the long term.

At the same time, one question is becoming increasingly important: How can we develop AI that people can trust?

Transparency, fairness, explainability, safety and human oversight are becoming central research questions.

Alongside fundamental research, transferring knowledge, methods and technologies into practice is becoming increasingly important. Through the AI Service Centre KISSKI and the Digital Innovation Hub DAISEC, the L3S supports companies in using modern AI technologies responsibly.

Europe needs powerful AI, open knowledge infrastructures and technological sovereignty. The L3S is actively helping to shape this development and is involved in the development of open European language models.

What remains?

The boundaries between humans and machines are being redefined. AI should not simply take over decision-making, but support people, make knowledge more accessible and accelerate scientific discovery.