CircleVis: A Visualization Tool for Circular Labeling Arrangements and Overlap Removal

Abstract

Information visualization refers to the practice of representing data in a meaningful, visual way that users can interpret and easily comprehend. Geometric or visual encoding shapes such as circles, rectangles, and bars have grown in popularity in data visualization research over time. Circles are a common shape used by domain experts to solve real-world problems and analyze data. As a result, data can be encoded using a simple circle with a set of labels associated with an arc or portion of the circle. Labels can then be arranged in various ways based on human perception (easy to read) or by optimizing the available space around the circle. However, overlaps can occur in one or more arrangements. This paper proposes CircleVis, a new visualization tool for label arrangement and overlap removal in circle visual encoding. First, a mathematical model is presented in order to formulate existing arrangements such as angular, path, and linear. Furthermore, based on user interaction, a new arrangement approach is proposed to optimize available space in each circle arc and delete label overlaps. Finally, users test and evaluate the designed tool using the COVID-19 dataset for validation purposes. The obtained results demonstrate the efficacy of the proposed method for label arrangement and overlapping removal in circular layout.