데이터시각화의 공감표현 연구

A Study on Empathy Expression of Data Visualization

This study focuses on the fact that there is no emotional connection with users in the current data visualization that is plentifully produced oriented number of charts and graphs. Accordingly, in order to examine what data visualization for humans is, research has begun to explore factors that can elicit empathy from data visualization. For analysis, the main images of data visualization cases expressing human death were classified based on Charles Sanders Peirce’s semiotics, and data visualization cases expressing ‘death’ were re-analyzed using the analysis criteria of previous studies that studied steps of anthropomorphizing. This study presents the following strategies that can elicit empathy in data visualization. First, data humanism must be expressed based on the narrative (context) of the data of a minority target. Second, when visualizing data, ideas can be spread beyond the standard chart representation by sketching it as ‘iconic, indexic, symbolic sign’, with a dataset. Third, when the data subject is a person, small number of data should be concerned, not thousands or hundreds of people, considering the high granularity and information specificity as much as possible. Since the realism of the image does not affect empathy much, more focus should be placed on authenticity. Fourth, when producing interactive data visualization, multiple senses are stimulated by utilizing the characteristics of the medium. Finally, as there is no fixed answer despite these strategies, users (readers) should be given the right to browse data through linear or nonlinear data visualization. It is expected that the results of this study will be used as basic data in the field of data visualization production and education based on humanism.