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Information Systems
Prof. Dr. M. Jarke
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Prof. Dr. M. Jarke
RWTH Aachen
Informatik 5
Ahornstr. 55
D-52056 Aachen
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Past Terms

  • SS 18

    show courses
    • 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: 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: 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.

    • 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.

  • WS 17/18

    show courses
    • 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

    • 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 schema.org, 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.

  • SS 17

    show courses
    • 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: 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: 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.

  • WS 16/17

    show courses
    • 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.

  • SS 16

    show courses
    • 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: 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.

  • WS 15/16

    show courses
    • Lecture: Semantic Web

    • Der Kurs befähigt die Studierenden das notwendige Wissen zu entwickelt, um daten-orientierte Web Technologien zu verstehen. Darauf aufbauend werden die Studierenden werden ebenfalls die notwendigen Fähigkeiten und Kompetenzen entwickeln um diese Technologien in Semantic Web Applikationen anzuwenden.

    • 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: 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 & algorithms, network models and web engineering principles) of Web Science. We then give an overview on regular and random network models. We will learn fundamental algorithms for web page ranking like PageRank and HITS as well as advanced community detection algorithms. The anatomy of recommender systems and dynamic processes on complex networks will finish this part. In the engineering part we dig into emerging cloud computing approaches and Post-HTTP protocols like the XMPP and WebRTC. 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 video annotation environments, personal learning environments and storytelling environments.

    • 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 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 with regard to ….. An understanding of the basic concepts will then make it possible to discuss opportunities and challenges of Linked Data.

    • Seminar: Big Data

    • 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, Big Data Analytics, Text Mining, 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.

  • SS 15

    show courses
    • 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.

    • Seminar: Web Science Seminar

    • Web Science has been becoming a new interdisciplinary study field between computer science, mathematics, sociology, and economics. This seminar researches advanced Web analytics and Web engineering topics in Web Science probably leading to master thesis topics. Topics include: network evolution models and network dynamics, (overlapping) community detection, recommender systems, adaptation and personalization in Web Environments, Educational Web and Web Credibility. Students do not only learn to write and present scientific papers but also to peer review them.

    • Practical course (advanced level): Smart Cities - Accenture Campus Innovation Challenge 2015

    • 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.

  • WS 14/15

    show courses
    • 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: 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 & algorithms, network models and web engineering principles) of Web Science. We then give an overview on regular and random network models. We will learn fundamental algorithms for web page ranking like PageRank as well as advanced community detection algorithms like HITS. The anatomy of recommender systems and dynamic processes on complex networks will finish this part. In the engineering part we dig into emerging cloud computing approaches and Post-HTTP protocols like the XMPP and Web Sockets. 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 video annotation environments, personal learning environments and storytelling environments.

    • 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.

  • SS 14

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    • 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: 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: Web Science Seminar

    • Web Science has been becoming a new interdisciplinary study field between computer science, mathematics, sociology, and economics. This seminar researches advanced theoretical and practical topics in Web Science probably leading to master thesis topics. Topics include: network evolution models and network dynamics, local-based (overlapping) community detection, tag recommender systems, link prediction in dynamic social networks, (overlapping) community detection in signed social networks, adaptive community detection in dynamic networks, cascading behaviors and their features in complex networks, peer-to-peer browser based collaboration based on WebRTC, mobile cloud computing, mobile shared editing.

    • Practical course (advanced level): Design for Analytics: Accenture Campus Challenge 2014

    • Die Campus Challenge ist ein von Accenture initiierter Wettbewerb für Studenten technischer und wirtschaftswissenschaftlicher Studiengänge. Die Studenten 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.

  • WS 13/14

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    • 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 & algorithms, network models and web engineering principles) of Web Science. We then give an overview on regular and random network models, influence, economic, and biological networks. We will learn basic algorithms for web page ranking like PageRank and HITS as well as advanced community detection algorithms. The anatomy of commercial recommender systems and dynamic processes on complex networks will finish this part. In the engineering part we dig into emerging cloud computing approaches like MapReduce and advanced topics in network protocols like the XMPP. 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 video annotation environments, personal learning environments and storytelling environments.

    • 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.

    • 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 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.

  • SS 13

    show courses
    • 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: Web Science Seminar

    • Twenty years after the birth of the World Wide Web, Web Science has been becoming a new study field in Computer Science. This seminar researches advanced theoretical and practical topics in Web Science probably leading to master thesis topics. Topics include: Browser-based P2P Connections using WebRTC, Commsonomies, Context-Aware Recommendations, Frameworks for Shared Editing, Intelligent Tutoring Systems, Life Cycles of Community Structure, Link Prediction in Social Networks, Multi-Agent Simulation of Social Networks, Opinion Mining in Dynamic Social Networks, Public Displays for Advanced Community Interaction, Social Network Analysis Methods for Tag Networks, Social Network Analysis in Open Source Software Community Research, Visual Analytics in Social Networks, Web Success Models & Metrics, Web Usage Mining, and Web-based Requirements Engineering.

    • Practical course (advanced level): Digitale Revolution (Accenture Campus Challenge)

    • Die Campus Challenge ist ein von Accenture initiierter Wettbewerb für Studenten technischer und wirtschaftswissenschaftlicher Studiengänge. Die Studenten 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.

    • Practical course (advanced level): Application of Multi-Agent Simulation for Interdisciplinary Research and Teaching

    • In this module students have the opportunity to jointly work on state-of-the-art research projects with students from other disciplines and faculties. Students will first be introduced to multi-agent simulation (MAS) on a conceptual basis. They will then form interdisciplinary teams with students from economics and sociology for working on a concrete research topic with MAS. In interim presentations the teams will report on their progress and will receive feedback for further development. In the final presentation students will present and discuss their project results. In addition, the group will reflect on communication and related processes during the project.

  • WS 12/13

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    • Lecture: Web Science

    • 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 & algorithms, network models and web engineering principles) of Web Science. We then give an overview on regular and random network models, influence, economic, and biological networks. In the following we study dynamic processes on complex networks (emergence, percolation, epidemics, synchrony, walking and searching, net gain and repeated games). In the engineering part we dig into emerging cloud & grid computing approaches like GoogleApp, Google Wave (XMPP) and Bittorrent. With the knowledge gained in the preceding chapter we can analyse and engineer advanced web applications like the Wikipedia, personal learning environments and massive 3D multimedia environments.

    • 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.

  • SS 12

    show courses
    • 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: 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.

    • Seminar: Web Science Seminar

    • Twenty years after the birth of the World Wide Web, Web Science has been becoming a new study field in Computer Science. This seminar researches advanced theoretical and practical topics in Web Science probably leading to master thesis topics. Topics include but are not limited to: Linked Data, Trend Analysis, Open Data Initiatives, Media Classification and Analysis, Web Metadata, Folksonomies, Tagging Networks, Web User Modelling and Analysis (User Behavior, Social Interaction), Communities and Web Lifestyles, Web Analysis, Web Search, Collaborative Information Management (Collaborative Production, collective Intelligence), Adaptive Web Hypermedia, Cloud Computing, Advanced Web Protocols (XMPP), Web Services and Web Application Engineering.

    • Practical course (advanced level): CSCW Experience Lab

    • The goal of this lab is to gain practical experience in collaboration by working on a project called Lightweight Collaboration Suite. Each student team consisting of three students will work on one subproject under different collaborative settings (synchronously, asynchronously, face-to-face, remote).

    • Practical course (advanced level): Accenture Campus Challenge 2012: Enterprise 2.0 - Plattformen

    • Die Campus Challenge ist ein von Accenture initiierter Wettbewerb für Studenten technischer und wirtschaftswissenschaftlicher Studiengänge. Die Studenten 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.

  • WS 11/12

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    • 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: Web Science

    • 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 & algorithms, network models and web engineering principles) of Web Science. We then give an overview on regular and random network models, influence, economic, and biological networks. In the following we study dynamic processes on complex networks (emergence, percolation, epidemics, synchrony, walking and searching, net gain and repeated games). In the engineering part we dig into emerging cloud & grid computing approaches like GoogleApp, Google Wave (XMPP) and Bittorrent. With the knowledge gained in the preceding chapter we can analyse and engineer advanced web applications like the Wikipedia, personal learning environments and massive 3D multimedia environments.

    • 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 "Serious Games" im Mittelpunkt. Voraussetzungen sind dabei Kenntnisse aus den Vorlesungen Programmierung sowie Datenstrukturen und Algorithmen.

    • Practical course (advanced level): Hightech 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.

  • SS 11

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    • Seminar: Algorithms for Complex Networks

    • Networks play a central role in many sectors employing information technology, such as communication, mobility, and transport, social interactions and political activities. Its complex and nearly incomprehensible entanglements of various structures and its huge effect on seemingly unrelated institutions and organizations, the need to understand large networks, their complex structures, and the processes governing them is becoming very important for many application areas and use cases, such as recommender systems, overlapping communities, mobile communities, multimedia networks, software artifact networks, software repositories, digital libraries, web 2.0 artifacts, XMPP protocol artifacts, innovation networks and learning networks. To analyze existing large and complex networks and to design new and more efficient algorithms for solving various problems on these networks is an important task since many of them have become so large and complex that classical algorithms are not sufficient anymore. This seminar tries to get an overview on existing algorithms and open research challenges leading to future research to be carried out in master thesis and Phd thesis work.

    • Practical course (advanced level): Hightech 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.

    • Practical course (advanced level): CSCW Experience Lab

    • The goal of this lab is to gain practical experience in collaboration by working on a selected project. Each student team will work on one project under different collaborative settings (synchronously, asynchronously, face-to-face, remote).

    • Practical course (advanced level): Accenture Campus Challenge 2011: Wettbewerbsvorteile durch Smart Sustainability

    • Die Campus Challenge ist ein Wettbewerb, bei dem Sie als Team im Frühjahr/Sommer 2011die Möglichkeit haben, Ihre wissenschaftlichen Methoden und Kenntnisse mit unternehmerischem Denken und unternehmerischer Umsetzungsfähigkeit zu kombinieren. Das Projekt wird von der Ideenfindung bis hin zur Präsentation Ihres Konzeptes vor einer hochkarätigen Jury am deutschen Hauptsitz von Accenture in Frankfurt/Kronberg intensiv durch Accenture-Coaches und die Betreuer der RWTH begleitet.

  • WS 10/11

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    • Lecture: Web Science

    • 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 & algorithms, network models and web engineering principles) of Web Science. We then give an overview on regular and random network models, influence, economic, and biological networks. In the following we study dynamic processes on complex networks (emergence, percolation, epidemics, synchrony, walking and searching, net gain and repeated games). In the engineering part we dig into emerging cloud & grid computing approaches like GoogleApp, Google Wave (XMPP) and Bittorrent. With the knowledge gained in the preceding chapter we can analyse and engineer advanced web applications like the Wikipedia, personal learning environments and massive 3D multimedia environments.

  • SS 10

    show courses
    • 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.

    • Practical course (basic level): Mobile Cloud Computing Lab

    • In this basic level lab course students will get the chance to operate on up to 128 virtual servers of Sun Enterprise T5240 based on Apache Hadoop and Google AppEngine in order to provide services for the consumption on various mobile clients including the Android devices such as Motorola Droid/Milestone and HTC Hero or the Apple iPhone. Tasks will mainly be located in the domain of mobile Multimedia Management, e.g. Mobile Augmented Reality scenarios. Further details will be announced later.

    • Practical course (advanced level): Accenture Campus Challenge 2010: Der Arbeitsplatz der Ne(x)t Generation

    • Die Campus Challenge ist ein Wettbewerb, bei dem Sie als Team im Frühjahr/Sommer 2010 die Möglichkeit haben, Ihre wissenschaftlichen Methoden und Kenntnisse mit unternehmerischem Denken und unternehmerischer Umsetzungsfähigkeit zu kombinieren. Das Projekt wird von der Ideenfindung bis hin zur Präsentation Ihres Konzeptes vor einer hochkarätigen Jury am deutschen Hauptsitz von Accenture in Frankfurt/Kronberg intensiv durch Accenture-Coaches begleitet.

  • WS 09/10

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    • Lecture: Implementation of Databases

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

  • SS 09

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