Study Guide@lith
 

Linköping Institute of Technology

 
 
Valid for year : 2017
 
TDDD43 Advanced Data Models and Databases, 6 ECTS credits.
/Datamodeller och databaser, avancerad kurs/

For:   CS   D   DAV   I   Ii   IT   U  

 

Prel. scheduled hours: 42
Rec. self-study hours: 118

  Area of Education: Technology

Main field of studies: Computer Engineering, Information Technology

  Advancement level (G1, G2, A): A

Aim:
The increase of variation in modern data applications and in data sets available on the Internet puts higher and higher requirements on technology for information retrieval and storage. The aim of this course is to gain theoretical and practical knowledge about principles for storage and retrieval in text, semi-structured and structured data. The course also discusses alternative data models for databases, XML and NoSQL databases and representation of semantic information, e.g. knowledge bases. After the completion of the course you should be able to:
  • explain differences between text, semi-structured and structured data, data models and knowledge-based data; further, given a data set state advantages and disadvantages of search and storage techniques
  • describe different algorithms for information retrieval in text
  • describe the properties of semi-structured data and how it differs from text and traditional data models
  • represent a given semi-structured data set using XML or RDF
  • design, implement and use XML schema and the query language XQuery
  • represent a given semi-structured data set using an object-oriented data model
  • describe the main principles of NoSQL databases
  • describe the main principles of knowledge bases
  • design, implement and use a knowledge base represented using OWL
  • describe methods and difficulties for data integration


Prerequisites: (valid for students admitted to programmes within which the course is offered)
Programming, Databases.

Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshhold requirements for progression within the programme, or corresponding.

Organisation:
The course consists of lectures, laboratory work and a project. Lectures are devoted to theory and methodology, and give practical examples. During the laboratory work students work with a number of exercises that illustrate principles for the data models, algorithms and database models that are discussed during the lectures.
The course runs over the entire autumn semester.


Course contents:
  • Information retrieval for text; Models, evaluation, query languages, query operations, text operations, indexing and search.
  • Semi-structured data: representation of semi-structured data using XML and RDF.
  • Data models: NoSQL and XML databases, XQuery, XML Schema, RDF.
  • Knowledge bases: ontologies, description logics, OWL, query languages and knowledge deduction for knowledge bases.
  • Data integration.


Course literature:
Articles

Examination:
Written examination
Laboratory work
Voluntary assignment
3 ECTS
3 ECTS
0 ECTS
 



Course language is English.
Department offering the course: IDA.
Director of Studies: Patrick Lambrix
Examiner: Patrick Lambrix
Link to the course homepage at the department


Course Syllabus in Swedish

Linköping Institute of Technology

 


Contact: TFK , val@tfk.liu.se
Last updated: 05/24/2017