Abstract Modern visualization software and programming libraries have made data visualization construction easier for everyone. However, the extent of accessibility design they support for blind and low‐vision people is relatively unknown. It is also unclear how they can improve chart content accessibility beyond conventional alternative text and data tables. To address these issues, we examined the current accessibility features in popular visualization tools, revealing limited support for the standard accessibility methods and scarce support for chart content exploration. Next, we investigate two promising accessibility approaches that provide off‐the‐shelf solutions for chart content accessibility: structured navigation and conversational interaction. We present a comparative evaluation study and discuss what to consider when incorporating them into visualization tools.

Computational thinking is nowadays considered an essential skill in the K-12 educational curriculum. Many tangible computational kits designed for early childhood are either too expensive to benefit a wide range of children or only provide predetermined challenges with limited creative content creation opportunities. In this paper, we investigated low-cost and expressive tangible interfaces that foster computational literacy. We present Draw2Code, a paper-based computational kit for young children to create an interactive AR animation. Children use Draw2Code to make their paper drawing alive as an animated virtual sprite and control it using hand gestures. It exposes children to basic programming concepts through playful and tangible interaction. Results from our initial evaluation with nine child-parent dyads indicate that children ages 5 to 12 successfully used Draw2Code and played with Draw2Code in 33 minutes on average while creating 2 to 5 diverse AR animations based on their ideas. Throughout the session, all children were engaged in computational thinking concepts and practices and learned drawing and gesture-based interactions.

Many personal informatics systems allow people to collect and manage personal data and reflect more deeply about themselves. However, these tools rarely offer ways to customize how the data is visualized. In this work, we investigate the question of how to enable people to determine the representation of their data. We analyzed the Dear Data project to gain insights into the design elements of personal visualizations. We developed DataSelfie, a novel system that allows individuals to gather personal data and design custom visuals to represent the collected data. We conducted a user study to evaluate the usability of the system as well as its potential for individual and collaborative sensemaking of the data.

In this paper, we present story curves, a visualization technique for exploring and communicating nonlinear narratives in movies. A nonlinear narrative is a storytelling device that portrays events of a story out of chronological order, e.g., in reverse order or going back and forth between past and future events. Many acclaimed movies employ unique narrative patterns which in turn have inspired other movies and contributed to the broader analysis of narrative patterns in movies. However, understanding and communicating nonlinear narratives is a difficult task due to complex temporal disruptions in the order of events as well as no explicit records specifying the actual temporal order of the underlying story. Story curves visualize the nonlinear narrative of a movie by showing the order in which events are told in the movie and comparing them to their actual chronological order, resulting in possibly meandering visual patterns in the curve. We also present Story Explorer, an interactive tool that visualizes a story curve together with complementary information such as characters and settings. Story Explorer further provides a script curation interface that allows users to specify the chronological order of events in movies. We used Story Explorer to analyze 10 popular nonlinear movies and describe the spectrum of narrative patterns that we discovered, including some novel patterns not previously described in the literature. Feedback from experts highlights potential use cases in screenplay writing and analysis, education and film production. A controlled user study shows that users with no expertise are able to understand visual patterns of nonlinear narratives using story curves.