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TDDD43 Advanced Data Models and Databases

Examples of exam question types


This is a collection of example exam question types.
Some old exams can be found here. (Observe that some topics in the old exams may not be included anymore, while some new topics may have appeared.)

Semi structured data, XML and RDF

  • 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.
  • 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 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 semantic 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 from a knowledge representation point of view 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 a 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
  • know 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 partial alignments in ontology alignment and discuss how well they perform

Page responsible: Patrick Lambrix
Last updated: 2013-09-02