RLMgB605 Digital data in the Study of Religions: from catalogue to table and graph

Faculty of Arts
Spring 2025
Extent and Intensity
1/1/0. 5 credit(s). Type of Completion: k (colloquium).
Teacher(s)
Mgr. Tomáš Hampejs, Ph.D. (lecturer)
Mgr. et Mgr. Tereza Menšíková (lecturer)
Mgr. Tomáš Glomb, Ph.D. (lecturer)
Guaranteed by
Mgr. Tomáš Glomb, Ph.D.
Department for the Study of Religions – Faculty of Arts
Contact Person: Mgr. Kristýna Čižmářová
Supplier department: Department for the Study of Religions – Faculty of Arts
Timetable
each odd Thursday 16:00–17:40 B2.21, except Mon 21. 4. to Sun 27. 4.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 30 student(s).
Current registration and enrolment status: enrolled: 4/30, only registered: 0/30, only registered with preference (fields directly associated with the programme): 0/30
fields of study / plans the course is directly associated with
Course objectives
Understanding the world through "data" is fundamentally dependent on the ability to work with standardized observation and its purposeful representation - the dataset, as well as digital tools for its creation, management and analysis. Using a selected case study, the course will go through the basic stages of creating a humanities dataset for research purposes. It will practically show that at the core of most datasets is one or more tables and the basic tool of a data researcher is a spreadsheet. The class will combine seminar discussions with topical excursions on selected challenges of working with data on culture and religion, and will develop imagination around choosing the right proxies where we do not have direct data but can infer from combinations of other data. Students will work collectively and incrementally in the course towards a common output in the direction of converting analogue data or semi-structured digital data from a catalogue source to structured data in a table and its subsequent basic statistical evaluation along with a visualisation of the chosen problem.
Learning outcomes
After the course completion, students will be able to:
  • understand the foundations of culture and the technologies of "data" in digital humanities context;
  • understand the principles of tables processors;
  • distinguish between data and metadata, distinguish between structured, semi-structured and structured data;
  • understand the basic phases of data life, to understand the data life cycle;
  • collect and capture data on religion and culture, create and operationalize datasets towards a research problem.
    • Syllabus
    • The data processing lifecycle and introduction to the dataset I
    • The data processing lifecycle and introduction to the dataset II
    • Data collection and operationalization I
    • Data collection and operationalization II
    • Basics of working with a spreadsheet processor I
    • Basics of working with a spreadsheet processor II
    • Basics of data analysis I
    • Basics of data analysis II
    • Visualization and chart creation I
    • Visualization and chart creation II
    Literature
    • Cantwell, C. D., & Petersen, K. (Eds.). (2021). Digital Humanities and Research Methods in Religious Studies: An Introduction. De Gruyter. https://doi.org/10.1515/9783110573022
    • Drucker, J. (2011). Humanities Approaches to Graphical Display. Digital Humanities Quarterly, 005(1).
    • Drucker, J. (2021). The Digital Humanities Coursebook: An Introduction to Digital Methods for Research and Scholarship (1st ed.). First edition. | Abingdon, Oxon ; New York : Routledge/Taylor & Francis, 2021.: Routledge. https://doi.org/10.4324/978100310
    Teaching methods
    Seminars. Students will work collectively and sequentially on a group output over the course of the semester. The colloquium will then focus on individual discussion of the evaluation and interpretation of the output. The basic steps in the course of the semester will be: 1) Working on assignments; 2) Manual collection of data from the source into a table based on critical interpretation of the source/catalog and appropriate categorization according to the selected attributes; 3) Basic descriptive statistics - contingency table; 4) Basic graph visualization.
    Assessment methods
    Joint group output. Individual colloquium on the final dataset, discussion on addressing the research question for the dataset, and reflection on the dataset completion.
    Language of instruction
    Czech
    Further comments (probably available only in Czech)
    Study Materials
    The course is taught once in two years.
    Information on course enrolment limitations: Zápis mimo religionistiku je podmíněn souhlasem vyučujících.
    Teacher's information
    The course is administered in the e-learning environment ELF.
    The course is also listed under the following terms Autumn 2025.
    • Enrolment Statistics (recent)
    • Permalink: https://is.muni.cz/course/phil/spring2025/RLMgB605