Universität Wien

070085 UE Course on Methodology - Data Structures and Data Management in the Humanities (2024W)

5.00 ECTS (2.00 SWS), SPL 7 - Geschichte
Continuous assessment of course work
Moodle

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

  • Wednesday 02.10. 10:45 - 12:15 Seminarraum Geschichte 2 Hauptgebäude, 2.Stock, Stiege 9
  • Wednesday 09.10. 10:45 - 12:15 Seminarraum Geschichte 2 Hauptgebäude, 2.Stock, Stiege 9
  • Wednesday 16.10. 10:45 - 12:15 Seminarraum Geschichte 2 Hauptgebäude, 2.Stock, Stiege 9
  • Wednesday 23.10. 10:45 - 12:15 Seminarraum Geschichte 2 Hauptgebäude, 2.Stock, Stiege 9
  • Wednesday 30.10. 10:45 - 12:15 Seminarraum Geschichte 2 Hauptgebäude, 2.Stock, Stiege 9
  • Wednesday 06.11. 10:45 - 12:15 Seminarraum Geschichte 2 Hauptgebäude, 2.Stock, Stiege 9
  • Wednesday 13.11. 10:45 - 12:15 Seminarraum Geschichte 2 Hauptgebäude, 2.Stock, Stiege 9
  • Wednesday 20.11. 10:45 - 12:15 Seminarraum Geschichte 2 Hauptgebäude, 2.Stock, Stiege 9
  • Wednesday 27.11. 10:45 - 12:15 Seminarraum Geschichte 2 Hauptgebäude, 2.Stock, Stiege 9
  • Wednesday 04.12. 10:45 - 12:15 Seminarraum Geschichte 2 Hauptgebäude, 2.Stock, Stiege 9
  • Wednesday 11.12. 10:45 - 12:15 Seminarraum Geschichte 2 Hauptgebäude, 2.Stock, Stiege 9
  • Wednesday 08.01. 10:45 - 12:15 Seminarraum Geschichte 2 Hauptgebäude, 2.Stock, Stiege 9
  • Wednesday 15.01. 10:45 - 12:15 Seminarraum Geschichte 2 Hauptgebäude, 2.Stock, Stiege 9
  • Wednesday 22.01. 10:45 - 12:15 Seminarraum Geschichte 2 Hauptgebäude, 2.Stock, Stiege 9
  • Wednesday 29.01. 10:45 - 12:15 Seminarraum Geschichte 2 Hauptgebäude, 2.Stock, Stiege 9

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

SP Digital Humanities/ Digitale Geschichtswissenschaft

MA Geschichte (V2019): PM1 - Methodenkurs (5 ECTS)

Last modified: We 31.07.2024 15:45