Kineticharts: Augmenting Affective Expressiveness of Charts in Data Stories with Animation Design

Abstract

In recent years, more and more researchers have reflected on the undervaluation of emotion in data visualization and highlighted the importance of considering human emotion in visualization design. Meanwhile, an increasing number of studies have been conducted to explore emotion-related factors. However, so far, this research area is still in its early stages and faces a set of challenges, such as the unclear definition of key concepts, the insufficient justification of why emotion is important in visualization design, and the lack of characterization of the design space of affective visualization design. To address these challenges, first, we conducted a literature review and identified three research lines that examined both emotion and data visualization. We clarified the differences between these research lines and kept 109 papers that studied or discussed how data visualization communicates and influences emotion. Then, we coded the 109 papers in terms of how they justified the legitimacy of considering emotion in visualization design (i.e., why emotion is important) and identified five argumentative perspectives. Based on these papers, we also identified 61 projects that practiced affective visualization design. We coded these design projects in three dimensions, including design fields (where), design tasks (what), and design methods (how), to explore the design space of affective visualization design.

How Does Automation Shape the Process of Narrative Visualization: A Survey on Tools

“…Therefore, user preferences (e.g., data of interest to the user) and other characteristics of the user (e.g., knowledge level, visual literacy, and personal preferences) need to be considered [3]. Moreover, different visualizations and presentations can convey different emotions and eventually lead to different interpretations of the content [41], [117]. Therefore, it is necessary to understand the user acceptance of different types of narrative visualizations and the specific reasons for the different acceptance.…”

“…DataClips [116] provides a set of data clip libraries that allow laymen to put together data-driven clips to form longer sequences of data videos. Lan et al [117] developed Kineticharts, a chart animation scheme for conveying emotions, based on the animations provided in DataClips [116]. Compared to DataClips, Kineticharts can enhance the emotional engagement of users by improving the presentation of the story without hindering users' understanding of the data.…”

Erato: Cooperative Data Story Editing via Fact Interpolation

“…Due to its importance, many theoretical design spaces have been introduced to help clarify the key concepts about visual narratives [31,40,46] and provide fundamental design principles [24,25,44,45,60]. Early studies focused on high-level concepts.…”

“…Stolper et al [46] presented four high-level categories of narrative visualization techniques. Recent studies introduce several design spaces that more elaborately provide fundamental design principles from two major aspects: the narrative structures [25,60] and the visual representation methods [24,44,45], while taking communication goals and design tasks into consideration.…”

“…To facilitate the creation of data stories, during the past decades, theories, techniques, and tools have been extensively studied and developed. For example, a series of design spaces have been proposed from two major aspects: the narrative structures [25,60] and the visual representation methods [18,24,31,40,[44][45][46], while taking communication goals and tasks into consideration. At the same time, to lower the technical barriers, a number of interactive authoring tools that integrate advanced data analysis and visualization functionalities have been developed [8,27,53,55].…”