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Information Visualization techniques are built on a context with many factors related to both vision and cognition, making it difficult to draw a clear picture of how data visually turns into comprehension. In the intent of promoting a…
Data-driven predictions are often perceived as inaccurate in hindsight due to behavioral responses. In this study, we explore the role of interface design choices in shaping individuals' decision-making processes in response to predictions…
A natural language interface exploits the conceptual simplicity and naturalness of the language to create a high-level user-friendly communication channel between humans and machines. One of the promising applications of such interfaces is…
Analyzing interaction data provides an opportunity to learn about users, uncover their underlying goals, and create intelligent visualization systems. The first step for intelligent response in visualizations is to enable computers to infer…
Using causal relations to guide decision making has become an essential analytical task across various domains, from marketing and medicine to education and social science. While powerful statistical models have been developed for inferring…
The quest to develop intelligent visual analytics (VA) systems capable of collaborating and naturally interacting with humans presents a multifaceted and intriguing challenge. VA systems designed for collaboration must adeptly navigate a…
In this paper, we present our design study on developing an interactive visual firewall log analysis system in collaboration with an IT service provider. We describe the human-centered design process, in which we additionally considered…
We survey a number of data visualization techniques for analyzing Computer Vision (CV) datasets. These techniques help us understand properties and latent patterns in such data, by applying dataset-level analysis. We present various…
As data visualizations have been increasingly applied in mass communication, designers often seek to grasp viewers immediately and motivate them to read more. Such goals, as suggested by previous research, are closely associated with the…
As the rate of data collection continues to grow rapidly, developing visualization tools that scale to immense data sets is a serious and ever-increasing challenge. Existing approaches generally seek to decouple storage and visualization…
Data has transformative potential to empower people with Intellectual and Developmental Disabilities (IDD). However, conventional data visualizations often rely on complex cognitive processes, and existing approaches for day-to-day analysis…
Online writers and journalism media are increasingly combining visualization (and other multimedia content) with narrative text to create narrative visualizations. Often, however, the two elements are presented independently of one another.…
The intersection of data visualization and human-robot interaction (HRI) is a burgeoning field. Understanding, communicating, and processing different kinds of data for creating versatile visualizations can benefit HRI. Conversely,…
Visual Analytics (VA) integrates humans, data, and models as key actors in insight generation and data-driven decision-making. This position paper values and reflects on 16 VA process models and frameworks and makes nine high-level…
Natural language interfaces (NLIs) for data visualization are becoming increasingly popular both in academic research and in commercial software. Yet, there is a lack of empirical understanding of how people specify visualizations through…
Sensemaking is the cognitive process of extracting information, creating schemata from knowledge, making decisions from those schemata, and inferring conclusions. Human analysts are essential to exploring and quantifying this process, but…
With most modern visualization tools, authors need to transform their data into tidy formats to create visualizations they want. Because this requires experience with programming or separate data processing tools, data transformation…
This paper describes the process of developing data visualisations to enhance a commercial software platform for combating insider threat, whose existing UI, while perfectly functional, was limited in its ability to allow analysts to easily…
Human-AI interfaces play a pivotal role in integrating clinicians' expertise with artificial intelligence to enhance both healthcare practice and research. However, designing effective interfaces in this domain remains a significant…
In recent years, considerable work has been devoted to explaining predictive, deep learning-based models, and in turn how to evaluate explanations. An important class of evaluation methods are ones that are human-centered, which typically…