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Module guide WS 2018-2022

Module CS3202-KP04, CS3202

Nonstandard Database Systems (NDB)

Duration:


1 Semester
Turnus of offer:


not available anymore
Credit points:


4
Course of studies, specific field and terms:
  • Bachelor Medical Informatics 2014 (optional subject), computer science, 5th or 6th semester
  • Bachelor Media Informatics 2014 (optional subject), computer science, 5th or 6th semester
  • Bachelor Computer Science 2014 (optional subject), central topics of computer science, 5th or 6th semester
  • Bachelor Medical Informatics 2011 (optional subject), Applied computer science, 4th to 6th semester
  • Master Computer Science 2012 (optional subject), specialization field media informatics, 2nd or 3rd semester
  • Master CLS 2010 (optional suject), computer science, Arbitrary semester
  • Bachelor CLS 2010 (optional subject), computer science, 6th semester
  • Master Computer Science 2012 (optional subject), advanced curriculum distributed information systems, 2nd or 3rd semester
  • Bachelor Computer Science 2012 (optional subject), central topics of computer science, 5th or 6th semester
Classes and lectures:
  • Nonstandard Database Systems (exercise, 1 SWS)
  • Nonstandard Database Systems (lecture, 2 SWS)
Workload:
  • 45 Hours in-classroom work
  • 65 Hours private studies
  • 10 Hours exam preparation
Contents of teaching:
  • introduction
  • semistructured databases
  • Temporal and spatial databases (temporally restricted validity, multidimensional index structures)
  • Sequence Databases
  • Databases for data streams (window concept)
  • Databases for incomplete information (e.g., constraint databases)
  • Probabilistic databases
  • Databases with answer ranking (top-k queries)
Qualification-goals/Competencies:
  • Knowledge: Students can name the main features of standard databases and, in addition, can explain which non-standard database models emerge if features are dropped. They can describe the main ideas behind non-standard databases presented in the course by explaining the main features of respective query languages (syntax and semantics) as well as the most important implementation techniques used for their practical realization.
  • Skills: Students can apply query languages for non-standard data models introduced in the course to retrieve desired structures from sample datasets in order to satisfy information needs specified textually in natural language. Students are able to represent data in the relational data model using encoding techniques presented in the course such that they can demonstrate how new formalisms relate to or can be implemented in SQL (in particular, SQL-99). In case an SQL transformation cannot be found, students can explain and apply dedicated algorithms for query answering. Students can demonstrate how index structures help answering queries fast by showing how index structures are built, updated, and exploited for query answering. The participants of the course can derive query answers by evaluating queries step by step and by deriving optimized query execution plans.
  • Social skills: Students work in teams to handle assignments, and they are encouraged to present their solution to other students in small presentations (in lab classes). In addition, self-dependence is fostered by giving pointers to query evaluation engines for various formalism presented in the lecture such that students get familiar with data models and query languages by self-controlled work.
Grading through:
  • Written or oral exam as announced by the examiner
Requires:
Responsible for this module:
Teachers:
Literature:
  • S. Abiteboul, P. Buneman, D. Suciu: Data on the Web - From Relations to Semistructured Data and XML - Morgan Kaufmann, 1999
  • J. Chomicki, G. Saake (Eds.): Logics for Databases and Information Systems - Springer, 1998
  • P. Rigaux, M. Scholl, A. Voisard: Spatial Databases With Applications to GIS - Morgan Kaufmann, 2001
  • P. Revesz: Introduction to Constraint Databases - Springer, 2002
  • P. Revesz: Introduction to Databases- From Biological to Spatio-Temporal - Springer 2010
  • S. Ceri, A. Bozzon, M. Brambilla, E. Della Valle, P. Fraternali, S. Quarteroni: Web Information Retrieval - Springer, 2013
  • S. Chakravarthy, Q. Jiang: Stream Data Processing A Quality of Service Perspective - Springer, 2009
  • D. Suciu, D. Olteanu, Chr. Re, Chr. Koch: Probabilistic Databases - Morgan & Claypool, 2011
Language:
  • offered only in German
Letzte Änderung:
10.10.2019