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Informatik 5
Information Systems
Prof. Dr. M. Jarke
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Prof. Dr. M. Jarke
RWTH Aachen
Informatik 5
Ahornstr. 55
D-52056 Aachen
Tel +49/241/8021501
Fax +49/241/8022321

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Annual Reports





Courses offered in WS 17/18

  • Lecture: Implementation of Databases

  • The lecture introduces basic technologies of the realization of database systems. Beside the coarse architecture (e.g. layered architecture) detailed procedures for the solution of special database tasks (especially query analysis and transaction management) will be discussed. The concepts of implementation will be applied to classical (relational model) as well as to more recent data models (distributed, XML). In addition to necessary theoretical fundamentals, practical concepts will be introduced that allow database administrators the efficient tuning of databases.

  • Lecture: Data Driven Medicine

  • Data play an important role in medicine: Intensive care relies on monitors presenting and analysing real-time patient data, medical imaging has become a domain of massive data processing, diagnostics rely on laboratory data, and the importance of data is ever increasing: Wearable sensors, mobile communication devices and respective apps will produce data streams, which support preventive measures in healthy individuals or allow screening as a basis for data-based prevention of diseases. Last but not least: molecular biology (e.g. by gene sequencing and gene expression analysis) introduces new biomarkers, which enable new minimally-invasive diagnostics and approaches to tailoring treatments based on individual characteristics of patients (precision medicine) – which would never be possible without sophisticated processing of huge amounts of data. Medical decision making in general will be markedly influenced by data processing and data analytics. Thus, we can expect data driven medicine to gain momentum in the nearer future. This course offers a project-oriented, multidisciplinary introduction to the basics of data driven medicine. Orientation, fundamental concepts, and methodological approaches are provided by lectures. In addition, the participants will also form small interdisciplinary teams including students of computer science as well as medical students in order to plan and implement an own project, which targets prediction or decision support generated from medical data.

  • Lecture: Semantic Web

  • As part of the W3C Semantic Web initiative standards and technologies have been developed for machine-readable exchange of data, information and knowledge on the Web. These standards and technologies are increasingly being used in applications and have already led to a number of exciting projects (e.g. DBpedia, semantic wiki or commercial applications such as, OpenCalais, or Google's KnowledgeGraph). The module provides a theoretically grounded and practically oriented introduction to this area.

  • Lecture: 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 from conferences and journals of the last few years as primary source material.

  • Lecture: Web Science

  • More than twenty years after the birth of the World Wide Web, Web Science has been becoming a new study field in Computer Science. This course introduces fundamental concepts (web centralities & basic algorithms, network models and web engineering principles) of Web Science. We will learn fundamental algorithms for web page ranking like PageRank and HITS as well as community detection algorithms. In the engineering part we dig into scalable approaches like cloud computing and peer-to-peer partly based on Post-HTTP protocols like the XMPP and WebRTC are. We will learn about Web Services and their RESTful implementation. With the knowledge gained in the preceding chapters we can analyze and engineer advanced Web applications like recommender systems, collaborative editing and Web multimedia environments.

  • 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: 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: Social Computing Seminar

  • Social Computing is an area of computer science that is concerned with the intersection of social behavior and computational systems. It is based on creating or recreating social conventions and social contexts through the use of software and technology. In this seminar we explore recent topics in social computing like Social Bots, Fake News, Filter Bubbles, Socio-political campaigns, Shit & Candy Storms, Social Augmented and Virtual Reality, Gamification, Serious Games, Science 2.0

  • Practical course (basic level): Scala-Programmierung für Data Science

  • Dieses Veranstaltung gibt eine Einführung in das Programmieren mit Scala. Nach einer Einführung der grundlegenden Konstrukte der Programmiersprache in mehreren kleinen Übungen, sollen die Studierende eine komplexere Projektaufgabe lösen, die den ganze Software-Entwicklungsprozess von Anforderungserfassung, Design, Implementierung, Testen, Deployment bis hin zur abschließenden Dokumentation umfasst.

  • Practical course (basic level): 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.

  • Practical course (advanced level): High-Tech Entrepreneurship and New Media

  • The course combines tutorials and lectures on the development of complex information products with practical experience in start-ups on specific and typical IT-related problems of the companies taking part in the lab. Integrated into the concept of this course is the development of presentation and other soft skills. This term we offer projects ranging from mobile cloud computing to NoSQL databases.

A list of current courses offered by our Chair can be also found in the CAMPUS-System of the RWTH Aachen.

Courses planned for the upcoming semester (SS 18)

  • Lecture: Social Computing

  • Social Computing is an area of computer science that is concerned with the intersection of social behavior and computational systems. It is based on creating or recreating social conventions and social contexts through the use of software and technology.

  • 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 (basic level): Blockchain Experience Lab

  • By the end of the experience lab on blockchain technology students will have an elaborated understanding of the concept of blockchains for distritbuted data and transaction management and its potential impact for the digitalization of processes and businesses.

  • Practical course (advanced level): Accenture Campus Innovation Challenge 2018: Greater than Reality

  • 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.

Working Groups

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