Modality and Uncertainty in Data Visualizations: A Corpus Approach to the Use of Connecting Lines

Abstract

In data visualizations, connecting lines may have various semiotic functions, including the semiotic potential of indicating modality and uncertainty. The goal of this article is to find out how this semiotic potential is realized in current best practices of data visualizations and what conventions exist for the visual manifestations of these functions. This issue is addressed by using a corpus-based approach and a two-level analysis method within a social semiotic framework. First, the article offers a theoretical discussion on how the concepts of modality and uncertainty interrelate. Second, a method for investigating how these concepts are visualized at different levels is presented. Third, a corpus analysis including 163 award-winning data visualizations is presented. The results indicate the existence of certain conventions for visual modality markers, and thus offer new insights relevant for both design theory and practice.