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Data Art: Methods of Data Visualization in Projects of 2010-2019

Student: Lipchanskaia Anastasiia

Supervisor: Ekaterina Lapina-Kratasyuk

Faculty: Faculty of Creative Industries

Educational Programme: Data Journalism (Master)

Year of Graduation: 2019

The research is devoted to the notion of data art and approaches to data visualization on the example of several projects, that appeared during last decade. The aim of the research at the same time was to define boundaries of the data art concept. Among the problems in this work there are analysis of the data art history and its key features, suggestion on theoretical basis for classification of data art projects. In order to reach the goals of the research there were used methods of identification of key concepts (based on theoretical literature), analysis of documents, analysis of media texts, historical analysis. Also there were used Software Studies and Cultural Analytics approaches. The hypothesis of the study was that visualization in data art is designed to aesthetically affect the viewer, using data only as a material for the artist's self-expression.

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