Master theses

Belgian parliamentary votes as a knowledge graph

Keywords: Linked Data, Artificial Intelligence, AI, Data Science, Knowledge Graph, Semantic Web

Supervision: Ben De Meester Anastasia Dimou

Students: max 1

  • Like govtrack.us, but for Belgian “kamer” votes

    • Other related work: https://progressivepunch.org/ , 538
  • Voting records are available on dekamer.be, but in a plaintext format not available for analysis (example)

  • Disclosing this data in a format ready for analysis would be great value, again, see govtrack.us

  • What needs to be done?

    • The voting data is structured in the form of CSV files embedded in different HTML pages,
    • There is much room for doing quality checks: did all (and only) 150 volksvertegenwoordigers either vote or abstain?
    • ontology engineering: making a schema for the voting data in RDF
  • Background knowledge

    • RDF and RML or willing to learn supe easy check tutorials at https://rml.io/docs/
    • Design of data models
    • HTML and JavaScript to create a website
    • Machine learning for data analysis
    • Interest in the Belgian political system! Or the courage to explore it