Dashboards have arguably been the most used visualizations during the COVID-19 pandemic. They were used to communicate its evolution to national governments for disaster mitigation, to the public domain to inform about its status, and to epidemiologists to comprehend and predict the evolution of the disease. Each design had to be tailored for different tasks and to varying audiences—in many cases set up in a very short time due to the urgent need. In this article, we collect notable examples of dashboards and reflect on their use and design during the pandemic from a user-oriented perspective. We interview a group of researchers with varying visualization expertise who actively used dashboards during the pandemic as part of their daily workflow. We discuss our findings and compile a list of lessons learned to support future visualization researchers and dashboard designers.

To understand current practice and explore the potential for more comprehensive evaluations of 3D immersive sketching, drawing, and painting, we present a survey of evaluation methodologies used in existing 3D sketching research, a breakdown and discussion of important phases (sub-tasks) in the 3D sketching process, and a framework that suggests how these factors can inform evaluation strategies in future 3D sketching research. Existing evaluations identified in the survey are organized and discussed within three high-level categories: 1) evaluating the 3D sketching activity, 2) evaluating 3D sketching tools, and 3) evaluating 3D sketching artifacts. The new framework suggests targeting evaluations to one or more of these categories and identifying relevant user populations. In addition, building upon the discussion of the different phases of the 3D sketching process, the framework suggests to evaluate relevant sketching tasks, which may range from low-level perception and hand movements to high-level conceptual design. Finally, we discuss limitations and challenges that arise when evaluating 3D sketching, including a lack of standardization of evaluation methods and multiple, potentially conflicting, ways to evaluate the same task and user interface usability; we also identify opportunities for more holistic evaluations. We hope the results can contribute to accelerating research in this domain and, ultimately, broad adoption of immersive sketching systems.

As computing capacity increases and data grows in both size and complexity, we are capable of understanding our surroundings with increasing nuance. Visualizing this often-multivariate environmental data presents complex visual scenes to be navigated, parsed, analyzed, and communicated. We draw from both the natural world and artistic color theory to present 1) a new color system, designed to establish an affective connection between big environmental data and its original source material, 2) a tool for extracting these workable palettes from natural imagery, and 3) a selection of pre-made linear colormaps and discrete color sets drawn from natural environments.

This chapter presents an approach to designing expressive three-dimensional (3D) user interfaces that make use of handheld input devices tracked in 3D space to go beyond a simple pointing metaphor. It considers a series of three examples that build upon each other to demonstrate how sophisticated 6-degree-of-freedom, beyond-pointing, bimanual virtual reality (VR) user interfaces can be built upon this framework. Although event-based user interfaces are common in desktop computing, there are several important nuances in VR. The state machine design pattern that developers suggest for programming VR interfaces helps programmers to track and respond appropriately to changes in context. The user interface to select curves must be flexible and controlled enough that users are able to indicate their desired selection regardless of the particular texture. The chapter describes how to implement contextual constraints to improve control of 3D User Interfaces.

Cell migration and traction are essential to many biological phenomena, and one of their key features is sensitivity to substrate stiffness, which biophysical models, such as the motor-clutch model and the cell migration simulator can predict and explain. However, these models have not accounted for the finite size of adhesions, the spatial distribution of forces within adhesions. Here, we derive an expression that relates varying adhesion radius ( R) and spatial distribution of force within an adhesion (described by s) to the effective substrate stiffness ( κsub ), as a function of the Young's modulus of the substrate ( E Y ), which yields the relation, κsub=RsEY , for two-dimensional cell cultures. Experimentally, we found that a cone-shaped force distribution ( s = 1.05) can describe the observed displacements of hydrogels deformed by adherent U251 glioma cells. Also, we found that the experimentally observed adhesion radius increases linearly with the cell protrusion force, consistent with the predictions of the motor-clutch model with spatially distributed clutches. We also found that, theoretically, the influence of one protrusion on another through a continuous elastic environment is negligible. Overall, we conclude cells can potentially control their own interpretation of the mechanics of the environment by controlling adhesion size and spatial distribution of forces within an adhesion.

We present Bento Box, a virtual reality data visualization technique and bimanual 3D user interface for exploratory analysis of 4D data ensembles. Bento Box helps scientists and engineers make detailed comparative judgments about multiple time-varying data instances that make up a data ensemble (e.g., a group of 10 parameterized simulation runs). The approach is to present an organized set of complementary volume visualizations juxtaposed in a grid arrangement, where each column visualizes a single data instance and each row provides a new view of the volume from a different perspective and/or scale. A novel bimanual interface enables users to select a sub-volume of interest to create a new row on-the-fly, scrub through time, and quickly navigate through the resulting virtual “bento box.” The technique is evaluated through a real-world case study, supporting a team of medical device engineers and computational scientists using in-silico testing (supercomputer simulations) to redesign cardiac leads. The engineers confirmed hypotheses and developed new insights using a Bento Box visualization. An evaluation of the technical performance demonstrates that the proposed combination of data sampling strategies and clipped volume rendering is successful in displaying a juxtaposed visualization of fluid-structure-interaction simulation data (39 GB of raw data) at interactive VR frame rates.

Virtual reality (VR) environments are typically designed so users feel present in a single virtual world at a time, but this creates a problem for applications that require visual comparisons (e.g., forest scientists comparing multiple data-driven virtual forests). To address this, we present Worlds-in-Wedges, a 3D user interface and visualization technique that supports comparative immersive visualization by dividing the virtual space surrounding the user into volumetric wedges. There are three visual/interactive levels. The first, worlds-in-context, visualizes high-level relationships between the worlds (e.g., a map for worlds that are related in space). The second level, worlds-in-miniature, is a multi-instance implementation of the World-in-Miniature technique extended to support mutlivari-ate glyph visualization. The third level, worlds-in-wedges, displays multiple large-scale worlds in wedges that act as volumetric portals. The interface supports navigation, selection, and view manipulation. Since the techniques were inspired directly by problems facing forest scientists, the interface was evaluated by building a complete multivariate data visualization of the US Forest Service Forest Inventory and Analysis public dataset. Scientist user feedback and lessons from iterative design are reported.

Background Scapulothoracic upward rotation (UR) is an important shoulder complex motion allowing for a larger functional work space and improved glenohumeral muscle function. However, the kinematic mechanisms producing scapulothoracic UR remain unclear, limiting the understanding of normal and abnormal shoulder movements. Objective The objective of this study was to identify the coupling relationships through which sternoclavicular and acromioclavicular joint motions contribute to scapulothoracic UR. Design This was a cross-sectional observational study. Methods Sixty participants were enrolled in this study; 30 had current shoulder pain, and 30 had no history of shoulder symptoms. Shoulder complex kinematics were quantified using single-plane fluoroscopy and 2D/3D shape matching and were described as finite helical displacements for 30-degree phases of humerothoracic elevation (30 degrees-60 degrees, 60 degrees-90 degrees, and 90 degrees-120 degrees). A coupling function was derived to estimate scapulothoracic UR from its component motions of acromioclavicular UR, sternoclavicular posterior rotation, and sternoclavicular elevation as a function of acromioclavicular internal rotation. The proportional contributions of each of the component motions were also calculated and compared between phases of humerothoracic elevation and groups. Results Scapulothoracic UR displacement could be effectively predicted using the derived coupling function. During the 30- to 60-degree humerothoracic elevation phase, acromioclavicular UR accounted for 84.2% of scapulothoracic UR, whereas sternoclavicular posterior rotation and elevation each accounted for <10%. During later phases, acromioclavicular UR and sternoclavicular posterior rotation each accounted for 32% to 42%, whereas sternoclavicular elevation accounted for <11%. Limitations Error due to the tracking of sternoclavicular posterior rotation may have resulted in an underprediction of its proportional contribution and an overprediction of the proportional contribution of acromioclavicular UR. Conclusions Acromioclavicular UR and sternoclavicular posterior rotation are the predominant component motions of scapulothoracic UR. More research is needed to investigate how these coupling relationships are affected by muscle function and influenced by scapular dyskinesis.

As scientific data grow larger and more complex, an equally rich visual vocabulary is needed to fully articulate its insights. We present a series of images that are made possible by a recent technical development “Artifact-Based Rendering,” a component of our broader effort to create a methodology for scientific visualization that draws on principles of art and design . Authors

Spatial navigation of virtual environments often requires different categories of navigation actions. In this paper, we describe a mapping between different forms of navigation and multimodal interactions to accomplish the actions. We select and define three forms of navigation, identify characteristics of those forms, and describe interactions that were selected to match those characteristics. We developed these mappings within a multidisplay, semi-immersive environment assembled from commodity components, with a goal of supporting use of similar semiimmersive environments in operational settings. In designing the interaction mappings, we considered both the constraints imposed by the environment as well as likely tasks of the targeted user populations. The goal of creating the mappings is to enable fast, natural, and efficient interactions, and minimize attention shifting.

We present a direct manipulation technique that allows material scientists to interactively highlight relevant parameterized simulation instances located in dimensionally reduced spaces, enabling a user-defined understanding of a continuous parameter space. Our goals are two-fold: first, to build a user-directed intuition of dimensionally reduced data. and second, to provide a mechanism for creatively exploring parameter relationships in parameterized simulation sets, called ensembles. We start by visualizing ensemble data instances in dimensionally reduced scatter plots. To understand these abstract views, we employ user-defined virtual data instances that, through direct manipulation, search an ensemble for similar instances. Users can create multiple of these direct manipulation queries to visually annotate the spaces with sets of highlighted ensemble data instances. User-defined goals are therefore translated into custom illustrations that are projected onto the dimensionally reduced spaces. Combined forward and inverse searches of the parameter space follow naturally allowing for continuous parameter space prediction and visual query comparison in the context of an ensemble. The potential for this visualization technique is confirmed via expert user feedback for a shock physics application and synthetic model analysis.

Abstract Spatial Correlation is an interactive digital artwork that provides a new window into the process of creating freeform handcrafted virtual sculptures while standing in an immersive Cave virtual reality (VR) environment. The piece originates in the lab, where the artist’s full-body, dance-like sculpting process is recorded using a combination of spatial tracking devices and an array of nine synchronized video cameras. Later, in the gallery, these raw data are reinterpreted as part of an interactive visualization that relates the three spaces in which the sculpture exists: 1) the physical lab/studio space in which the sculpture was created, 2) the digital virtual space in which the sculpture is mathematically defined and stored, and 3) the physical gallery space in which viewers now interact with the sculpture.

We introduce a virtual reality 3D user interface (3DUI) for anatomical 2D/3D shape-matching, a challenging task that is part of medical imaging processes required by biomechanics researchers. Manual shape-matching can be thought of as a nuanced version of classic 6 degree-of-freedom docking tasks studied in the 3DUI research community. Our solution combines dynamic gain for precise translation and rotation from 6 degree-of-freedom tracker input, constraints based on both 2D and 3D data, and immersive visualization and visual feedback.

A variety of visualization techniques can be utilized to compare multiple Spatial 3D or time-varying Sliadal 3D data instances (e.g., comparing pre-versus post-treatment volumetric medical images). However, despite the fact that comparative visualization is frequently needed - scientists, engineers, and even humanists must routinely compare such data - visualization users and practitioners suffer from a lack of adequate Spatial 3D comparative visualization tools and guidelines. Here we survey the field and present a taxonomy for classifying existing and new comparison visualization techniques for such data into four fundamental approaches: Juxtaposition, Superimposition, Interchangeable, and Explicit Encoding. The results clarify the key design decisions and tradeoffs that designers must make to create an effective comparative Spatial 3D data visualization and suggest the potential of emerging hybrid approaches, ones creatively combining aspects of the four fundamental approaches. (C) 2017 Published by Elsevier Ltd.

Diffusion MRI (dMRI) reveals microstructural features of the brain white matter by quantifying the anisotropic diffusion of water molecules within axonal bundles. Yet, identifying features such as axonal orientation dispersion, density, diameter, etc., in complex white matter fiber configurations (e.g. crossings) has proved challenging. Besides optimized data acquisition and advanced biophysical models, computational procedures to fit such models to the data are critical. However, these procedures have been largely overlooked by the dMRI microstructure community and new, more versatile, approaches are needed to solve complex biophysical model fitting problems. Existing methods are limited to models assuming single fiber orientation, relevant to limited brain areas like the corpus callosum, or multiple orientations but without the ability to extract detailed microstructural features. Here, we introduce a new and versatile optimization technique (MIX), which enables microstructure imaging of crossing white matter fibers. We provide a MATLAB implementation of MIX, and demonstrate its applicability to general microstructure models in fiber crossings using synthetic as well as ex-vivo and in-vivo brain data.

We explore the role that immersive technologies, specifically virtual reality (VR) and hybrid 2D/3D sketch-based interfaces and visualizations, can play in analytical reasoning for medicine. Two case studies are described: (1) immersive explanations of medical procedures, and (2) immersive design of medical devices. Both tightly integrate 2D imagery and data with 3D interfaces, models, and visualizations. This is an approach we argue is likely to be particularly useful in medicine, where analytical tasks often involve relating 2D data (e.g., medical imaging) to 3D contexts (e.g., a patient's body). User feedback and observations from our interdisciplinary team indicate the utility of the approach for the current case studies as well as some shortcomings and areas for future research. This work contributes to a broader discussion of how hybrid 2D/3D interfaces may form an essential ingredient of future immersive analytics systems across a variety of domains.

We present Visualization-by-Sketching, a direct-manipulation user interface for designing new data visualizations. The goals are twofold: First, make the process of creating real, animated, data-driven visualizations of complex information more accessible to artists, graphic designers, and other visual experts with traditional, non-technical training. Second, support and enhance the role of human creativity in visualization design, enabling visual experimentation and workflows similar to what is possible with traditional artistic media. The approach is to conceive of visualization design as a combination of processes that are already closely linked with visual creativity: sketching, digital painting, image editing, and reacting to exemplars. Rather than studying and tweaking low-level algorithms and their parameters, designers create new visualizations by painting directly on top of a digital data canvas, sketching data glyphs, and arranging and blending together multiple layers of animated 2D graphics. This requires new algorithms and techniques to interpret painterly user input relative to data "under" the canvas, balance artistic freedom with the need to produce accurate data visualizations, and interactively explore large (e.g., terabyte-sized) multivariate datasets. Results demonstrate a variety of multivariate data visualization techniques can be rapidly recreated using the interface. More importantly, results and feedback from artists support the potential for interfaces in this style to attract new, creative users to the challenging task of designing more effective data visualizations and to help these users stay "in the creative zone" as they work.