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DBIS

Courses

Courses offered in SS 25

  • Bridge Course Databases

    A blended learning bridge course for master students in Data Science, Computational Social Science, and related programs.

  • Data Ecosystems Lab

  • Data Science in Medicine

    Health data analytics is one of the main drivers for the future of medicine. Various sources of big data, including patient records, diagnostic images, genomic data, wearable sensors, are being generated in our everyday life by health care practitioners, researchers, and patients themselves. Data science aims to identify patterns, discovering the underlying cause of diseases […]

  • Data Stream Management and Analysis

    In many fields today data is produced continuously, potentially unbounded, and at high rates, which is termed as data stream. Applications in smart manufacturing, aerospace,  particle physics, or stock exchange trading have a high demand to handle and analyze the massive data streams created. Due to their challenging characteristics specific technologies and methods for data […]

  • Dataspaces Proseminar

    Inhalt Die Anforderungen an den Datenaustausch im World Wide Web haben sich in den letzten Jahrzehnten stetig verändert. Anfangs konsumierten die Nutzer nur manuell ausgewählte Inhalte. Durch Trends wie IoT und Industrie 4.0 ist die Datenmenge exponentiell gestiegen, aber Suchmaschinen wie Google helfen dabei. Durch Social Media können Menschen auch selbst Inhalte produzieren und mit […]

  • Datenbanken und Informationssysteme

    Die Vorlesung “Datenbanken und Informationssysteme” gibt einen einführenden Überblick über Datenbanken und ihre Verwendung in Informationssystemen.

  • Knowledge Graph Lab SS 2025

    Knowledge Graphs are large graphs used to capture information about the real world in such a way that is is useful for applications. In these data structures, there are all sorts of entities (for example, people, events, places, organizations, etc.). Knowledge Graphs are used by many organizations to represent the information they need for their […]

  • Knowledge Graphs Seminar

    Knowledge Graphs are large graphs used to capture information about the real world in such a way that is is useful for applications. In these data structures, there are all sorts of entities (for example, people, events, places, organizations, etc.). Knowledge Graphs are used by many organizations to represent the information they need for their […]

  • Mixed Reality Lab

    Mixed Reality is a continuum of spatial computing experiences on virtual, augmented and extended reality devices, such as the Microsoft HoloLens 2, the HTC Vive Pro, Meta Quest 3 and Android smartphones. In this lab, we learn the basics of mixed reality software development in independent project work that student groups can propose and elaborate.

  • Privacy Enhancing Technologies for Data Science

    This lecture covers current research results in the area of Privacy Enhancing Technologies (PETs) which can be applied to Data Science. These PETs have the potential to enable a new generation of privacy-enabled services which are not focused on maximizing the collection of user data. We use a mix of recent book chapters and papers […]

  • Proseminar: Web3 Concepts and Applications

    This seminar will discuss the baseline technologies and concepts of the web 3 such as Blockchain, Distributed Ledger, Tokenization, Self-sovereign identity, etc. as well as its applications e.g. in a Metaverse. After the seminar the participants will understand the Web3 Basics and will be able to develop concepts for new Web3 Applications.

  • Software Projektpraktikum – Building Large Language Model Applications

Courses planned for the upcoming semester (WS 25/26)

  • Bulding Large Language Model Applications – Lab

    Large Language Models (LLMs), such as GPT, Claude and Llama, are powerful tools that have transformed the landscape of Natural Language Processing (NLP), enabling advanced applications in various fields. The “Building Large Language Model Applications,” course is a practical, hands-on course designed to provide students with in-depth knowledge and experience in developing applications utilizing LLMs. […]

  • Data Ecosystems Lab

  • Data Visualisation and Analytics

    This course provides participants with a comprehensive and versatile toolbox of data visualisation and analysis methods, which can be transferred to a vast number of applications.

  • Empathic Computing Lab

    Empathic computing investigates how technology can support collaboration, shared understanding and human-centered interaction. In this lab, student teams design and develop their own projects using immersive and pervasive media—ranging from XR headsets and smartphones to tablets, laptops, and wearable devices. Projects may leverage open standards like WebXR, or use engines such as Unity, depending on […]

  • Intelligent Data Management with Generative AI

    Generative AI unlocks new potentials supporting tasks in many fields – including data management. It can significantly enhance data management by automating and improving tasks across the data lifecycle. In research data management, it supports metadata creation, documentation, and data curation. For database modeling, it enables schema generation from natural language, query formulation, and schema […]

  • Knowledge Graphs Lab

    The Knowledge Graphs Lab offers a practical insight into structured semantic graphs, which model real-world entities and their complex relationships. By leveraging Knowledge Graphs (KGs), you can represent, integrate, and reason over heterogeneous information in a way that makes data more Findable, Accessible, Interoperable, and Reusable (FAIR). Why Knowledge Graphs?Knowledge Graphs power a wide range […]

  • Knowledge Graphs Seminar

    Knowledge Graphs are large graphs used to capture information about the real world in such a way that is is useful for applications. In these data structures, there are all sorts of entities (for example, people, events, places, organizations, etc.). Knowledge Graphs are used by many organizations to represent the information they need for their […]

  • Mixed Reality Lab

    Mixed Reality is a continuum of spatial computing experiences on virtual, augmented and extended reality devices, such as the Microsoft HoloLens 2, the HTC Vive Pro, Meta Quest 3 and Android smartphones. In this lab, we learn the basics of mixed reality software development in independent project work that student groups can propose and elaborate.

Working Groups

  • Data Stream Management and Analysis

    Data Stream Management and Analysis

  • Advanced Community Information Systems

    We are using state-of-the-art techniques of software engineering for the specifications of requirements, design, and for implementation. We practice teamwork techniques and use high-end hardware and software. For our group communication, we use the BSCW system and Moodle (prior TikiWiki).

Specialization Areas

Themenbereiche für eine Prüfung im Vertiefungsgebiet Informatik:

  • Einführung in Datenbanken
  • Implementierung von Datenbanken
  • Informationssysteme
  • Wissensbasierte Systeme
  • Spezialvorlesungen aus den Bereichen Dokumentenmanagement, Electronic Commerce, CSCW & Groupware, deduktive Datenbanken, objektorientierte Datenbanken, Wissensrepräsentation, natürlichsprachliche Schnittstellen, Logikprogrammierung, sowie Informationssystem-Anwendungen in Büro, Ingenieurwissenschaften und Medizin

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