Background

We are living in times where massive amounts of data are gathered on a daily basis. Understanding and interpreting them correctly is essential to decision making. The worldwide pandemic has led to an increased public interest in the discipline of Data Visualization. The transformation of abstract data – tables and lists of numbers – into visual representations makes it easier for people to see systems, patterns, and relationships in them. However, data are becoming increasingly complex, up to the point where traditional pie- bar- and line charts are no longer sufficient to display all aspects of it. Since we usually do not learn how to interpret visualizations beyond these simple forms in the course of our education, most people have difficulties working with them. Recently, researchers have been exploring so-called “onboarding systems” to introduce novice users to complex (interactive) visualizations (i.e., to enable them to learn to interpret them by themselves).

Project Content

Communicating data to different groups of people with different levels of expertise and different levels of visualization literacy (the ability to interpret different kinds of data visualizations) is a challenge. Various formats with the aim to make data more accessible have been established over time, but many of them sacrifice details about methods, conditions, and context for simplicity. This is good to bring certain messages across but makes it hard to verify claims and make informed decisions. A recent attempt of presenting data in an appealing way while still preserving the details were made in the form of Data Comics, a young genre of data-driven storytelling. Storytelling can also be used in onboarding processes for visualization, since its step-by-step structure facilitates learning.

Goals

Data Comics are an effective way to communicate data in an accessible, but not oversimplified way. Through their story-driven approach, they enhance comprehensibility and enable the viewer to consume the content at their own pace and desired level of detail. This makes them a suitable tool to guide novice users through the process of learning an interactive visualization (the “onboarding”). Adding features of other multimedia learning methods (such as interactivity and animation) could enhance their effectivity. Building on these assumption, the following research questions arise:

• How can Data Comics support users with low visualization literacy in understanding interactive, dynamic visualizations?
• How do Data Comics have to be designed to ensure a good understanding of what they want to convey to their target groups?
• In what ways do interactivity and the integration of animation influence how users perceive and learn from Data Comics?
• How can Data Comics be integrated into onboarding processes during which users are introduced to interactive visualizations?

Methods

Existing onboarding approaches and Data Comics will be evaluated in the course of a state-of-the-art analysis. Interviews with experts and potential users will be conducted to identify patterns in the usage of onboarding systems and how Data Comics might influence these patterns. Target groups will be defined and modelled through personas (i.e., a fictional person representing a target group’s characteristics and goals). Since students in particular benefit from comics in knowledge transfer, the main target group will be students from 14 to 19 years. Based on interviews with users of these target groups, use cases in which Data Comics can support visualization learning processes will be defined. Concepts of possible solutions will be developed and refined in focus groups and design thinking workshops. Building on the insights gained, prototypes of comic-supported onboardings will be created. They will be evaluated through qualitative user tests using methods such as log analyses, observations, interviews and eye-tracking; The results of these evaluations will then be used to create new prototypes, which will be evaluated again. This procedure will be repeated until it yields a workable solution (i.e., iterative prototyping). All the insights gained will be transformed into a design framework and guidelines on how to use Data Comics for onboarding scenarios.

Results

Data Comics are a valuable tool to support people in understanding and learning about complex data visualizations. However, going beyond static representations by enabling interactivity and adding cinematographic elements such as animations may help to further improve the process of learning and understanding interactive visualizations. In this project, it will be evaluated how they can be incorporated into a visualization onboarding process by developing multiple prototypes and testing their practicality. The insights gained during this process result in design and implementation guidelines and will be published in peer-reviewed journals and conferences in the field of information visualization and human-computer interaction, such as IEEE CG&A / TVCG, IEEE Vis, CHI, EuroVIS, AVI, or C&C.