CORE147 Digital data in Social Sciences and Humanities

Faculty of Informatics
Autumn 2024
Extent and Intensity
2/0/0. 2 credit(s) (plus 1 for the colloquium). Type of Completion: k (colloquium).
In-person direct teaching
Teacher(s)
RNDr. Zuzana Nevěřilová, Ph.D. (lecturer)
Mgr. Hana Žižková, Ph.D. (lecturer)
Guaranteed by
RNDr. Zuzana Nevěřilová, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. RNDr. Vojtěch Řehák, Ph.D.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Thu 26. 9. to Thu 19. 12. Thu 10:00–11:50 A217
Prerequisites (in Czech)
TYP_STUDIA(BM) && ! FAKULTA(FI)
Course Enrolment Limitations
The course is offered to students of any study field.
The capacity limit for the course is 100 student(s).
Current registration and enrolment status: enrolled: 7/100, only registered: 1/100, only registered with preference (fields directly associated with the programme): 0/100
Course objectives
The aim of the course is to introduce students to the world of social sciences and humanities (SSH) through the eyes of a data scientist. The data science approaches we will show in the course can be applied to economics, pedagogy, or law in addition to SSH. The practical goal is to introduce all components of data science applied to SSH: data collection and organization, data annotation, existing data sources, data preprocessing methods, software tools for data inspection, analysis and visualization, and evaluation methods. We will also introduce research infrastructures and digital archives that contribute significantly to the democratization of SSH. The course will review the important topics of SSH from a digital data perspective, show the data processing methods used, introduce software tools, and allow learners to try out the tasks independently.
Learning outcomes
Upon completion of the course, the student will be able to:
- understand the issues that SSH addresses: digitization, optical character recognition (OCR, ICR), preservation of cultural heritage; data and metadata, standardization, openness, sharing;
- understand the methods used by SSH: quantitative data description, visualization, data processing software tools, remote storage and remote services, application programming interfaces (APIs) and their use;
- understand the issues of data and metadata collection, processing, organization;
- to work fundamentally with textual data (corpora, word embeddings, language models);
- to work fundamentally with image data (object recognition, 3D imaging) and multimodal data (social link processing);
- list some examples of digital archives and research infrastructures;
- be able to process data from some SSH domain using freely available software tools
Syllabus
  • stories of humanities and social sciences
  • digitization - the journey from paper to computer
  • tell a computer to tell another computer to do...
  • humanities scholars and texts
  • data chores
  • computers also see (but what? and how?)
  • Germany and Hitler are like Russia and ...?
  • there is a story everywhere
  • show me your infographic
  • data pipelines
  • (digital) humanities and project management
  • infrastructures for humanities and social sciences
Literature
    recommended literature
  • Julian Chambliss and Ellen Moll: Making Sense of Digital Humanities. Michigan State University. 2022. https://openbooks.lib.msu.edu/makingsensedh/
Teaching methods
lecture with practical demonstrations, source codes and tutorials for home testing in the course materials
Assessment methods
Students choose one of the pre-prepared projects, develop it, and publish it. Next, they provide feedback to two other students who have selected the same project. The evaluation will be composed of three outcomes (quality of own elaboration, quality of feedback to another students' work).
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.

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