Data Driven Research Methodology for the Digital Humanities

136038 UE 2023S

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Vortragende der Germanistik:

The first class on Friday 03.03. will take place on site. All following classes will take place online.


Ziele, Inhalte und Methode der Lehrveranstaltung

The course is aimed at introducing students to data-driven methods, frameworks, projects and examples with a particular focus on Digital Humanities projects and data sets. Generally speaking, a data-driven approach is when decisions and research questions are based on the inspection, analysis and interpretation of a particular set of data rather than on anecdotal judgements and observations. One of the larger aims of data-driven projects is the process of collecting and analysing data in order to derive insights and propose solutions for a defined challenge or general problem. In the field of Digital Humanities, data-driven research is particularly interesting as it allows not only to apply a variety of data processing tools, but also to gain insights into aspects of complex data, often hidden or unexplored. In this course a theoretical introduction will be followed by ideation and hands-on sessions where students will work on conceptualising and prototyping their own data-driven project based on selected sets of open-data. Basics of the Python Programming Language will be introduced together with Jupyter Notebooks as a working environment. The course approach is both theoretical and practical, with hands-on exercises in project planning and prototyping. Students are expected to have some familiarity with digital environments, and previous practice with programming is desired, but not strictly mandatory. The course will be held in both English and German.


Art der Leistungskontrolle und erlaubte Hilfsmittel

The course evaluation will be a combination of continuous assessment including in-class participation, homework and presentations. At the end of the course students are expected to present their capstone project.
Further information will be given in the first lecture.



All the references to papers, presentations, articles and data sources will be distributed through Moodle.



There is no examination for the course.


Mindestanforderungen und Beurteilungsmaßstab

Regular attendance is required as well as regular participation in group presentations and hands-on sessions. Students must submit their homework assignments on time (some can be completed later as a part of the final project, but this must be discussed with the instructors whenever the issue arises); the final project must be submitted on time.