Module 39-M-Inf-SW Semantic Web

Faculty

Person responsible for module

Regular cycle (beginning)

Every winter semester

Credit points and duration

5 Credit points

For information on the duration of the modul, refer to the courses of study in which the module is used.

Competencies

Non-official translation of the module descriptions. Only the German version is legally binding.

Topics conveyed in the lecture give an insight into the area of the Semantic Web and semantic technologies. At the end of the course students should be familiar with the fundamental formalisms and data models of the Semantic Web. They should also be capable to develop simple applications based on semantic technologies.

Content of teaching

This module discusses the principles of the Semantic Web as well as semantic information systems and semantic technologies and their applications. We will get acquainted with the data models and interchange formats of the Semantic Web (RDF, RDFS, OWL, SKOS) and the query language SPARQL.The module also introduces the basics of ontologies and deals with their design and modelling. In this context, we discuss current methodologies for the modeling of ontologies by using modelling tools, e.g. Protégé. We also discuss semantic data bases as a storage for RDF data and applications of semantic technologies. Furthermore, we introduce the idea of Open Linked Data. Practical exercises using modelling tools like Protégé and semantic data bases like SESAME complete the module.

Literature:

  • Pascal Hitzler, Markus Krötzsch, Sebastian Rudolph, York Sure, "Semantic Web Grundlagen", Springer, 2008 (ISBN: 978-3-5403-3994-6)
  • Pascal Hitzler, Markus Krötzsch, Sebastian Rudolph, "Foundations of Semantic Web Technologies", CRC, 2009 (ISBN: 978-1-4200-9050-5)

Recommended previous knowledge

Competences as gained through, e.g., 36-Inf-1 Algorithmen und Datenstrukturen and 39-Inf-6 Grundlagen Theoretischer Informatik (esp. Logik).
Basic knowledge of mathematics

Necessary requirements

Explanation regarding the elements of the module

The (partial) examination of the module can be performed as "ungraded" in some study programs at the students choice. Before the examination a respective determination must be carried out, a later modification (graded - ungraded) is impossible. If the "ungraded" option is chosen, it is not possible to include this module in a study program where this module is deemed to enter the calculation of the overall grade.

Module structure: 0-1 bPr, 0-1 uPr 1

Courses

Semantic Web
Type exercise
Regular cycle WiSe
Workload5 60 h (30 + 30)
Semantic Web
Type lecture
Regular cycle WiSe
Workload5 60 h (30 + 30)
LP 2

Examinations

portfolio with final examination
Allocated examiner Teaching staff of the course Semantic Web (exercise)
Weighting without grades
Workload 30h
LP2 1

In some degree programmes of the Faculty of Technology, the module examination can also be "ungraded" at the student's discretion (see explanations of the module elements and the respective subject-specific regulations). If the ungraded option is selected, it is not possible to use this module for a degree programme in which this module is taken into account in the overall grade calculation.
See below for explanations of this examination (graded examination option).

portfolio with final examination
Allocated examiner Teaching staff of the course Semantic Web (exercise)
Weighting 1
Workload 30h
LP2 1

Exercises based on the material covered in the lectures (pass mark of 60%, students have to be able to demonstrate how they arrived at the solution). Exercises are usually handed out on a weekly basis. Final oral presentation (15 - 25min.).

The module is used in these degree programmes:

Degree programme Profile Recom­mended start 3 Duration Manda­tory option 4
Data Science / Master of Science [FsB vom 06.04.2018 mit Änderungen vom 01.07.2019, 02.03.2020, 21.03.2023 und 10.12.2024] Variante 1 3. one semester Compul­sory optional subject
Data Science / Master of Science [FsB vom 06.04.2018 mit Änderungen vom 01.07.2019, 02.03.2020, 21.03.2023 und 10.12.2024] Variante 2 3. one semester Compul­sory optional subject
Intelligent Systems / Master of Science [FsB vom 27.07.2018 mit Änderung vom 04.06.2020] 1. o. 3. one semester Compul­sory optional subject
Intelligent Systems / Master of Science [FsB vom 17.12.2012 mit Änderungen vom 15.04.2013, 01.04.2014, 15.10.2014, 02.03.2015 und Berichtigung vom 17.11.2014] 1. o. 3. one semester Compul­sory optional subject
Informatics for the Natural Sciences / Master of Science [FsB vom 30.09.2016 mit Berichtigung vom 10.01.2017 und Änderungen vom 15.09.2017, 02.05.2018, 04.06.2020 und 31.03.2023] 1. o. 3. one semester Compul­sory optional subject
Informatics for the Natural Sciences / Master of Science [FsB vom 17.12.2012 mit Änderungen vom 15.04.2013, 01.04.2014, 15.10.2014, 02.03.2015, 01.12.2015 und Berichtigungen vom 01.04.2014, 17.11.2014 und 12.07.2017] 1. o. 3. one semester Compul­sory optional subject

Automatic check for completeness

The system can perform an automatic check for completeness for this module.


Legend

1
The module structure displays the required number of study requirements and examinations.
2
LP is the short form for credit points.
3
The figures in this column are the specialist semesters in which it is recommended to start the module. Depending on the individual study schedule, entirely different courses of study are possible and advisable.
4
Explanations on mandatory option: "Obligation" means: This module is mandatory for the course of the studies; "Optional obligation" means: This module belongs to a number of modules available for selection under certain circumstances. This is more precisely regulated by the "Subject-related regulations" (see navigation).
5
Workload (contact time + self-study)
SoSe
Summer semester
WiSe
Winter semester
SL
Study requirement
Pr
Examination
bPr
Number of examinations with grades
uPr
Number of examinations without grades
This academic achievement can be reported and recognised.