We explore the design and utility of situated manual self-tracking visualizations on dedicated displays that integrate data tracking into existing practices and physical environments. Situating self-tracking tools in relevant locations is a promising approach to enable reflection on and awareness of data without needing to rely on sensorized tracking or personal devices. In both a long-term autobiographical design process and a co-design study with six participants, we rapidly prototyped and deployed 30 situated self-tracking applications over a ten month period. Grounded in the experience of designing and living with these trackers, we contribute findings on logging and data entry, the use of situated displays, and the visual design and customization of trackers. Our results demonstrate the potential of customizable dedicated self-tracking visualizations that are situated in relevant physical spaces, and suggest future research opportunities and new potential applications for situated visualizations.
https://dl.acm.org/doi/abs/10.1145/3491102.3517737
Basketball writers and journalists report on the sport that millions of fans follow and love. However, the recent emergence of pervasive data about the sport and the growth of new forms of sports analytics is changing writers' jobs. While these writers seek to leverage the data and analytics to create engaging, data-driven stories, they typically lack the technical background to perform analytics or efficiently explore data. We investigated and analyzed the work and context of basketball writers, interviewed nine stakeholders to understand the challenges from a holistic view. Based on what we learned, we designed and constructed two interactive visualization systems that support rapid and in-depth sports data exploration and sense-making to enhance their articles and reporting. We deployed the systems during the recent NBA playoffs to gather initial feedback. This article describes the visualization design study we conducted, the resulting visualization systems, and what we learned to potentially help basketball writers in the future.
https://dl.acm.org/doi/abs/10.1145/3491102.3502078
Data videos are an increasingly popular storytelling form. The opening of a data video critically influences its success as the opening either attracts the audience to continue watching or bores them to abandon watching. However, little is known about how to create an attractive opening. We draw inspiration from the openings of famous films to facilitate designing data video openings. First, by analyzing over 200 films from several sources, we derived six primary cinematic opening styles adaptable to data videos. Then, we consulted eight experts from the film industry to formulate 28 guidelines. To validate the usability and effectiveness of the guidelines, we asked participants to create data video openings with and without the guidelines, which were then evaluated by experts and the general public. Results showed that the openings designed with the guidelines were perceived to be more attractive, and the guidelines were praised for clarity and inspiration.
https://dl.acm.org/doi/abs/10.1145/3491102.3501896
Designing responsive visualizations can be cast as applying transformations to a source view to render it suitable for a different screen size. However, designing responsive visualizations is often tedious as authors must manually apply and reason about candidate transformations. We present Cicero, a declarative grammar for concisely specifying responsive visualization transformations which paves the way for more intelligent responsive visualization authoring tools. Cicero's flexible specifier syntax allows authors to select visualization elements to transform, independent of the source view's structure. Cicero encodes a concise set of actions to encode a diverse set of transformations in both desktop-first and mobile-first design processes. Authors can ultimately reuse design-agnostic transformations across different visualizations. To demonstrate the utility of Cicero, we develop a compiler to an extended version of Vega-Lite, and provide principles for our compiler. We further discuss the incorporation of Cicero into responsive visualization authoring tools, such as a design recommender.
https://dl.acm.org/doi/abs/10.1145/3491102.3517455