Related papers: Visualizing the Weird and the Eerie
As online news increasingly include data journalism, there is a corresponding increase in the incorporation of visualization in article thumbnail images. However, little research exists on the design rationale for visualization thumbnails,…
Experiential AI is proposed as a new research agenda in which artists and scientists come together to dispel the mystery of algorithms and make their mechanisms vividly apparent. It addresses the challenge of finding novel ways of opening…
Micro-expressions are brief and subtle facial movements that convey nuanced affective information but often remain imperceptible during natural social interaction. Although prior research has primarily focused on computational recognition…
Charts are used to communicate data visually, but often, we do not know whether a chart's intended message aligns with the message readers perceive. In this mixed-methods study, we investigate how data journalists encode data and how…
In order to ground my approach to the study of paranormal phenomena, I first explain my operational approach to physics, and to the ``historical'' sciences of cosmic, biological, human, social and political evolution. I then indicate why I…
Physical representations of data offer physical and spatial ways of looking at, navigating, and interacting with data. While digital fabrication has facilitated the creation of objects with data-driven geometry, rendering data as a…
This paper is a collaborative piece between two worlds of expertise in the field of data visualization: accessibility and bias. In particular, the rise of generative models playing a role in accessibility is a worrying trend for data…
A strange metal is an exotic state of correlated quantum matter; intensive efforts are ongoing to decipher its nature. Here we explore whether the quantum Fisher information (QFI), a concept from quantum metrology, can provide new insight.…
The power of neural networks lies in their ability to generalize to unseen data, yet the underlying reasons for this phenomenon remain elusive. Numerous rigorous attempts have been made to explain generalization, but available bounds are…
The diffusion of AI and big data is reshaping decision-making processes by increasing the amount of information that supports decisions while reducing direct interaction with data and empirical evidence. This paradigm shift introduces new…
In creating SkyGlyphs, our goal was to develop a data visualization that could possibly capture people's attention and spark their curiosity to explore a dataset. This work was inspired by a mingling of research including serendipitous…
Students of visualization come to formal education with an abundance of personal experience. However, one's exposure to graphics through media and education may not be sufficiently diverse to appreciate the nuance and complexity required to…
Few concepts are as ubiquitous in computational fields as trust. However, in the case of information visualization, there are several unique and complex challenges, chief among them: defining and measuring trust. In this paper, we…
The visualization community has a rich history of reflecting upon flaws of visualization design, and research in this direction has remained lively until now. However, three main gaps still exist. First, most existing work characterizes…
This paper contributes a novel visualization method, Missingness Glyph, for analysis and exploration of missing values in data. Missing values are a common challenge in most data generating domains and may cause a range of analysis issues.…
Chartjunk is a popular yet contentious topic. Previous studies have shown that extreme minimalism is not always best, and that visual embellishments can be useful depending on the context. While more knowledge is being developed regarding…
The rapid advancement of AI is transforming human-centered systems, with profound implications for human-AI interaction, human-data interaction, and visual analytics. In the AI era, data analysis increasingly involves large-scale,…
Rule sets are often used in Machine Learning (ML) as a way to communicate the model logic in settings where transparency and intelligibility are necessary. Rule sets are typically presented as a text-based list of logical statements…
High-dimensional representations for words, text, images, knowledge graphs and other structured data are commonly used in different paradigms of machine learning and data mining. These representations have different degrees of…
The goal of this paper is to investigate the importance of providing visual "big pictures" in the teaching of economics. The plurality and variety of concepts, variables, diagrams, and models involved in economics can be a source of…