Universität Wien

136038 UE Data Driven Research Methodology for the Digital Humanities (2023S)

5.00 ECTS (2.00 SWS), SPL 13 - Europäische und Vergleichende Sprach- und Literaturwissenschaft
Continuous assessment of course work
REMOTE
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

The first class on Friday 03.03. will take place on site. All following classes will take place online.

  • Friday 03.03. 09:45 - 11:15 Seminarraum 6 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
  • Friday 10.03. 09:45 - 11:15 Seminarraum 6 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
  • Friday 17.03. 09:45 - 11:15 Seminarraum 6 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
  • Friday 24.03. 09:45 - 11:15 Seminarraum 6 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
  • Friday 31.03. 09:45 - 11:15 Seminarraum 6 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
  • Friday 21.04. 09:45 - 11:15 Seminarraum 6 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
  • Friday 28.04. 09:45 - 11:15 Seminarraum 6 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
  • Friday 05.05. 09:45 - 11:15 Seminarraum 6 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
  • Friday 12.05. 09:45 - 11:15 Seminarraum 6 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
  • Friday 19.05. 09:45 - 11:15 Seminarraum 6 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
  • Friday 26.05. 09:45 - 11:15 Seminarraum 6 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
  • Friday 02.06. 09:45 - 11:15 Seminarraum 6 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
  • Friday 16.06. 09:45 - 11:15 Seminarraum 6 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
  • Friday 23.06. 09:45 - 11:15 Seminarraum 6 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
  • Friday 30.06. 09:45 - 11:15 Seminarraum 6 Hauptgebäude, Tiefparterre Stiege 9 Hof 5

Information

Aims, contents and method of the course

The course is aimed at introducing students to data-driven methods, frameworks, projects and examples with a particular focus on Digital Humanities projects and data sets. Generally speaking, a data-driven approach is when decisions and research questions are based on the inspection, analysis and interpretation of a particular set of data rather than on anecdotal judgements and observations. One of the larger aims of data-driven projects is the process of collecting and analysing data in order to derive insights and propose solutions for a defined challenge or general problem. In the field of Digital Humanities, data-driven research is particularly interesting as it allows not only to apply a variety of data processing tools, but also to gain insights into aspects of complex data, often hidden or unexplored. In this course a theoretical introduction will be followed by ideation and hands-on sessions where students will work in groups on conceptualising and prototyping their own data-driven project based on selected sets of open-data. Basics of the Python Programming Language will be introduced together with Jupyter Notebooks as a working environment. The course approach is both theoretical and practical, with hands-on exercises in project planning and prototyping. Students are expected to have some familiarity with digital environments, and previous practice with programming is desired, but not strictly mandatory. The course will be held in both English and German.

Assessment and permitted materials

The course evaluation will be a combination of continuous assessment including in-class participation, homework and presentations. At the end of the course students are expected to present their capstone project.
Further information will be given in the first lecture.

Minimum requirements and assessment criteria

Regular attendance is required as well as regular participation in presentations and hands-on sessions. Students must submit their homework assignments on time (some can be completed later as a part of the final project, but this must be discussed with the instructors whenever the issue arises); the final project must be submitted on time.

Examination topics

There is no examination for the course.

Reading list

All the references to papers, presentations, articles and data sources will be distributed through Moodle.

Association in the course directory

DH-S II

Last modified: Th 04.07.2024 00:13