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Knowledge Graphs

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

Main content

Level of Study

Bachelor

Teaching semester

Spring

Objectives and Content

Students will learn theories, techniques, tools, and best practices for managing semantic data and metadata. Students will acquire understanding and skills for programming applications that use and produce such data. Students will learn about existing sources of and standards for big, open, and semantically marked-up data. They will gain practical experience in developing semantic model-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:

Knowledge

The candidate has theoretical knowledge of basic concepts related to:

  • standards and technologies for semantic information systems, for example using RDF and SPARQL
  • semantic modelling of interoperable information systems, for example using RDFS and OWL
  • available sources of and vocabularies for big, open, and semantically marked-up data

Skills

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 data and metadata
  • can use existing frameworks and tools for developing semantic applications

Required Previous Knowledge

INFO135 Advanced Programming

Recommended Previous Knowledge

Basic data skills in data management and artificial intelligence

Medium level skills in programming

INFO125 Data Management

INFO132 Programming

INFO180 Methods in Artificial Intelligence

Credit Reduction due to Course Overlap

5 ECTS in combination with INFO116

Access to the Course

Open

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

  • 3 hours written exam (60%)
  • 1 group assignment (40%)

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

Exam information