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Lecturer(s)
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Záhořík Martin, Mgr. Ph.D.
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Course content
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Digital transformation in the humanities and social sciences; digital humanities; digitization of cultural heritage; open science; FAIR principles; replication crisis and responses to it; programming languages and reproducibility of data analysis; formal network analysis; geographic information systems; natural language processing; distant reading; agent simulations.
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Learning activities and teaching methods
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Lecture
- Preparation for an examination (30-60)
- 234 hours per semester
- Contact hours
- 26 hours per semester
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| prerequisite |
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| Knowledge |
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| to describe the crucial methods of humanities |
| to introduce basic types of computer applications |
| to describe common functions of the most common computer applications |
| Skills |
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| to use the apparatus of philosophy of humanities |
| to use a personal computer to search for and study relevant information on the Internet |
| to use a personal computer, tablet or smartphone to read academic texts |
| to use modern technology, especially digital libraries |
| Competences |
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| N/A |
| N/A |
| dr. studium: prezentují výstupy vlastního výzkumu |
| learning outcomes |
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| Knowledge |
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| to present the basic effects of the digital revolution on the humanities and social sciences |
| to characterize types of research in the digital humanities |
| to prove understanding of the current state of international research in the field |
| to introduce common methods used in digital humanities |
| to characterize epistemological issues related to the use of computational methods in the humanities/social sciences |
| to explain the basic concepts of open science and the principles of transparent and reproducible practices when working with scientific data |
| Skills |
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| to use selected computer tools in the field of digital humanities in their own research |
| to design a database structure suitable for selected humanities data |
| to analyze data using a selected computer tool in the field of digital humanities |
| Competences |
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| N/A |
| N/A |
| teaching methods |
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| Knowledge |
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| One-to-One tutorial |
| Self-study of literature |
| Textual studies |
| Skills |
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| One-to-One tutorial |
| Individual study |
| Competences |
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| One-to-One tutorial |
| Textual studies |
| Self-study of literature |
| assessment methods |
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| Knowledge |
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| Oral exam |
| Skills |
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| Oral exam |
| Competences |
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| Oral exam |
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Recommended literature
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BORGMAN, Christine. Big Data, Little Data, No Data: Scholarship in the Networked World. Cambridge - London: The MIT Press, 2015. ISBN 978-0-262-52991-4.
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Burdick, Anne; Schnapp, Jeffrey; Drucker, Johanna,; Lunenfeld, Peter,; Presner, Todd. Digital humanities. 2012. ISBN 978-0-262-52886-3.
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BUYALSKAYA, Anastasia; Marcos GALLO a Colin F. CAMERER. The golden age of social science. Proceedings of the National Academy of Sciences. 2021, ISSN 0027-8424.
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DESAI, Jules; David WATSON; Vincent WANG; Mariarosaria TADDEO a Luciano FLORIDI. The epistemological foundations of data science: a critical review. Synthese. 2022, ISSN 1573-0964.
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Hladík, Radim. Digitální obrat v českých humanitních a sociálních vědách. Vydání první. 2022. ISBN 978-80-246-5193-4.
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JOST, Jürgen; Roberto LALLI; Manfred D. LAUBICHLER; Eckehard OLBRICH; Jürgen RENN; Guillermo RESTREPO; Peter F. STADLER a Dirk WINTERGRÜN. Computational History: Challenges and Opportunities of Formal Approaches. Journal of Social Computing. 2023, ISSN 2688-5255.
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KITCHIN, Rob. The data revolution: a critical analysis of big data, open data & data infrastructures. Los Angeles, CA: Sage Publications, 2022. ISBN 978-1-5297-3375-4.
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