Universität Wien

136011 UE Data Structures and Data Modelling (2025S)

5.00 ECTS (2.00 SWS), SPL 13 - Europäische und Vergleichende Sprach- und Literaturwissenschaft
Continuous assessment of course work
Moodle
Fr 02.05. 11:30-13:00 Hörsaal 2 Hauptgebäude, Tiefparterre Stiege 5 Hof 3

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 25 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Friday 07.03. 11:30 - 13:00 Hörsaal 2 Hauptgebäude, Tiefparterre Stiege 5 Hof 3
  • Friday 14.03. 11:30 - 13:00 Hörsaal 2 Hauptgebäude, Tiefparterre Stiege 5 Hof 3
  • Friday 21.03. 11:30 - 13:00 Hörsaal 2 Hauptgebäude, Tiefparterre Stiege 5 Hof 3
  • Friday 28.03. 11:30 - 13:00 Hörsaal 2 Hauptgebäude, Tiefparterre Stiege 5 Hof 3
  • Friday 04.04. 11:30 - 13:00 Hörsaal 2 Hauptgebäude, Tiefparterre Stiege 5 Hof 3
  • Friday 11.04. 11:30 - 13:00 Hörsaal 2 Hauptgebäude, Tiefparterre Stiege 5 Hof 3
  • Friday 09.05. 11:30 - 13:00 Hörsaal 2 Hauptgebäude, Tiefparterre Stiege 5 Hof 3
  • Friday 16.05. 11:30 - 13:00 Hörsaal 2 Hauptgebäude, Tiefparterre Stiege 5 Hof 3
  • Friday 23.05. 11:30 - 13:00 Hörsaal 2 Hauptgebäude, Tiefparterre Stiege 5 Hof 3
  • Friday 30.05. 11:30 - 13:00 Hörsaal 2 Hauptgebäude, Tiefparterre Stiege 5 Hof 3
  • Friday 06.06. 11:30 - 13:00 Hörsaal 2 Hauptgebäude, Tiefparterre Stiege 5 Hof 3
  • Friday 13.06. 11:30 - 13:00 Hörsaal 2 Hauptgebäude, Tiefparterre Stiege 5 Hof 3
  • Friday 20.06. 11:30 - 13:00 Hörsaal 2 Hauptgebäude, Tiefparterre Stiege 5 Hof 3
  • Friday 27.06. 11:30 - 13:00 Hörsaal 2 Hauptgebäude, Tiefparterre Stiege 5 Hof 3

Information

Aims, contents and method of the course

The aim of this course is to familiarise students with the basic structure of digital data and, in particular, to teach them about semantic data modeling based on analysis of requirements. This is a practice-based class; students will generate appropriate data models based on real data sets from the humanities and implement them technically. No programming knowledge is necessary in advance, although there will be synergies with "Introduction to DH: Tools and Methods". Students will acquire the necessary knowledge through hands-on work over the course of the semester (as is usual in DH), working in small teams to develop data, structures and models for a project of their own choice. They will present requirements, planned solutions, and finally an implementation of their data for a final project, which will also be documented in writing. Along the way we will discuss empirical and theoretical frameworks of data mining and data processing.

Assessment and permitted materials

Active participation in class, small project-based exercises, project presentation and final project (including written abstract, data management plan, database model).

Minimum requirements and assessment criteria

Active participation in class (20%); homework assignments (40%); final project presentation (10%); final project written submission (30%).

Examination topics

- CSV, XML and JSON data structures
- Relational databases, schemas and modelling (SQL)
- NoSQL / graph-based data modelling

Reading list

Available through Moodle

Association in the course directory

DH-S I

Last modified: Fr 07.02.2025 10:46