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Undergraduate course

Knowledge Graphs

  • ECTS credits10
  • Teaching semesterSpring
  • Course codeINFO216
  • Number of semesters1
  • LanguageEnglish
  • Resources

Main content

Level of Study


Teaching semester


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

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:

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 the UiB. The course has 100 study places. Students who have this course as a compulsory part of their study plan will have priority access

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

Grading Scale

Letter grade (A-F)

Assessment Semester

Assessment in teaching semester. Only students who have a valid document of absence will be entitled to take a new written exam the following semester.

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

Contact Information