About this course

The course delivers an introduction to foundational aspects of practice and theory in data management, with a focus both on relational databases and non-relational knowledge bases. Topics to be discussed include:

  • Principles of good practice in data managment: FAIR principles, data and metadata quality, dealing with insufficiently annotated data.
  • Relational databases: SQL (structured query language), database schemas, user interfaces, entity-relationship diagrams and connection to object-oriented programming.
  • Knowledge graph technology: RDF, semantically characterized data exchange, ontology development.

Learning outcome

The participants develop the ability to

  • assess requirements and evaluate/improve processes in data managment in accordance with established recommendations for good practice;
  • work with relational databases in a systematic way and support users by developing simple interfaces in Python;
  • use non-relational databases, specify metadata and communicate information following the formalism based on RDF/OWL.

Competencies from the course can be developed further through INF131B (Introduction to logic).

  • Learning activities

    Lectures combined with tutorials tailored to the students pre-established competencies and skills.

  • Teaching support

    The main lecturer + teaching assistant(s) will assist and support the students.

  • Syllabus

    To be announced at the beginning of the course.

  • Prerequisites

    Programming and Data Processing (INF120) or equivalent

  • Assessment method

    Portfolio evaluation

  • About use of AI

    K2. Specified use of AI. No generative AI tools whatsoever are permitted when working on submissions that contribute to the grade by portfolio evaluation. For other purposes, they can be used freely.

    Descriptions of AI-category codes.

  • Examiner scheme

    The external and internal examiner jointly prepare the exam questions and the correction manual.

  • Admission requirements

    REALFAG