Universität Wien

070343 UE Methodological course - Collecting Data for the Humanities (2025S)

5.00 ECTS (2.00 SWS), SPL 7 - Geschichte
Prüfungsimmanente Lehrveranstaltung
Moodle
Mi 02.04. 16:45-20:00 Seminarraum 2, Währinger Straße 29 1.UG

An/Abmeldung

Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").

Details

max. 25 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

Block course with double sessions on Wednessday between 16:45 and 20:00 until 07.05.2025

  • Mittwoch 05.03. 16:45 - 20:00 Seminarraum 2, Währinger Straße 29 1.UG
  • Mittwoch 19.03. 16:45 - 20:00 Seminarraum 2, Währinger Straße 29 1.UG
  • Mittwoch 26.03. 16:45 - 20:00 Seminarraum 2, Währinger Straße 29 1.UG
  • Mittwoch 09.04. 16:45 - 20:00 Seminarraum 2, Währinger Straße 29 1.UG
  • Mittwoch 30.04. 16:45 - 20:00 Seminarraum 2, Währinger Straße 29 1.UG
  • Mittwoch 07.05. 16:45 - 20:00 Seminarraum 2, Währinger Straße 29 1.UG

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

The aim of this course is to familiarise students with methods and principles of collecting, creating and formatting digital data for the use of digital humanities research. In this practice-based class, students will gain hands-on expierence with methods to collect data from the internet (webscraping), data annotation and OCR. Along the way we will discuss empirical and theoretical frameworks of data mining and data processing.

Students will acquire the necessary knowledge through hands-on work over the course of the semester, working in small teams to develop methods to collect data 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.

While no programming knowledge is required, it is advised for students to have prior knowledge of Python and a basic understanding of data structures.

Art der Leistungskontrolle und erlaubte Hilfsmittel

Active participation in class, small project-based exercises, project presentation and final project.

Mindestanforderungen und Beurteilungsmaßstab

Active participation in class (10%); homework assignments (50%); final project presentation (10%); final project written submission (30%).

Prüfungsstoff

- Theoretical frameworks of data mining and data processing
- (No)code approaches to OCR
- Automatically collect data from webpages
- Collecting data through web API’s
- Annotating data for Humanities research

Literatur

Available through Moodle

Zuordnung im Vorlesungsverzeichnis

SP: Digital Humanities

MA Geschichte (2019): PM1 - Methodenkurs (5 ECTS)
MA Digital Humanities: DH-S II

Letzte Änderung: Mi 12.02.2025 14:46