Databases and Information Systems
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Data Analysis and Query Languages


[19.06.2017, 10:00] The written exam is taking place on 29.09.2017 at 10 o'clock in room 101-00-036.


Prof. Georg Lausen


Anas Alzoghbi and Victor Anthony Arrascue Ayala


Course Contents

The course introduces into the topic of Data Analysis and Query Languages. As motivation, the integration problem of data published on the Web is discussed. The W3C-Standard RDF for data representation is introduced and the RDF query language SPARQL is presented in detail. To remedy inherent limitations of querying, data analysis techniques are presented which have their roots in Information Retrieval and Machine Learning. Data representation leveraged by data analysis allows to replace querying by proposing recommendations. Wide spread techniques and current research directions in the recommender systems field are presented.


Slides, exercise sheets and other material can be found in ILIAS.

Necessary Prerequisites

The key course (Kursvorlesung) 'Databases and Information Systems' or an equivalent Database course.

Time, Location and Organization:

Lecture: Tuesday 14 - 16 and Thursday 10 - 12 (in case there is no tutorial scheduled)

Tutorials: Thursday 10 - 12 (in case there is no lecture scheduled)

Location: Geb. 52, Seminar 02-017

Language: English

ECTS: 6 Points

Program of Study: Bachelor CS, Master CS/ESE, Lehramt Informatik


Exam modality: written


  • Exercises will consist of theoretical and pratical tasks.
  • Pratical tasks require some programming proficiency but this will be very helpful to directly apply the learnt knowledge.
  • 50% of the overall points as a prerequisite for the exam.

Literature and Additional Material

  • Foundations of Semantic Web Technologies. Pascal Hitzler, Markus Krötzsch, Sebastian Rudolph. Chapman and Hall/CRC Press 2010, ISBN 9781420090505
  • Anand Rajaraman and Jeffrey David Ullman. 2011. Mining of Massive Datasets. Cambridge University Press, New York, NY, USA. Publisher. Download (see terms of use).
  • Introduction to information retrieval. Christopher D. Manning, Prabhakar Raghavan, Hinrich Schütze. Cambridge University Press 2008, ISBN 978-0-521-86571-5, pp. I-XXI, 1-482
  • Recommender Systems Handbook. Editors: Francesco Ricci, Lior Rokach, Bracha Shapira, Paul B. Kantor. Springer Verlag, 2011.
  • Recommender Systems - An Introduction. Dietmar Jannach, Markus Zanker, Alexander Felfernig, Gerhard Friedrich. Cambridge University Press 2010, ISBN 978-0-521-49336-9, pp. I-XV, 1-335