UMD Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/3
New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a given thesis/dissertation in DRUM.
More information is available at Theses and Dissertations at University of Maryland Libraries.
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Item Designing Human-Centered AI Tools with Interactive Visualization(2024) Hoque, Md Naimul; Kraus, Kari; Information Studies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Human-centered AI (HCAI), rather than replacing the human, puts the user in the driver's seat of so-called human-centered AI-infused tools (HCAI tools): interactive software tools that amplify, augment, empower, and enhance human performance using AI models. In this dissertation, I discuss how interactive visualization can be a key enabling technology for creating such human-centered AI tools. Visualization has already been shown to be a fundamental component in explainable AI models, and coupling this with data-driven, semantic, and unified interaction feedback loops will enable a human-centered approach for bridging AI models and human users. To validate this approach, I at first interviewed HCI, AI, and Visualization experts to define the characteristics of HCAI tools. I then discuss the design and development process of four HCAI tools powered by visualization. I conclude by outlining the design guidelines learned from the design process of the tools and research directions for designing future HCAI tools.Item SIMULATION, REPRESENTATION, AND AUTOMATION: HUMAN-CENTERED ARTIFICIAL INTELLIGENCE FOR AUGMENTING VISUALIZATION DESIGN(2024) Shin, Sungbok; Elmqvist, Niklas; Computer Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Data visualization is a powerful strategy for using graphics to represent data for effective communication and analysis. Unfortunately, creating effective data visualizations is a challenge for both novice and expert design users. The task often involves an iterative process of trial and error, which by its nature, is time-consuming. Designers frequently seek feedback to ensure their visualizations convey the intended message clearly to their target audience. However, obtaining feedback from peers can be challenging, and alternatives like user studies or crowdsourcing is costly and time-consuming. This suggests the potential for a tool that can provide design feedback for visualizations. To that end, I create a virtual, human vision-inspired system that looks into the visualization design and provides feedback on it using various AI techniques. The goal is not to replicate an exact version of a human eye. Instead, my work aims to develop a practical and effective system that delivers design feedback to visualization designers, utilizing advanced AI techniques, such as deep neural networks (DNNs) and large language models (LLMs). My thesis includes three distinct works, each aimed at developing a virtual system inspired by human vision using AI techniques. Specifically, these works focus on simulation, representation, and automation, collectively progressing toward the aim. First, I develop a methodology to simulate human perception in machines through a virtual eye tracker named A SCANNER DEEPLY. This involves gathering eye gaze data from chart images and training them using a DNN. Second, I focus on effectively and pragmatically representing a virtual human vision-inspired system by creating PERCEPTUAL PAT, which includes a suite of perceptually-based filters. Third, I automate the feedback generation process with VISUALIZATIONARY, leveraging large language models to enhance the automation. I report on challenges and lessons learned about the key components and design considerations that help visualization designers. Finally, I end the dissertation by discussing future research directions for using AI for augmenting visualization design process.Item The Role of 3D Spatiotemporal Telemetry Analysis in Combat Flight Simulation(2024) Mane, Sourabh Vijaykumar; Elmqvist, Niklas Dr; Library & Information Services; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Analyzing 3D telemetry data collected from competitive video games on the internet can support players in improving performance as well as spectators in viewing data-driven narratives of the gameplay. In this thesis, we conduct an in-depth qualitative study on the use of telemetry analysis by embedding over several weeks in a virtual F-14A Tomcat squadron in the multiplayer combat flight simulator DCS World (DCS) (2008). Based on formative interviews with DCS pilots, we design a web-based game analytics framework for rendering 3D telemetry from the flight simulator in a live 3D player, incorporating many of the data displays and visualizations requested by the participants. We then evaluate the framework with real mission data from several air-to-air engagements involving the virtual squadron. Our findings highlight the key role of 3D telemetry playback in competitive multiplayer gaming.Item Immersive Visual Analytics of Wi-Fi Signal Propagation and Network Health(2023) Rowden, Alexander R; Varsnhney, Amitabh; Computer Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)e are immersed in waves of information. This information is typically transmitted as radio waves in many protocols and frequencies, such as WiFi, Bluetooth, and Near-Field Communications (NFC). It carries vital information such as health data, private messages, and financial records. There is a critical need for systematic and comprehensive visualization techniques to facilitate seamless, resilient, and secure transmission of these signals. Traditional visualization techniques are not enough because of the scale of these datasets. In this dissertation, we present three novel contributions that leverage advances in volume rendering and virtual reality (VR): (a) an outdoor volume-rendering visualization system that facilitates large-scale visualization of radio waves over a college campus through real-time programmable customization for analysis purposes, (b) an indoor, building-scale visualization system that enables data to be collected and analyzed without occluding the user's view of the environment, and (c) a systematic user study with 32 participants which shows that users perform analysis tasks well with our novel visualizations. In our outdoor system, we present the Programmable Transfer Function. Programmable Transfer Functions offer the user a way to replace the traditional transfer function paradigm with a more flexible and less memory-demanding alternative. Our work on indoor WiFi visualization is called WaveRider. WaveRider is our contribution to indoor-modeled WiFi visualization using a virtual environment. WaveRider was designed with the help of expert signal engineers we interviewed to determine the needs of the visualization and who we used to evaluate the application. These works provide a solid starting point for signal visualization as our networks transition to more complex models. Indoor and outdoor visualizations are not the only dichotomy in the realm of signal visualization. We are also interested in visualizations of modeled data compared to visualization of data samples. We have also explored designs for multiple sample-based visualizations and conducted a formal evaluation where we compare these to our previous model-based approach. This analysis has shown that visualizing the data without modeling improves user confidence in their analyses. In the future, we hope to explore how these sample-based methods allow more routers to be visualized at once.Item Data-driven Storytelling in Dynamic Graph Comics through Hierarchical Clustering(2023) Kannan, Abhinav; Elmqvist, Niklas; Computer Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)In this work, we propose a tool to generate a dynamic graph comic given dense, time-series edge-vertex data. Prior research has demonstrated the effectiveness of node-link diagrams as an expressive medium for storytelling with dynamic graphs, and in this work, we develop an interface that generates a customizable comic strip consisting of node-link diagram snapshots. We use hierarchical aggregation to cluster and pile graphs based on the number of frames a user may wish to see, with each frame depicting a snapshot in time. We validate the interface with real-world datasets to understand temporal changes in a graph network, and evaluate the interface against an expert audience. Finally, we propose a path forward for improvement of dynamic graph comics as a storytelling medium.Item Enabling Collaborative Visual Analysis across Heterogeneous Devices(2019) Badam, Sriram Karthik; Elmqvist, Niklas; Computer Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)We are surrounded by novel device technologies emerging at an unprecedented pace. These devices are heterogeneous in nature: in large and small sizes with many input and sensing mechanisms. When many such devices are used by multiple users with a shared goal, they form a heterogeneous device ecosystem. A device ecosystem has great potential in data science to act as a natural medium for multiple analysts to make sense of data using visualization. It is essential as today's big data problems require more than a single mind or a single machine to solve them. Towards this vision, I introduce the concept of collaborative, cross-device visual analytics (C2-VA) and outline a reference model to develop user interfaces for C2-VA. This dissertation covers interaction models, coordination techniques, and software platforms to enable full stack support for C2-VA. Firstly, we connected devices to form an ecosystem using software primitives introduced in the early frameworks from this dissertation. To work in a device ecosystem, we designed multi-user interaction for visual analysis in front of large displays by finding a balance between proxemics and mid-air gestures. Extending these techniques, we considered the roles of different devices–large and small–to present a conceptual framework for utilizing multiple devices for visual analytics. When applying this framework, findings from a user study showcase flexibility in the analytic workflow and potential for generation of complex insights in device ecosystems. Beyond this, we supported coordination between multiple users in a device ecosystem by depicting the presence, attention, and data coverage of each analyst within a group. Building on these parts of the C2-VA stack, the culmination of this dissertation is a platform called Vistrates. This platform introduces a component model for modular creation of user interfaces that work across multiple devices and users. A component is an analytical primitive–a data processing method, a visualization, or an interaction technique–that is reusable, composable, and extensible. Together, components can support a complex analytical activity. On top of the component model, the support for collaboration and device ecosystems comes for granted in Vistrates. Overall, this enables the exploration of new research ideas within C2-VA.Item AN ANALYSIS OF EN ROUTE AIR TRAFFIC MANAGEMENT INITIATIVES(2018) Sanz, Santiago Javier; Lovell, David J; Systems Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Ensuring the safety and efficiency of flights is a large mission the FAA is tasked with. Since the early 2000’s the FAA has been working on implementing their next generation air transportation system that aims at modernizing the way flights are managed. Some of the changes brought on by the implementation of next gen include additions and modifications to the time management initiatives (TMIs) that the FAA uses for managing flights. For that reason, the FAA is interested in how these TMIs compare with each other. This document focuses on comparing different TMIs by conducting statistical analysis on the available data and examining the results.Item E XPLORING DIFFERENCES IN MULTIVARIATE DATASETS USING HIERARCHIES AN INTERACTIVE INFORMATION VISUALIZATION APPROACH(2013) Guerra Gómez, John Alexis; Shneiderman, Ben; Plaisant, Catherine; Computer Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Hierarchies are a useful way of representing data. The parent-child relationships they define facilitate the analysis of a dataset by breaking it down into its component parts. Representing data as hierarchies can also be used to track changes to a dataset over time or between versions. For example, analysts can use hierarchies to uncover changes in the US Federal Budget in the last twenty years, by grouping accounts by Agencies and Bureaus. Similarly, a company manager can analyze changes to their product sales due to the holiday season by breaking them up by markets and product categories. Exploring differences in such trees could help them understand changes in the data. However, comparing hierarchies is a difficult task, even when comparing two trees with a small number of nodes. To address this, information visualization techniques were used to support data comparison tasks using hierarchies. After evaluating my techniques with domain experts on real world problems, I identified and addressed two main research topics: Abstract This dissertation first tackled the problem of comparing two versions of a tree by using two types of change, while most of the significant work on this topic has focused only on changes in node values or changes in topology. TreeVersity (http://hcil.cs.umd.edu/treeversity) is a comparison tool that allows users to explore changes between two versions of a tree by tracking node value differences, and newly created or removed nodes. Domain experts using TreeVersity were excited to discover differences in the trees, but expressed a desire to explore the evolution of a dataset over time. To that end, they suggested applying TreeVersity comparison capabilities to datasets that were non inherently hierarchical. Abstract Following users' feedback, the problem of exploring changes over time in datasets that can be categorized as trees was addressed next. TreeVersity2 (http://treeversity.cattlab.umd.edu is a web-based data comparison tool that allows users to explore a tree that changes over time and of datasets that are not inherently hierarchical, by categorizing them by their attributes. TreeVersity2 also helps users navigate the sometimes large amounts of differences between versions of a tree using an interactive textual reporting tool. Abstract My research has resulted in three main contributions: First, the introduction of the Bullet, a visualization glyph to represent four characteristics of change (as described in Section 1.2) in tree nodes, and the implementation of the Bullet in TreeVersity. Second, the creation of the StemView, a tree visualization technique that represents five characteristics of change in all the nodes of a tree (not just the leaves), and the implementation of the StemView in TreeVersity2. Furthermore, my research resulted in the development of the reporting tool, another feature of TreeVersity2, which helps users navigate outstanding changes in the tree with textual representations and coordinated interactions. Third, the development of 13 case studies with domain experts on real world comparison problems. The case studies have validated the utility and flexibility of my approaches. Finally, my research opens possibilities for future research on comparing hierarchical structures.