The Conference on Visualization and Data Analysis (VDA) 2022 covers all research, development, and application aspects of data visualization and visual analytics. Since the first VDA conference was held in 1994, the annual event has grown steadily into a major venue for visualization researchers and practitioners from around the world to present their work and share their experiences. We invite you to participate by submitting your original research as a full paper, for an oral or interactive (poster) presentation, and attending VDA 2022.
Simulation is a recognized and much-appreciated tool in healthcare and education. Advances in simulation have led to the burgeoning of various technologies. In recent years, one such technological advancement has been Augmented Reality (AR). Augmented Reality simulations have been implemented in healthcare on various fronts with the help of a plethora of devices including cellphones, tablets, and wearable AR headsets. AR headsets offer the most immersive experience of the AR simulation as they are head-mounted and offer a stereoscopic view of the superimposed 3D models through the attached goggles overlaid on real-world surfaces. To this effect, it is important to understand the performance capabilities of the AR headsets based on workload. In this paper, our objective is to compare the performances of two prominent AR headsets of today, the Microsoft Hololens and the Magic Leap One. We use surgical AR software that allows the surgeons to show internal structures, such as the rib cage, to assist in the surgery as a reference application to obtain performance numbers for those AR devices. Based on our research, there are no performance measurements and recommendations available for these types of devices in general yet.
When conducting Coastal Water Navigation, a ship's Navigating Officer (NavO) has multiple sources of data to consider. To obtain the information required to safely manoeuvre the ship, they make use of specialized equipment. The time spent interacting with the equipment is a risk, as it prevents them from visually monitoring the ever-changing maritime environment. Data visualization through Augmented Reality (AR) offers a way to obtain the information while maintaining a proper and effective lookout. Additionally, our research suggests that the information can be presented in new ways. We created a simulator that allows testing and evaluation of AR Navigation Aids (ARNAs). These visualizations were evaluated by subject matter experts through a user study. The user study suggests that ARNAs can improve maritime safety and assist in the conduct of navigation.
Reconstructing 3D models from large, dense point clouds is critical to enable Virtual Reality (VR) as a platform for entertainment, education, and heritage preservation. Existing 3D reconstruction systems inevitably make trade-offs between three conflicting goals: the efficiency of reconstruction (e.g., time and memory requirements), the visual quality of the constructed scene, and the rendering speed on the VR device. This paper proposes a reconstruction system that simultaneously meets all three goals. The key idea is to avoid the resource-demanding process of reconstructing a high-polygon mesh altogether. Instead, we propose to directly transfer details from the original point cloud to a low polygon mesh, which significantly reduces the reconstruction time and cost, preserves the scene details, and enables real-time rendering on mobile VR devices. While our technique is general, we demonstrate it in reconstructing cultural heritage sites. We for the first time digitally reconstruct the Elmina Castle, a UNESCO world heritage site at Ghana, from billions of laser-scanned points. The reconstruction process executes on low-end desktop systems without requiring high processing power, making it accessible to the broad community. The reconstructed scenes render on Oculus Go in 60 FPS, providing a real-time VR experience with high visual quality.
We present CoursePathVis, a visual analytics tool for exploring and analyzing students’ progress through a college curriculum using a Sankey diagram. Focusing on four student cohorts in a department, we group students in multiple ways (by their AP courses, term courses, and a user-specified funnel course) to comprehensively understand the data. CoursePathVis helps us identify patterns or outliers that affect student success with these flexible grouping techniques and the funnel-augmented Sankey diagram. Three stakeholders from the same department formulate design requirements and provide an ad-hoc evaluation.
3D object clouds, first introduced by Hong and Brooks, visualize the pairwise similarity between a set of objects and a central object of interest. This similarity is used to determine the position of each object within the cloud. However, this does not capture the semantic relationship of all the objects and the lack of consistency may reduce the expectation of finding an object when performing visual search. To generate a semantic 3D object cloud, we define and subsequently minimize an energy function that captures the pairwise similarity amongst all objects within the cloud. The energy is minimized using several statistical machine learning techniques and we show that the generated layouts from such techniques outperform those of other algorithms on a variety of metrics for evaluating layouts.
This paper presents Nirmaan, an open-source web-based tool for generating synthetic datasets of multiclass blobs for use in research related to scatterplots. We demonstrate how to use Nirmaan to generate datasets in the context of a user study where users must determine the centers of each class, but this tool can be used to generate datasets for other scatterplot tasks as well.
Smooth topological surfaces embedded in 4D create complex internal structures in their projected 3D figures. Often these 3D figures twist, turn, and fold back on themselves, leaving important properties behind the surface sheets. Triangle meshes are not well suited for illustrating such internal structures and their topological features. In this paper, we propose a new approach to visualize these internal structures by slicing the 4D surfaces in our dimensions and revealing the underlying 4D structures using their cross-sectional diagrams. We think of a 4D-embedded surface as a collection of 3D curves stacked and evolved in time, very much like a 3D movie in a time-elapse form; and our new approach is to translate a surface in 4-space into such a movie --- a sequence of time-lapse frames where successive terms in the sequence differ at most by a critical change. The visualization interface presented in this paper allows us to interactively define the longitudinal axis, and the automatic algorithms can partition the 4D surface into parallel slices and expose its internal structure by generating a time-lapse movie consisting of topologically meaningful cross-sectional diagrams from the representative slices. We have extracted movies from a range of known 4D mathematical surfaces with our approach. The results of the usability study show that the proposed slicing interface allows a mathematically true user experience with surfaces in four dimensions.