Semantic Web

Welcome to the Semantic Web zone!



  • Please work alone or in pairs.
  • After each class, please prepare a report and send it to Krzysztof Kutt.
    • Write the report in English or Polish.
    • Be concise and specific.
    • Name the file as follows: semweb2019_labN_surname1[_surname2].pdf, using your name(s) and the number of the lab e.g., semweb2019_lab1_hewlett_packard.pdf
    • If you need to send additional files (besides the report in pdf), zip them into a *.zip or *.tar.gz file and name accordingly.
    • DEADLINE for the reports: a minute before the next lab.
    • If you submit the report after the deadline you will get -1 point for each started day.
  • You may get 0-2 points for each report:
    1. Answer the questions marked 8-) in lab instructions.
    2. (Optionally) Add extra feedback section in the report to earn extra credit.
  • If you get at least 75%, you will be exempted from the Test (and get as many points as you earned from the reports).


No. Date Lab Instruction
1. 01.10.2019 Introduction. Modeling knowledge with RDF
2. 08.10.2019 Advanced modeling with RDF
3. 15.10.2019 Querying the Semantic Web with SPARQL
4. 29.10.20191)
5. 05.11.2019 Introduction to ontologies
6. 12.11.2019 14:00 Ontology engineering with Protégé
7. 12.11.2019 15:30 Reasoning with Ontologies
OPTIONAL: Intro to Description Logics
TEST (30 minutes)

Attendance and notes


  • Org:
    • Work in teams of 2-3 students.
    • Final raport and working piece of code is evaluated (Jupyter Notebook, PDF, whatever you want; code will be presented on your own laptops, so there are no limitations on technology used)
    • Deadline: before the exam! ;-)
  • Topics:
    • [1-2 groups] Review of knowledge graphs embeddings methods (with evaluation of existing libraries in Python) – may be extended as a workshop project (topic listed on SBK list)
    • [1 group] Loki on triple store – may be extended as a workshop project (topic listed on KKT list)
    • [1-3 groups] Semantic mashup – link data from at least 3 sources (eg. Wikidata,, dataset from LOD Cloud, polish GUS data) in a fancy way (e.g. question answering systems, recommendation system, some analysis using statistical methods or machine learning methods)
    • [1 group] Beyond the RDF/OWL – review of other knowledge graphs approaches = „What do people do when they say they do knowledge graphs?” (with some code if possible) (start from: A Common Sense View of Knowledge Graphs)

Additional materials

Additional labs

  1. Semantic Web Programming (external copyrights)
    • JavaOne Online Technical Sessions and Labs: JavaOne2009 - Lab-4449: Semantic Web Programming
    • Uses: Jena Framework, Pellet Reasoner, NetBeans IDE


Old projects

General reading





TED talks:





Online Semantic Web courses:

Semantic Web tools and applications:

Triplestores / graph databases:


These course materials are prepared by GEIST Research Group and are available according to license.

If you have any questions, suggestions or concerns regarding the course materials and lab instructions, please contact us:

There is no lab on 22.10.2019 :!:
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