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Root number
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515971 |
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Semester
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FS2026 |
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Type of course
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Seminar |
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Allocation to subject
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Digital Humanities |
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Type of exam
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Oral exam |
| Title |
From data to knowledge: introduction to data analysis using Linked Open Data (LOD) |
| Description |
This seminar will introduce students to some of the key data analysis methodologies used in the humanities and social sciences (HSS), including descriptive statistics, multivariate analysis, network analysis, and the spatial projection of features. They will also learn about some classical machine learning approaches such as community detection and logistic regression. Using information from the Semantic Web in the form of Linked Open Data (LOD), particularly from DBpedia and Wikidata, as well as from German and French libraries and other topic-related resources, students will define research questions they wish to address regarding their chosen topic. They will then learn how to retrieve, clean and prepare data in order to apply analysis tools. They will gain new insights from the collected LOD information and discover how to answer research questions in the HSS domain and generate new knowledge from existing data.
Each student's individual seminar work will be documented in a GitHub repository comprising a project description, Jupyter notebooks detailing the analysis process, and web pages presenting the research process and results, including figures and comments. The aim is to present the insights discovered as a narrative and provide full documentation of the underlying process.
Participants will need to bring their own laptops to the seminar. While previous Python skills are not required, they are welcome and can be helpful. |
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ILIAS-Link (Learning resource for course)
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Registrations are transmitted from CTS to ILIAS (no admission in ILIAS possible).
ILIAS
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Link to another web site
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| Lecturers |
PD Dr.
Francesco Emilio Pietro Beretta, Digital Humanities @ University of Bern ✉
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ECTS
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6 |
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Recognition as optional course possible
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Yes |
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Grading
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1 to 6 |
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| Dates |
Wednesday 10:15-12:00 Weekly
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| Rooms |
Seminarraum 215, Hauptgebäude H4
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| Students please consult the detailed view for complete information on dates, rooms and planned podcasts. |
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