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TDDD43 Advanced Data Models and Databases

Examples of exam questions


This is a a collection of what we expect you to know for the exam. Samples of old exams can be found here.
Questions given on the exam will concentrate on these topics:

Semi structured data

  • describe general properies of semi-structured data
  • describe the general properties and concepts of XML
  • describe the general properties and concepts of RDF
  • model a given scenario or set of data in the OEM
  • model a given scenario (text or ER) using XML
  • model a given scenario (text or ER) using RDF
  • use and understand model languages: DTD, XML schema, RDF schema
  • reason about the quality if a given XML model and propose alternative solutions.
  • describe the general idea and define the properties of a dataguide.
  • define minimal and strong dataguides.
  • given a description of data construct the minimal and strong dataguides for thet data.

Querying semi structured data

  • explain how the primitive constructs in XPath corresponds to the general concepts in XML
  • write an XPath query
  • write an XQuery query
  • explain how the pimitive constructs of SPARQL correspond to the general concepts in RDF

Efficient storage for XML

  • Explain the main principle behind the mapping of XML d model into relational model
  • Explain the main principle of mapping XML queries into SQL
  • Explain the basic principle of the node/edge based mapping schema
  • Explain the basic principle of interval-based approach
  • Explain the basic principle of path-based mapping

Information Retrieval

  • Describe the components of IR models
  • Explain term conjunctive component
  • Explain the basic principle of boolean model for IR
  • Describe the advantages and drawbacks of boolean model
  • Define term weighting
  • Define TF-IDF
  • Describe vector model for IR
  • Explain the basic priciple of probabilistic model for IR
  • Define Steiner tree
  • Explain algorithms for Steiner tree computation
  • Describe Fagin's algorithm

NoSQL databases

  • Explain the basic concepts of NoSQL.
  • Explain the difference of vertical scalability and horizontal scalability.
  • Explain the CAP theorem.
  • Understand the principles of consistent hashing.
  • Understand the principles of vector clocks.
  • Explain the basic principles of MapReduce.

Semantic web and ontologies

  • describe the problems in the current web and the vision of the sematic web
  • show how semantic annotations based on ontologies would help solve the problems of the current web
  • explain what ontologies are used for
  • describe and explain the OBO Foundry principles
  • explain and give examples of the components of ontologies
  • describe the different kinds of ontologies

Description logics and OWL

  • describe the notions of T-box, A-box, knowledge base, subsumption, satisfiability
  • model a given a scenario using description logics
  • give the semantics for a given description logic construct
  • describe the difference between open-world assumption and closed-world assumption
  • describe the different reasoning services
  • given 2 concepts, prove that one concept subsumes the other (or not) using the tableau algorithm
  • know some reasons for intractibility, undecidability of description logics
  • know the difference between the 3 variants of OWL

Data source integration

  • describe the problems occuring with data source integration
  • describe the different steps in data source integration
  • describe the method for integration based on link driven federations
  • understand a query in the SRS query language
  • advantages and disadvantages of link driven federations
  • describe the method for integration based on mediation
  • describe mappings and query processing in GAV and LAV
  • given two data sources (schema, data guide, data, ...), integrate them using GAV or LAV
  • define the notion of capabilities

Ontology alignment

  • describe the problem of ontology alignment
  • describe a framework for ontology alignment and explain the different components
  • explain and give examples for different strategies for preprocessing/matching/combining/filtering
  • explain how to evaluate ontology alignment strategies / systems
  • understand performance of different approaches
  • describe different approaches for recommending ontology alignment strategies
  • describe different approaches for using PRA in ontology alignment and discuss how well they perform

Page responsible: Patrick Lambrix
Last updated: 2012-12-15