相关论文: Identifying Framing Practices in Visualization Des…
The intersection of visualization and the humanities (VIS*H) is marked by a tension between chasing analytical "insight" and interpretive "meaning." The effectiveness of visualization techniques hinges on established evaluation frameworks…
Visualization's design knowledge-effectiveness rankings, encoding guidelines, color models, preattentive processing rules -- derives from six decades of psychophysical studies of human vision. Yet vision-language models (VLMs) increasingly…
Information design is typically studied through the lens of Bayesian signaling, where signals shape beliefs purely based on their correlation with the true state of the world. However, behavioral economics and psychology emphasize that…
Visual representations are becoming important in science communication and education. This explorative study investigates the perception of STEM researchers, without any specific visual design background, and the value of visual…
This paper is a call to action for research and discussion on data visualization education. As visualization evolves and spreads through our professional and personal lives, we need to understand how to support and empower a broad and…
Large language models (LLMs) are increasingly integrated into design and development workflows, yet decisions about their use are rarely binary or purely technical. We report findings from a constructivist grounded theory study based on…
Great storytellers know how to take us on a journey. They direct characters to act -- not necessarily in the most rational way -- but rather in a way that leads to interesting situations, and ultimately creates an impactful experience for…
Traditional approaches to data visualization have often focused on comparing different subsets of data, and this is reflected in the many techniques developed and evaluated over the years for visual comparison. Similarly, common workflows…
Information visualization plays a key role in business intelligence analytics. With ever larger amounts of data that need to be interpreted, using the right visualizations is crucial in order to understand the underlying patterns and…
Problem-driven visualization work is rooted in deeply understanding the data, actors, processes, and workflows of a target domain. However, an individual's personality traits and cognitive abilities may also influence visualization use.…
Analysts increasingly explore data through evolving, narrative-driven inquiries, moving beyond static dashboards and predefined metrics as their questions deepen and shift. As these explorations progress, insights often become dispersed…
Visualization linters are end-user facing evaluators that automatically identify potential chart issues. These spell-checker like systems offer a blend of interpretability and customization that is not found in other forms of automated…
Among different phases of the life cycle of a building or facility, design is of the utmost importance to ensure safety, efficiency and sustainability of the building or facility. How to control and improve design quality and efficiency has…
Recent advances in image generation have made diffusion models powerful tools for creating high-quality images. However, their iterative denoising process makes understanding and interpreting their semantic latent spaces more challenging…
Understanding the agent's learning process, particularly the factors that contribute to its success or failure post-training, is crucial for comprehending the rationale behind the agent's decision-making process. Prior methods clarify the…
Clinicians and other analysts working with healthcare data are in need for better support to cope with large and complex data. While an increasing number of visual analytics environments integrates explicit domain knowledge as a means to…
Current research on visual analytics systems largely follows the research paradigm of interactive system design in the field of Human-Computer Interaction (HCI), and includes key methodologies including design requirement development based…
Data visualization should be accessible for all analysts with data, not just the few with technical expertise. Visualization recommender systems aim to lower the barrier to exploring basic visualizations by automatically generating results…
The urgency of climate change is now recognized globally. As humanity confronts the critical need to mitigate climate change and foster sustainability, data visualization emerges as a powerful tool with a unique capacity to communicate…
Standing at the intersection of science and art, artistic data visualization has gained popularity in recent years and emerged as a significant domain. Despite more than a decade since the field's conceptualization, a noticeable gap remains…