Formalizing Emphasis in Information Visualization

Abstract

This is the accepted version of the paper.This version of the publication may differ from the final published version. Permanent AbstractWe provide a fresh look at the use and prevalence of emphasis effects in Infovis. Through a survey of existing emphasis frameworks, we extract a set-based approach that uses visual prominence to link visually and algorithmically diverse emphasis effects. Visual prominence provides a basis for describing, comparing and generating emphasis effects when combined with a set of general features of emphasis effects. Therefore, we use visual prominence and these general features to construct a new mathematical Framework for Information Visualization Emphasis, FIVE. The concepts we introduce to describe FIVE unite the emphasis literature and point to several new research directions for emphasis in information visualization.

Cartographic Redundancy in Reducing Change Blindness in Detecting Extreme Values in Spatio-Temporal Maps

“…Conducted studies confirm that the use of color and size to highlight information in visualizations is justified [56,57]. The method proposed by the authors might be understood as redundancy, but also as magnification, due to the use of the most popular visual variables [58]. For the proportional symbol map, where we used an abrupt transition, seven classes were defined, in accordance with the commonly known cartographic principle stating that the number of classes should not exceed seven, give or take two [47].…”

“…The proposed method of redundant encoding meets the requirements of the FIVE framework, which concerns the issue of emphasizing spatio-temporal data [58]. According to this framework, cartographic redundancy is a prominent method of visualization and could be considered one of the most effective ones.…”

Survey of Surveys (SoS) ‐ Mapping The Landscape of Survey Papers in Information Visualization

“…Hall et al present a mathematical Framework for Information Visualization Emphasis (FIVE) by reviewing existing emphasis literature and frameworks [HPK*16]. Some examples of emphasis provided include highlighting regions of interest, animating data points, and altering the size of data points.…”

Visualization of Features in 3D Terrain

“…When applying these concepts, visually emphasizing interesting parts of the data is particularly important. Regarding data values, a comprehensive overview of emphasis techniques is given by Hall et al [37].…”

“…Hence, emphasizing such characteristics means highlighting the location of respective data points. To expose subsets of the data, various techniques exist, such as coloring, blurring or resizing [37,46]. Figure 8 shows examples for extrinsic and intrinsic visualization, respectively.…”