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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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Courses offered in WS 16/17

  • 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 chapter we can analyze and engineer advanced Web applications like recommender systems, collaborative editing and Web multimedia environments.

  • 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: 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: Big Data in Medical Informatics

  • This module will cover methods for the representation, interpretation and analysis of biomedical data. We will cover data interoperability methods, standards, terminologies for electronic health records and genomic data, as well as predictive analytics and decision making systems in medicine. Algorithmic and methodological approaches will be introduced with practical applications using the R programming language and the Galaxy open source platform. The topics of the lectures are • Biomedical data sources and standards • Biomedical data interoperability • Semantic technologies in biomedicine • Methods and tools for biomedical analysis • Predictive analytics and decision making systems • Genomic data analysis

  • 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 schema.org, OpenCalais, or Google's KnowledgeGraph). The module provides a theoretically grounded and practically oriented introduction to this area.

  • 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: 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: 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: Big Data Integration and Quality

  • The Big Data era is upon us: data is being generated, collected and analyzed at an unprecedented scale, and data-driven decision making is sweeping through all aspects of society. This seminar will discuss recent results in Big Data research, e.g., Big Data integration, Data Quality, Big Data Analytics, Text Mining, and Data Stream Processing.

  • Practical course (basic level): Unternehmensgründung und neue Medien

  • Unternehmensgründung und neue Medien ist ein Praktikum für Bachelor-Studenten, in dem die Erstellung eines komplexen Informationsprodukts erlernt wird. In diesem Semester stehen RESTful APIs in einer peer-to-peer Umgebung im Mittelpunkt. Voraussetzungen sind dabei Kenntnisse aus den Vorlesungen Programmierung sowie Datenstrukturen und Algorithmen.

  • 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 17)

  • 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.

  • 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.

  • Lecture: Scientific Data Management

  • The lecture will give a practical introduction into the data management in scientific applications (e.g., in life sciences or engineering). In addition to the theoretical foundations, the participants will learn to use state-of-the-art technologies to manage large scale data sets.

  • Proseminar: Algorithmen für die Entdeckung von Communities in sozialen Netzwerken

  • In diesem Proseminar werden sogenannte Overlapping Community Detection Algorithms (OCDA) mittels eines multi-perspektivischen Kriterienkatalogs untersucht. Neben klassischen informatischen Kriterien wie Korrektheit, Laufzeit und Speicherplatzverbrauch werden Kriterien wie Genauigkeit und Güte der gewonnen Information, aber auch die Anwendbarkeit auf bestimmte Formen sozialer Netzwerke (assoziativ und dissassoziativ) eingesetzt. Die Bewertungen werden beispielsweise durch Spinnendiagramme visualisiert. Das Proseminar bietet neben der üblichen Einführung in das wissenschaftliche Arbeiten spannende neue Formen des kollaborativen Forschen und Publizieren auf dem Web geübt. So werden die fachlichen Themen in Zweiergruppen mittels einer Wiki-Buch Plattform erarbeitet. Zusätzlich werden Gruppen zum fachlichen Begutachten, zum Web-Design und zur Animation von Algorithmen gebildet. Die Ergebnisse des Proseminars werden daher nicht in einer Schublade verschwinden, sondern auf dem Web als Open Content publiziert.

  • 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.

  • 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: 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: 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: Research Data Management

  • Research data are the foundation of scientific knowledge and new discoveries. Today we have a rapid explosion in scientific research. The amount of research published in 2014 (514,395) was more than triple the amount published in 1990 (136,545), more than 100 times the amount published in 1950 (4,432), and more than 3,000 times the amount published in 1940 (153). However due the lack of reproducibility, there is an increasing concern about the reliability of many experimental or observational results. With the increased digitization of research there are new possibilities to store and preserve research data with the benefits of making research more controllable and replicable. When data are available, findings described in publications can be validated, thereby increasing the trust. Also when data more easily reused, it will save resources and foster multidisciplinary research. Computer science tackle data sharing and reusability problem by developing new methods and tools to create an eScience ecosystem. In this seminar we will cover technologies to make data findable, diverse data access mechanisms, semantic interoperability technologies, data quality, provenance tracing, and reuse issues. Students with research interests in scientific data management, sharing, and reuse can participate this seminar and learn more.

  • Practical course (basic level): Scala-Programmierung und 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): 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): Arbeitswelt der Zukunft: 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.

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