Advanced Data Models and Databases, ht 2016
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 representation of semantic information.
GoalsAfter the completion of the course you should be able to:
- explain differences between text, semi-structured, data models and knowledge-based data
- for a given 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
- explain key notions and algorithms related to noSQL databases
- describe the main principles of knowledge bases
- design, implement and use a knowledge base represented using OWL
- represent knowledge using description logics
- explain key notions related to the Semantic web
- describe methods and difficulties for data integration
First lecture: Wednesday, 31/8, 15:15-17:00.
Time table for HT1 is available on the schedule server. (Together with TDDD43)
Time table for HT2 is also available (same link).
Page responsible: AdvDB
Last updated: 2016-11-15