Knowledge Graphs

Undergraduate course

Course description

Objectives and Content

Students will learn theories, techniques, tools, and best practices for managing knowledge graphs. Students will acquire understanding and skills for programming applications that use and produce such data and metadata. Students will learn about existing sources of and standards for big, open, and semantic data. They will gain practical experience in developing knowledge graph-based applications using technologies such as RDF, RDFS, OWL, SPARQL, and JSON-LD.

Learning Outcomes

A student who has completed the course should have the following learning outcomes defined in terms of knowledge, skills and general competence:


The candidate has theoretical knowledge of basic concepts related to:

  • standards and techniques for knowledge graphs, for example RDF and SPARQL
  • semantic modelling of information systems, for example using RDFS and OWL
  • available sources of and vocabularies for big, open, and semantic data


The candidate

  • can develop advanced information models, for example ontologies
  • can use formats and languages such as RDF, RDFS, OWL, SPARQL, and JSON-LD
  • can use existing frameworks and tools for managing semantic knowledge graphs
  • can use existing frameworks and tools for developing knowledge graph-based applications

Level of Study


Semester of Instruction

Required Previous Knowledge
INFO132 Programming or equivalent
Recommended Previous Knowledge
  • Basic data skills in data management and artificial intelligence
  • Medium level skills in programming
  • For example:
  • INFO125 Data Management
  • INFO135 Advanced Programming
  • INFO180 Methods in Artificial Intelligence
  • Credit Reduction due to Course Overlap
    5 ECTS in combination with INFO116
    Access to the Course

    The course is open to students with admission to study at UiB.

    The course has 100 study places and enrolment is based on application in StudentWeb.

    Students who have this course as a compulsory part of their study plan will have priority access.

    The application deadline is Monday week 2.

    You will receive confirmation of whether you received a seat no later than Thursday the same week as the deadline.

    Teaching and learning methods
    14 two-hour lectures, 14 two-hour labs or seminars
    Compulsory Assignments and Attendance

    Compulsory participation: Attendance at labs (at least 75 %)

    Approved compulsory requirements are valid for the two following semesters.

    Forms of Assessment

    4 hours written exam

    The exam assignment will be given in the language of instruction in the course.
    The exam answer must be submitted in the same language as the exam assignment.

    Grading Scale
    Letter grade (A-F)
    Assessment Semester

    Assessment in teaching semester.

    A retake exam is arranged for students with valid absence according to ยง 5-5. If there is a retake exam, this will be available for students with the follow results/absences:

    • Medical certificate/valid absence
    • Interruption during the exam
    • Fail/failed

    If you have the right to take a retake exam and a retake exam is arranged for students with valid absences, you can sign up yourself in Studentweb after January 15/August 1.

    Course Evaluation
    The course is evaluated by students every three years, and by the responsible lecturer each year.
    Programme Committee
    The Programme Committee is responsible for the content, structure and quality of the study programme and courses