Authors:
Xiao Tan
;
Ünsal Satan
;
Jonas Zellweger
;
Gaudenz Halter
;
Barbara Flückiger
;
Renato Pajarola
and
Alexandra Diehl
Affiliation:
Department of Informatics, University of Zurich, Binzmühlestrasse 14, Zürich, Switzerland
Keyword(s):
Exploratory Data Analysis, High-Dimensional Data Visualization, Digital Humanities.
Abstract:
Digital archives, especially audiovisual archives, often contain a large number of features of interest to digital humanities scholars, including video, audio, metadata, and annotation data. These large and complex datasets pose numerous challenges, such as how to get an overview of the overall data structure, how to identify associations between relevant data features, and how to formulate hypotheses based on observations or elicit new conceptualizations. To address these challenges, we propose a visualization tool SnakeTrees that allows digital humanities scholars to explore audiovisual archives in a novel interactive way based on computational grouping and similarity analysis provided by dimensionality reduction methods and clustering techniques. The main goal of visualizing and exploring these abstract representations is to encourage the finding of new concepts, discover new unexpected connections between different audiovisual elements, and engage users in exploratory analysis. O
ur approach uses interactive visualization and computational hierarchical structures to provide pre-configured groupings and categorizations that users can use as a basis for exploration and analysis.
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