Abstract Evidence continues to accrue around the difficulties people have understanding new and complex visualizations, which in turn provides continued incentive to explore additional methods of supporting visualization viewers. Through leveraging viewers' spontaneous visualization sensemaking activities, we introduce a Serendipitous Explanation Approach (SEA). A significant part of SEA's contribution is making active use of a viewer's spontaneous, exploration interactions to offer in situ explanations. SEA adds semantic and structural explanations, making use of visual transformations, and additional representations of visualization elements themselves to communicate meaning through highlights, reconfigurations, and in‐situ annotations. We designed and studied VisTips as an instantiation of SEA. Our study demonstrates the prevalence of spontaneous interaction and appreciation of this approach. Among the explanation types, visual transformations stood out as especially impactful. Our findings also offer practical insights for future use of the ideas in SEA, opening possibilities for seamlessly integrating explanatory visuals that support viewers' natural visualization sensemaking.

Enhancing visualization comprehension has been approached through multiple research streams, with significant contributions from areas such as visualization literacy, sensemaking, insight, and graphical perception. While each of these streams independently enhances specific aspects of viewers understanding, they have tended to remain distinct. In this paper, first, we describe the distinct streams of visualization comprehension research and elucidate the interplay between them. Then, we provide design considerations that emerge from these streams. We also outline research opportunities within and at the intersections of these streams. By exploring these connections, we aim to provide a broader perspective on how different approaches to visualization comprehension can inform one another and enhance user engagement with visual data.

This paper investigates how people use physical space, free from digital constraints, to organize thoughts and ideas. Such spatial arrangements commonly support sensemaking, idea generation, and data understanding. We collected over 300 publicly shared images capturing these activities collected from real-world contexts. Our visual analysis identifies a small set of recurring spatial patterns such as clusters, grids as well as the techniques people use to build and adapt them, such as color coding, directional lines, and selective rule-following. We discuss how these practices can inform the design of more expressive and adaptable digital spatially-aware tools that better support the diverse ways people think with space.

We designed, developed, and studied a visualization, WPHPVis, to support exploration of the Women’s Print History Project (WPHP) data. WPHP are manually-collecting a bibliography that spans the years 1700 to 1836 recording information about books in which women have been involved through a number of roles including as authors, editors, translators, publishers, printers and booksellers. By working directly with WPHP experts to focus on their understanding, and their research practices and needs, we co-designed WPHPVis using interactive construction of network links to support exploration of their data. Through our qualitative study with both experts and non-experts, we learned about how the tool supported the WPHP experts’ research practices as well as about how to improve overall interactive experience. We conclude by discussing the importance of representing missing data, the advantages of striking a balance between visualization structure and explorability, and the opportunities enabled by co-design with domain experts.

While the visualization community is increasingly aware that people often find visualizations difficult to understand, there is less information about what we need to do to create comprehensible visualizations. To help visualization creators and designers improve their visualizations, we need to better understand what kind of support people are looking for in their sensemaking process. Empirical studies are needed to tease apart the details of what makes the process of understanding difficult for visualization viewers. We conducted a qualitative study with 14 participants, observing them as they described how they were trying to make sense of 20 information visualizations. We identified the challenges participants faced throughout their sensemaking process and the strategies they employed to help themselves in overcoming the challenges. Our findings show how details and nuances within visualizations can impact comprehensibility and offer research suggestions to help us move toward more understandable visualizations.

An important challenge in smart environments is how to manipulate the smart objects. Although mobile applications are typically used for controlling a smart environment, no previous study has evaluated the users performance in manipulating smart objects under different environmental complexities. This article presents an experimental comparison between three different selection techniques 3-D, 2-D, and physical user interfaces (UIs). We evaluate these techniques across two levels of environment complexity measuring 51 participants timing data and errors. Our results indicate that the 3-D UI is superior for task completion time and error, and the 2-D UI is not a better solution than the physical UI when the environment is not complex. The results also show the importance of considering the environment complexity in choosing the proper UI.