Universität Wien

136033 SE Research Seminar Digital Humanities - Linked Data and Big Data in Digital Cultural Heritage (2023W)

4.00 ECTS (3.00 SWS), SPL 13 - Europäische und Vergleichende Sprach- und Literaturwissenschaft
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

  • Monday 02.10. 09:45 - 12:15 Hörsaal 2 Hauptgebäude, Tiefparterre Stiege 5 Hof 3
  • Monday 09.10. 09:45 - 12:15 Hörsaal 2 Hauptgebäude, Tiefparterre Stiege 5 Hof 3
  • Monday 16.10. 09:45 - 12:15 Hörsaal 2 Hauptgebäude, Tiefparterre Stiege 5 Hof 3
  • Monday 23.10. 09:45 - 12:15 Hörsaal 2 Hauptgebäude, Tiefparterre Stiege 5 Hof 3
  • Monday 30.10. 09:45 - 12:15 Hörsaal 2 Hauptgebäude, Tiefparterre Stiege 5 Hof 3
  • Monday 06.11. 09:45 - 12:15 Hörsaal 2 Hauptgebäude, Tiefparterre Stiege 5 Hof 3
  • Monday 13.11. 09:45 - 12:15 Hörsaal 2 Hauptgebäude, Tiefparterre Stiege 5 Hof 3
  • Monday 20.11. 09:45 - 12:15 Hörsaal 2 Hauptgebäude, Tiefparterre Stiege 5 Hof 3
  • Monday 27.11. 09:45 - 12:15 Hörsaal 2 Hauptgebäude, Tiefparterre Stiege 5 Hof 3
  • Monday 04.12. 09:45 - 12:15 Hörsaal 2 Hauptgebäude, Tiefparterre Stiege 5 Hof 3
  • Monday 11.12. 09:45 - 12:15 Hörsaal 2 Hauptgebäude, Tiefparterre Stiege 5 Hof 3
  • Monday 08.01. 09:45 - 12:15 Hörsaal 2 Hauptgebäude, Tiefparterre Stiege 5 Hof 3
  • Monday 15.01. 09:45 - 12:15 Hörsaal 2 Hauptgebäude, Tiefparterre Stiege 5 Hof 3
  • Monday 22.01. 09:45 - 12:15 Hörsaal 2 Hauptgebäude, Tiefparterre Stiege 5 Hof 3
  • Monday 29.01. 09:45 - 12:15 Hörsaal 2 Hauptgebäude, Tiefparterre Stiege 5 Hof 3

Information

Aims, contents and method of the course

The digitisation of cultural heritage and historical data has created previously unimagined possibilities for humanities researchers. We now have instant, online access to databases harvested from museum collections, archives and libraries, and researchers can access and use data and materials stored in any location, at any time, from anywhere in the world. At the heart of this innovation are the principles of big data and linked open data - both inherited from the natural and social sciences - which are being reimagined for use in cultural heritage contexts by historians, classicists, museologists, art historians, literary scholars and librarians.

But heritage data is, by its nature, complex, and requires thoughtful interrogation by those who produce it, and those who make use of it. It is not neutral, and often bears traces of the historical context in which objects were collected and data was created.

In this seminar, we will approach these complexities and consider them in the light of current debates taking place in the broader Digital Humanities. Topics we will cover include:

Artificial Intelligence & Algorithmic Justice
• Heritage Data in AI models
Museum & Archival Data and Their Uses
• Using Wikidata to trace looted art
• Digital and non-digital restitution of colonial era materials
• Archival re-evaluation
• Digital objects and their biographies
Ethical Use of Heritage Data
• Digitising and accessing sensitive historical materials
• Ethical use of linked data repositories
• Difficult materials and digital media
• Ethical use of linked data repositories
Privacy, Copyright and Ownership of Data
• User-generated content in heritage contexts

Practical sessions, teaching basic digital research skills using heritage data, such as data mining, cleaning, geo-referencing and visualisation may also be included in the syllabus if there is sufficient interest.

Assessment and permitted materials

Assessment will consist of project work, written assignments and in-class participation. Students should be sure to plan enough time for this.
However, the effective workload is difficult to estimate and employee and family-friendly solutions can be found in consultation with the course instructors.

Minimum requirements and assessment criteria

No prior knowledge of working with data is assumed. However, students will need to have access to a computer for the practical component of the course.

Examination topics

Examination material is the final research project.

Reading list

Association in the course directory

DH/DS/BI / DHP-S

Last modified: We 03.07.2024 15:05