In this work, we explore different combinations of techniques for an interactive, on-body visualization in augmented reality (AR) of an upper arm muscle simulation model. In terms of data, we focus on a continuum-mechanical simulation model involving five different muscles of the human upper arm, with physiologically realistic geometry. In terms of use cases, we focus on the immersive illustration, education, and dissemination of such simulation models. We describe the process of developing six on-body visualization prototypes over the period of five years. For each prototype, we employed different types of motion capture, AR display technologies, and visual encoding approaches, and gathered feedback throughout outreach activities. We reflect on the development of the individual prototypes and summarize lessons learned of our exploration process into the design space of situated on-body visualization.

Bus route planning is a complex application problem within the transportation domain, aiming to identify the best route among numerous candidate solutions. Despite existing research significantly reducing the exploration space of solutions, planners still face challenges in further exploring optimal route planning solutions. Specifically, the diversity of route attributes increases the complexity of determining their impact, such as the variety and quantity of reachable points of interest. Therefore, we present BRPVis, an interactive visual analytics system designed to assist bus route planners in exploring optimal solutions through multi-level visualization and rich interaction design. Furthermore, we propose a human-machine collaborative multicriteria decision-making method, which quantitatively analyzes the weights of route attributes while incorporating interactive feedback mechanisms to support personalized route exploration. Based on exploration using real-world traffic datasets, three case studies conducted with domain experts demonstrate that BRPVis effectively provides decision support for bus route planning tasks.

Fiber tracking is a powerful technique that provides insight into the brain's white matter structure. Despite its potential, the inherent uncertainties limit its widespread clinical use. These uncertainties potentially hamper the clinical decisions neurosurgeons have to make before, during, and after the surgery. Many techniques have been developed to visualize uncertainties, however, there is limited evidence to suggest whether these uncertainty visualization influences neurosurgical decision-making. In this paper, we evaluate the hypothesis that uncertainty visualization in fiber tracking influences neurosurgeon's decisions and the confidence in their decisions. For this purpose, we designed a user study through an online interactive questionnaire and evaluate the influence of uncertainty visualization in neurosurgical decision-making. The results of this study emphasize the importance of uncertainty visualization in clinical decision making by highlighting the influence of different interval of uncertainty visualization in critical clinical decisions.

It is time- and man-power intensive to craft various fish species for underwater animations and games. Even professionals spend hours to days for one. Therefore, we propose Procedural Fish Generation, which presents an innovative and automatic approach to generate 3D fish models with one lateral image. The core lies in parameterizing the ray-finned fish with curves and optimizing them with textures to fit the input using differentiable rendering, greatly reducing the manual modeling work. It presents advantages over multi-image reconstruction in requiring single image, while state-of-the-art methods suffer from such a scenario to achieve informative reconstruction. Also, our method outputs a polygon mesh, widely compatible with modern graphics hardware and software, thus facilitating further editing. Furthermore, we fine tune the prompts for Stable Diffusion while users can type a name to find high-quality lateral images. Extensive ablation studies and comparisons have proved its effectiveness and efficiency for experts and non-experts.

A sphere-mesh is a class of geometric proxies defined as the volume swept by spheres with linearly interpolated centers and radii, potentially striking a good balance between conciseness of representation, simplicity of spatial queries, and expressive power. We investigate the semiautomatic generation of sphere-meshes from standard triangular meshes. We improve one known automatic construction algorithm, based on iterative local coarsening operation, by introducing a mechanism to prevent operations that would result in spheres exceeding the target shape; then, we propose a 3-D interface designed to permit users to easily and intuitively modify the automatically generated sphere-meshes. The two phases, an improved automatic algorithm and a novel interactive tool, used in cascade, constitute a viable semiautomatic way to produce high-quality sphere-meshes. We test our method on several inputs tri-meshes, assess their quality, and finally exemplify the usability of our results by testing them in a few downstream applications.

The ongoing second quantum revolution, marked by advancements harnessing quantum phenomena, has permeated various fields, including communications, computation, and networking, collectively known as quantum technologies (QTs). Quantum computing, a focal point within QT, has led to the emergence of quantum games, a novel research and development area exploring creative applications of quantum computing in game development. While more than 300 quantum games have been developed by enthusiasts and commercial parties, a comprehensive research program or state-of-the-art review is notably absent. This article addresses this gap by conducting a thorough literature review, presenting current advancements and examples in quantum games and interactive designs, and exploring future prospects for QT in game development practices.

Business uses of charts and visualizations, and by extension business users, are usually considered mundane and boring. But they, too, want to get their audience's attention, emphasize a point they are making, or simply break out of the monotony of the limited palette of common chart types. I believe that there is ample opportunity to develop new approaches and build better tools that go far beyond the current one-size-fits-all approach to creating charts-much more than is currently recognized in the visualization community. The first step is to reexamine our notions of who business users are, and what they actually want and need.

In this article, we investigated the representation of wind in urban spaces through computational fluid dynamics simulations in virtual environments (VE). We compared wind perception (force and direction) as well as the sense of presence and embodiment in VE using different display technologies: head-mounted displays (HMD) and large screens, with or without an avatar. The tactile display was found to be most effective for detecting wind characteristics and enhancing presence and embodiment in virtual scenes, regardless of display type. Wind force and overall presence showed no significant differences between projection methods, but the perception of wind direction varied, which can be attributed to the head tracking of the HMD. In addition, gender differences emerged: females had a 7.42% higher presence on large screens, while males had a 23.13% higher presence with HMD (avatar present). These results highlight nuances in wind perception, the influence of technology, and gender differences in VE.

ParaView is one of the most prominent software tools for scientific visualization used by scientists around the world. Color is a primary conduit to visually map data to its representation and, thus, enable investigation and interpretation of the data. Colormap selection has a significant impact on the data revealed; its design and selection is a critical aspect of scientific data visualization. A common choice for a user is the program's default colormap, so careful consideration of this default is consequential. Although the current default colormap in ParaView, a succession of hues from cool blue to warm red, has served the community well, research shows that more nuanced colormap configurations increase discriminability while maintaining other critical metrics. These findings inspire us to revisit and update the default colors in ParaView. Here we present a new ParaView default colormap, the criteria and methods of development, and example visualizations and analytic metrics.

Scientists often explore and analyze large-scale scientific simulation data by leveraging 2-D and 3-D visualizations. The data and tasks can be complex and therefore best supported using myriad display technologies, from mobile devices to large high-resolution display walls to virtual reality headsets. Using a simulation of neuron connections in the human brain provided for the 2023 IEEE Scientific Visualization Contest, we present our work leveraging various web technologies to create a multiplatform scientific visualization application. Users can spread visualization and interaction across multiple devices to support flexible user interfaces and both colocated and remote collaboration. Drawing inspiration from responsive web design principles, this work demonstrates that a single codebase can be adapted to develop scientific visualization applications that operate everywhere.

Recent developments in extended reality (XR) are already demonstrating the benefits of this technology in the educational sector. Unfortunately, educators may not be familiar with XR technology and may find it difficult to adopt this technology in their classrooms. This article presents the overall architecture and objectives of an EU-funded project dedicated to XR for education, called Extended Reality for Education (XR4ED). The goal of the project is to provide a platform, where educators will be able to build XR teaching experiences without the need to have programming or 3-D modeling expertise. The platform will provide the users with a marketplace to obtain, for example, 3-D models, avatars, and scenarios; graphical user interfaces to author new teaching environments; and communication channels to allow for collaborative virtual reality (VR). This article describes the platform and focuses on a key aspect of collaborative and social XR, which is the use of avatars. We show initial results on a) a marketplace which is used for populating educational content into XR environments, b) an intelligent augmented reality assistant that communicates between nonplayer characters and learners, and c) self-avatars providing nonverbal communication in collaborative VR.

Visualizations of mass shooting incidents in the United States appearing in the media can influence people's beliefs and attitudes. However, different data sources each use their own definition of mass shootings, resulting in varying counts and trends of these incidents across the sources. To investigate the effects of these varying definitions on public perceptions, we conducted a crowdsourced study using data from four sources-Mother Jones, Mass Shooter Database, Everytown for Gun Safety, and The Washington Post. We used one or more line plots, with or without explicitly providing the definition, to see how these variations affect viewers' understanding of a 10-year trend in mass shooting frequency. We found that, depending on the data shown, participants' perceptions of the trend changed in both directions (i.e., more or less increasing) compared to their prestudy perceptions. We discuss how data from a single source can influence people's perceptions, and how visualizing data from multiple sources (e.g., superimposed line graphs) can enable more transparent communication. Our work has implications for other media and public visualizations, highlighting the importance of embracing pluralistic approaches to enquiry, especially when dealing with data of significant importance and consequence.

As a self-professed AI artist, Nina Rajcic presented an opportunity for us to explore a curiosity regarding how AI artists have been developing a process during an AI boon brought on by transformer and generative AI tools. Although her journey has been one of pursuing text as a creative output, the nature of transformers and diffusion suggested relevance to graphical outputs. The following interview did not disappoint in that pursuit.

Virtual reality (VR) is increasingly employed in archaeology to showcase reconstructions of ancient sites to the general public, yet its utilization for professional purposes by archaeologists remains less common. To address this gap, we introduce a VR application specifically designed to streamline the storage and access of critical data for archaeological studies. This application provides experts with an immersive visualization of excavation sites and related information during the postexcavation analysis phase. The application interface facilitates direct interaction with 3-D models generated through photogrammetry and modeling techniques, enabling detailed examination of collected data and enhancing research activities. We applied this system to the case study of excavations at the Temple of Juno in Agrigento, Italy. In addition, we present the findings of a pilot user study involving archaeologists, which evaluates the effectiveness of immersive technologies for professionals in documenting, preserving, and exploring archaeological sites, while also driving potential future developments.

We have enjoyed getting to know Beatie Wolfe after finding her work to be compelling for its consistent ability to use art and communication to build bridges between different societal worlds. Beatie is a multimedia artist who started her career reimagining the ceremonial experiences of analog music formats, creating a new series of retro-future designs for the digital age, and now perfects an artistic process, which melds art and science and other disciplines to create stunning multifaceted installations that draw huge enthusiastic audiences when displayed in public.

Quantum computers exhibit an inherent randomness, so it seems natural to consider them for procedural content generation. In this work, a quantum version of the famous (classical) wave function collapse algorithm is proposed. This quantum wave function collapse algorithm is based on the idea that a quantum circuit can be prepared in such a way that it acts as a special-purpose random generator for content of a desired form. The proposed method is presented theoretically and investigated experimentally on simulators and IBM Quantum devices.

This article presents AlterVerse, a framework that provides users with novel experiences through visual illusions of interactively altering physical objects in extended reality environments. In the AlterVerse framework, physical objects are seamlessly virtualized by aligning their 3-D virtual replicas with them. It enables users to manipulate (move or rotate) and reshape (deform the shapes or transform the styles of) the physical objects virtually. Simultaneously, the physical objects are visually removed from a physical environment, creating the perception that the altering occurs directly on the physical objects. As a promising application of the AlterVerse framework, the article demonstrates interactive virtual altering of home furniture in interior design or decoration scenarios without physically altering existing furniture.

This article introduces an innovative interactive visualization tool designed to demystify quantum machine learning (QML) algorithms. Our work is inspired by the success of classical machine learning visualization tools, such as TensorFlow Playground, and aims to bridge the gap in visualization resources specifically for the field of QML. The article includes a comprehensive overview of relevant visualization metaphors from both quantum computing and classical machine learning, the development of an algorithm visualization concept, and the design of a concrete implementation as an interactive web application. By combining common visualization metaphors for the so-called data reuploading universal quantum classifier as a representative QML model, this article aims to lower the entry barrier to quantum computing and encourage further innovation in the field. The accompanying interactive application is a proposal for the first version of a QML playground for learning and exploring QML models.

We present Q-Seg, a novel unsupervised image segmentation method based on quantum annealing, tailored for existing quantum hardware. We formulate the pixelwise segmentation problem, which assimilates spectral and spatial information of the image, as a graph-cut optimization task. Our method efficiently leverages the interconnected qubit topology of the D-wave advantage device, offering superior scalability over existing quantum approaches and outperforming several tested state-of-the-art classical methods. Empirical evaluations on synthetic datasets have shown that Q-Seg has better runtime performance than the state-of-the-art classical optimizer Gurobi. The method has also been tested on earth observation image segmentation, a critical area with noisy and unreliable annotations. In the era of noisy intermediate-scale quantum, Q-Seg emerges as a reliable contender for real-world applications in comparison to advanced techniques like Segment Anything. Consequently, Q-Seg offers a promising solution using available quantum hardware, especially in situations constrained by limited labeled data and the need for efficient computational runtime.

Visualization is crucial to augment and enhance human understanding and decision-making in today's data-driven world. However, the way data are visualized can influence and drastically change the conclusions people draw using data. The findings around visualization effectiveness are nuanced, and guidelines for effective visualization design depend on the visual channels used, chart types, and analysis tasks. This points to a significant need to understand the intersection of these factors to create optimized visualizations. We need a framework to define this intersection that fills the gap by providing a task-optimized visualization design for better quality and higher decision-making confidence that gives designers objective guidance. A task-optimized visualization design framework strategically integrates visual channels, visualization types, and specific low-level tasks to enhance data interpretation and optimize user task performance. We discuss constructing a visualization framework that considers both human perception for encoding techniques and the task being performed, enabling optimizing visualization design to maximize efficiency. Furthermore, we highlight a task-optimized framework's impact and potential applications.

Quantum computing is a highly abstract scientific discipline, which, however, is expected to have great practical relevance in future information technology. This forces educators to seek new methods to teach quantum computing for students with diverse backgrounds and with no prior knowledge of quantum physics. We have developed an online course built around an interactive quantum circuit simulator designed to enable easy creation and maintenance of course material with ranging difficulty. The immediate feedback and automatically evaluated tasks lower the entry barrier to quantum computing for all students, regardless of their background.