Browsing by Author "Yang, Yalong"
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- Andromeda in Education: Studies on Student Collaboration and Insight Generation with Interactive Dimensionality ReductionTaylor, Mia Rachel (Virginia Tech, 2022-10-04)Andromeda is an interactive visualization tool that projects high-dimensional data into a scatterplot-like visualization using Weighted Multidimensional Scaling (WMDS). The visualization can be explored through surface-level interaction (viewing data values), parametric interaction (altering underlying parameterizations), and observation-level interaction (directly interacting with projected points). This thesis presents analyses on the collaborative utility of Andromeda in a middle school class and the insights college-level students generate when using Andromeda. The first study discusses how a middle school class collaboratively used Andromeda to explore and compare their engineering designs. The students analyzed their designs, represented as high-dimensional data, as a class. This study shows promise for introducing collaborative data analysis to middle school students in conjunction with other technical concepts such as the engineering design process. Participants in the study on college-level students were given a version of Andromeda, with access to different interactions, and were asked to generate insights on a dataset. By applying a novel visualization evaluation methodology on students' natural language insights, the results of this study indicate that students use different vocabulary supported by the interactions available to them, but not equally. The implications, as well as limitations, of these two studies are further discussed.
- Evaluating Navigation and Comparison Performance of Computational Notebooks on Desktop and in Virtual RealityIn, Sungwon; Krokos, Eric; Whitley, Kirsten; North, Christopher L.; Yang, Yalong (ACM, 2024-05-11)The computational notebook serves as a versatile tool for data analysis. However, its conventional user interface falls short of keeping pace with the ever-growing data-related tasks, signaling the need for novel approaches. With the rapid development of interaction techniques and computing environments, there is a growing interest in integrating emerging technologies in data-driven workflows. Virtual reality, in particular, has demonstrated its potential in interactive data visualizations. In this work, we aimed to experiment with adapting computational notebooks into VR and verify the potential benefits VR can bring. We focus on the navigation and comparison aspects as they are primitive components in analysts’ workflow. To further improve comparison, we have designed and implemented a Branching&Merging functionality. We tested computational notebooks on the desktop and in VR, both with and without the added Branching&Merging capability. We found VR significantly facilitated navigation compared to desktop, and the ability to create branches enhanced comparison.
- Exploring the Impacts of Aspect Ratios on Visual Perception in ScatterplotsShen, Zhen (Virginia Tech, 2023-06-23)This thesis investigates the effect of aspect ratio on visual perception in scatterplots. Four tasks explored how the aspect ratio affects participants' perception of distance, amount, and correlation in scatterplots. The results showed that square aspect ratio scatterplots are more suitable for detecting length and number, while rectangular aspect ratio scatterplots are better for detecting correlation. In addition, the JND (Just Noticeable Difference) was used in evaluating the visual perception of scatterplots in this experiment. The findings of this study have important implications for the design of scatterplots in data visualization, as well as for future research on visual perception in data visualization.
- Glanceable AR: Towards a Pervasive and Always-On Augmented Reality FutureLu, Feiyu (Virginia Tech, 2023-07-06)Augmented reality head-worn displays (AR HWDs) have the potential to assist personal computing and the acquisition of everyday information. With advancements in hardware and tracking, these devices are becoming increasingly lightweight and powerful. They could eventually have the same form factor as normal pairs of eyeglasses, be worn all-day, overlaying information pervasively on top of the real-world anywhere and anytime to continuously assist people’s tasks. However, unlike traditional mobile devices, AR HWDs are worn on the head and always visible. If designed without care, the displayed virtual information could also be distracting, overwhelming, and take away the user’s attention from important real- world tasks. In this dissertation, we research methods for appropriate information displays and interactions with future all-day AR HWDs by seeking answers to four questions: (1) how to mitigate distractions of AR content to the users; (2) how to prevent AR content from occluding the real-world environment; (3) how to support scalable on-the-go access to AR content; and (4) how everyday users perceive using AR systems for daily information acquisition tasks. Our work builds upon a theory we developed called Glanceable AR, in which digital information is displayed outside the central field of view of the AR display to minimize distractions, but can be accessed through a quick glance. Through five projects covering seven studies, this work provides theoretical and empirical knowledge to prepare us for a pervasive yet unobtrusive everyday AR future, in which the overlaid AR information is easily accessible, non-invasive, responsive, and supportive.
- Immersive Analytics Spaces and SurfacesSerrano, Marcos; Satriadi, Kadek Ananta; Yang, Yalong; Ens, Barrett; Prouzeau, Arnaud; Zollmann, Stefanie (ACM, 2022-11-20)Immersive Analytics has now fully emerged as a research topic in the Visualisation and Human-Computer Interaction research communities. While evidence of its benefits has been accumulating, we have still attained only a basic understanding of the extent to which they can support human sensemaking, This workshop aims to define a roadmap for new directions in leveraging the benefits of spatial interaction to support sensemaking. In particular the main goal of this workshop will be to focus on understanding the benefits and applications of immersive interactive spaces and surfaces (e.g. body, walls, smartphones or other interactive surfaces such as tabletops) for enhancing human sensemaking.
- Interpreting Dimension Reductions through Gradient VisualizationHamal, Sahil (Virginia Tech, 2023-05-26)Dimension reduction (DRs) are significant in data analysis to reduce the complexity of high dimensional data while preserving information to the greatest extent. However, the complex processes involved in DRs attribute to their inability to reason the relationship between the projection and the original data features (dimensions). "Why points are clustered?" and "What feature/s caused the points to scatter?" are some of the common questions. As a solution, we use gradients of the projection to generate visual explanations of the DRs. Utilizing these gradients, we show the point-wise sensitivities of the projection with respect to the original data features to explain the reasoning of DR. The combination of the gra- dients with various visualization techniques contribute to the exploration of the impact of dimensions on the projection. To overcome the curse of dimensionality, we propose inter- active techniques that facilitate the combination and comparison of features impact on the projection through gradients. Encapsulating the gradients and the visualization techniques, we present a web-based framework that facilitates an overview of impacts of all features and allows users to selectively explore notable features.
- Investigating Asymmetric Collaboration and Interaction in Immersive EnvironmentsEnriquez, Daniel (Virginia Tech, 2024-01-23)With the commercialization of virtual/augmented reality (VR/AR) devices, there is an increasing interest in combining immersive and non-immersive devices (e.g., desktop computers, mobile devices) for asymmetric collaborations. While such asymmetric settings have been examined in social platforms, questions surrounding collaborative view dimensionalities in data-driven decision-making and interaction from non-immersive devices remain under-explored. A crucial inquiry arises: although presenting a consistent 3D virtual world on both immersive and non-immersive platforms has been a common practice in social applications, does the same guideline apply to lay out data? Or should data placement be optimized locally according to each device's display capacity? To this effect, a user study was conducted to provide empirical insights into the user experience of asymmetric collaboration in data-driven decision-making. The user study tested practical dimensionality combinations between PC and VR, resulting in three conditions: PC2D+VR2D, PC2D+VR3D, and PC3D+VR3D. The results revealed a preference for PC2D+VR3D, and PC2D+VR2D led to the quickest task completion. Similarly, mobile devices have become an inclusive alternative to head-worn displays in virtual reality (VR) environments, enhancing accessibility and allowing cross-device collaboration. Object manipulation techniques in mobile Augmented Reality (AR) have been typically evaluated in table-top scale and we lack an understanding of how these techniques perform in room-scale environments. Two studies were conducted to analyze object translation tasks, each with 30 participants, to investigate how different techniques impact usability and performance for room-scale mobile VR object translations. Results indicated that the Joystick technique, which allowed translation in relation to the user's perspective, was the fastest and most preferred, without difference in precision. These findings provide insight for designing collaborative, asymmetric VR environments.
- Multi-Focus Querying of the Human Genome using Virtual Reality and DesktopReiske, Gunnar William (Virginia Tech, 2023-07-25)The human genome is incredibly information dense, consisting of approximately 25,000 protein-coding genes contained within 24 unique chromosomes. An aspect of the genome that is critically important is maintaining spatial context which assists in understanding gene interactions and relationships. Existing methods of genome visualization that utilize spatial awareness are inefficient and prone to limitations in gene information and spatial context. The solution proposed in this thesis was the development and evaluation of alternative methods of genome visualization and exploration using virtual reality and desktop. To determine the optimal location of gene information within virtual reality and the influence of virtual reality, three interaction methods were implemented that interact with the ideograms. Multi-focus was applied to the ideogram interaction design to assist in visualizing multiple locations within the genome without sacrificing gene information detail or spatial awareness of the user. Two interaction methods were developed in virtual reality to determine if gene information is better suited embedded within the chromosome ideogram or separate from the ideogram. The final interaction method was implemented as a desktop application to evaluate if virtual reality provided an advantage. Results from the user study conducted determined that the use of virtual reality gave users a higher degree of confidence when navigating the chromosome ideograms and was preferred over desktop. In addition, depending on the type of task, the placement of gene information within the visualization had a notable impact on the ability of a user to work the task.
- The Pattern is in the Details: An Evaluation of Interaction Techniques for Locating, Searching, and Contextualizing Details in Multivariate Matrix VisualizationsYang, Yalong; Xia, Wenyu; Lekschas, Fritz; Nobre, Carolina; Krüger, Robert; Pfister, Hanspeter (ACM, 2022-04-27)Matrix visualizations are widely used to display large-scale network, tabular, set, or sequential data. They typically only encode a single value per cell, e.g., through color. However, this can greatly limit the visualizations’ utility when exploring multivariate data, where each cell represents a data point with multiple values (referred to as details). Three well-established interaction approaches can be applicable in multivariate matrix visualizations (or MMV): focus+context, pan&zoom, and overview+detail. However, there is little empirical knowledge of how these approaches compare in exploring MMV. We report on two studies comparing them for locating, searching, and contextualizing details in MMV. We first compared four focus+context techniques and found that the fisheye lens overall outperformed the others. We then compared the fisheye lens, to pan&zoom and overview+detail. We found that pan&zoom was faster in locating and searching details, and as good as overview+detail in contextualizing details.