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2022 | OriginalPaper | Buchkapitel

A Research-Teaching Guide for Visual Data Analysis in Digital Humanities

verfasst von : Stefan Jänicke

Erschienen in: Computer Vision, Imaging and Computer Graphics Theory and Applications

Verlag: Springer International Publishing

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Abstract

The use of visualization to underpin distant reading arguments on cultural heritage data has established in the digital humanities domain. Novel strategies to represent data visually typically arise from interdisciplinary projects involving humanities and visualization scholars. However, the quality of outcomes might be inhibited as typical challenges of interdisciplinary research arise, and, at the same time, problem solving strategies are missing. I taught a course on visual data analysis in the digital humanities to let students with diverse study backgrounds experience those challenges in their early academic careers. This paper illustrates the research-teaching components of my course. This includes the contents of the theoretical training with active learning tasks, aspects of the practical training and considerations for teachers aiming to compose a related course.

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Titel: A Research-Teaching Guide for Visual Data Analysis in Digital Humanities
verfasst von: Stefan Jänicke
Verlag: Springer International Publishing
Buch: Computer Vision, Imaging and Computer Graphics Theory and Applications
Print ISBN: 978-3-030-94892-4

Electronic ISBN: 978-3-030-94893-1

Copyright-Jahr: 2022
DOI: https://doi.org/10.1007/978-3-030-94893-1_9

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