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Courses offered in SS 16

  • Lecture: Advanced Data Models

  • This lecture presents advanced concepts in data modeling. In particular, we will discuss formal methods for the representation and management of data models. In addition, methods for data integration, which are based on these formalizations, will be discussed. The tutorials will present practical examples for the presented concepts.

  • Lecture: Informationsmanagement für öffentliche Mobilitätsangebote

  • Die Vorlesung gibt eine Einführung in die organisatorischen und technischen Aufgabenstellungen bei der Planung, der Organisation, dem Betrieb und der Qualitätssicherung von öffentlichen Mobilitätsangeboten, die mit Hilfe von Ansätzen aus der Informatik und mit Informationssystemen gelöst werden können.

  • Lecture: Datenbanken und Informationssysteme

  • Die Vorlesung gibt einen einführenden Überblick über Datenbanken und ihre Verwendung in Informationssystemen. Wesentliche Ziele der Veranstaltung sind das Kennenlernen verschiedener bekannter Datenmodelle, wobei der Schwerpunkt auf dem relationalen Modell liegt. Es werden theoretische sowie praktische Grundlagen der Datenmodelle und zugehöriger Anfragesprachen vermittelt. Außerdem werden Modellierungs- und Entwurfstechniken für das relationale Modell vorgestellt und Einblicke in grundlegende Datenbanksystemtechniken, z.B. die Transaktionsverwaltung, gegeben.

  • Seminar: Linked Data

  • The World Wide Web made it possible to exchange documents and services on a global level - one can access and display documents from the other side of planet instantaneous, without prior agreement. Linked Data is a name for an effort to achieve the same for data - to make data accessible, usable, queryable regardless from where the data is coming from or what the contents is. Linked Data does not replace the current Web. It adds instead an interoperable data layer based best practices, on open standards and technical components which define how data should be published and interlinked. The purpose of this seminar is to provide a conceptual and technical introduction to Linked Data and discuss individual approaches as well as state-of-the-art. An understanding of the basic concepts will then make it possible to discuss opportunities and challenges of Linked Data.

  • Seminar: Privacy and Big Data

  • This seminar is about new and emerging approaches to adjust and balance privacy and utility in data intensive applications, such as information retrieval, data mining and personalisation. These new approaches have the potential to enable a new generation of privacy-enabled services which are not focused on maximizing the collection of user data. Instead these new approaches enable user privacy under different threat models, such as protecting the identity of individual users when querying aggregated data, or preventing leakage of query patterns when users retrieve data from a database. As a result, these new approaches may help businesses in their compliance with increasingly regulatory trust and reinforce user trust, while enabling new business models at the same time.

  • Seminar: Big Data in Personalized Medicine

  • Today’s health care and wellbeing technologies such as diagnostic imaging, next generation sequencing, molecular profiling, mobile and wearable technologies produce vast amount of data, which is by nature high volume, variety and velocity. Big data infrastructure and analytical methods has potential to create significant value by tailoring health care intervention and prevention to the separate needs of different groups, and yielding better outcomes. In this seminar students will explore the challenges and the state of art of applying big data technologies to the personalized medicine domain.

  • Seminar: Web Science Seminar

  • Web Science has become an interdisciplinary study field between computer science, mathematics, sociology, economics, and other disciplines. This seminar researches advanced Web Analytics and Web Engineering topics in Web Science probably leading to master thesis topics for excellent students.Topics include: network evolution models and network dynamics, (overlapping) community detection, recommender systems, adaptation and personalization in Web Environments, the Educational Web, Web Trust & Credibility, Web Protocols, Peer-to-Peer Networking for Web Clients, Web-based Software Development Models, particular Web Development methods like Web Components and many more. Students do not only learn to write and present scientific papers but also to peer review them. Students will be assigned to a supervisor helping the student through all steps like literature research, seminar paper and seminar presentation.

  • Practical course (advanced level): Industrial Internet of Things (Accenture Campus Innovation Challenge)

  • Die Campus Innovation Challenge ist ein von Accenture initiierter Wettbewerb für Studierende technischer und wirtschaftswissenschaftlicher Studiengänge. Die Studierenden erhalten die Möglichkeit, sich mit modernen Technologien auseinander zu setzen und von der intensiven Zusammenarbeit mit unseren IT-Beratern sowie unseren Technologie-Partnern zu profitieren. Eine große Chance, aktuelles Wissen in Projektmethodik und der Lösung praxisrelevanter Anwendungsprobleme zu erwerben.