TH Köln

Master Digital Sciences

Documents for Study Program Accreditation

Module »Linked-Open Data and Knowledge Graphs« (LOD)

Organizational Details

Responsible for the module
Prof. Dr. Konrad Förstner (Faculty F03)
Language
English
Offered in
Winter Semester (Duration 1 Semester)
Location
Campus Köln Süd, or remote
Number of participants
minimum 6, maximum 20
Precondition
none
Recommendation
Basic Python programming skills
ECTS
6
Effort
Total effort 180h
Total contact time
60h (30h lecture / 15h exercise / 15h project supervision)
Time for self-learning
120h (containing 120h self-organized project work)
Exam
Written exam in conjunction with assignments (2 partial exams)
Competences taught by the module
Implement Concepts, Deploy Products, Optimize Systems, Apply Standardization
General criteria covered by the module
Interdisciplinarity, Digitization

Mapping to Focus Areas

Below, you find the module's mapping to the study program's focus areas. This is done as a contribution to all relevant focus areas (in ECTS, and content-wise). This is also relevant for setting the module in relation to other modules, and tells to what extent the module might be part of other study programs.

Focus Area ECTS (prop.) Module Contribution to Focus Area
Generating and Accessing Knowledge 4

The course introduces the basic concepts of Linked Open Data (LOD) as well as the construction of knowledge graphs.

Acting Responsibly 1

The course introduces the basic concepts of Linked Open Data (LOD) as well as the construction of knowledge graphs.

Designing Innovations and Products 1

The course introduces the basic concepts of Linked Open Data (LOD) as well as the construction of knowledge graphs.

Learning Outcome

The course introduces the basic concepts of Linked Open Data (LOD) as well as the construction of knowledge graphs.

Equiped with this understanding participants will explore real world applications like Wikidata and Open Research Knowledge Graph (ORKG).

After finishing this course students are able to use, extend and construct knowledge graphs.

Module Content

  1. Linked Open Data
  2. Knowledge Graphs
  3. Semantic Searches
  4. RDF
  5. SPARQL
  6. Applications - Wikidata and ORKG

Forms of Teaching and Learning

The class will follow a flipped classroom approach and involve self-studying based on provided reading, audio and video material. Excersises in which small solutions are implemented will help the participants to explore available tools and help to gain practical skills to work with knowledge graphs.

Learning Material Provided by Lecturer

  • lecture slides and videos
  • exercises

Literature