Feature Driven Combination of Animated Vector Field Visualizations

Animated visualizations are one of the methods for finding and understanding complex structures of time-dependent vector fields. Many visualization designs can be used to this end, such as streamlines, vector glyphs, and image-based techniques. While all such designs can depict any vector field, their effectiveness in highlighting particular field aspects has not been fully explored. To fill this gap, we compare three animated vector field visualization techniques, OLIC, IBFV, and particles, for a critical point detection-and-classification task through a user study. Our results show that the effectiveness of the studied techniques depends on the nature of the critical points. We use these results to design a new flow visualization technique that combines all studied techniques in a single view by locally using the most effective technique for the patterns present in the flow data at that location. A second user study shows that our technique is more efficient and less error prone than the three other techniques used individually for the critical point detection task.     

Taxonomy for visualizing location-based information

Location-based data is digital information that has a real-world location. Location-based data can be used for many purposes, such as providing additional information on real-world objects or helping a user in a specific task. Access to such data can be provided in many ways, for example, with augmented reality (AR) systems. AR techniques can help its user in various tasks and the AR data can be presented to the user in various ways, depending on the task at hand. The different visualizations that can be used are heavily dependent on the hardware platform and, thus, all technologies are not suitable for every situation. This paper studies two factors that affect the visualization of location-based data. The two factors are the environment model they use, ranging from three dimensions (3D) to no dimensions (0D) at all; and the viewpoint, whether it is a first-person or a third-person view. As a result, we define a taxonomy for visualizing location-based data, where each model–view (MV) combination is referred to using its MV number. We also present numerous case studies with different MV values.     

A Survey on Multimodal Medical Data Visualization

Multi‐modal data of the complex human anatomy contain a wealth of information. To visualize and explore such data, techniques for emphasizing important structures and controlling visibility are essential. Such fused overview visualizations guide physicians to suspicious regions to be analysed in detail, e.g. with slice‐based viewing. We give an overview of state of the art in multi‐modal medical data visualization techniques. Multi‐modal medical data consist of multiple scans of the same subject using various acquisition methods, often combining multiple complimentary types of information. Three‐dimensional visualization techniques for multi‐modal medical data can be used in diagnosis, treatment planning, doctor–patient communication as well as interdisciplinary communication. Over the years, multiple techniques have been developed in order to cope with the various associated challenges and present the relevant information from multiple sources in an insightful way. We present an overview of these techniques and analyse the specific challenges that arise in multi‐modal data visualization and how recent works aimed to solve these, often using smart visibility techniques. We provide a taxonomy of these multi‐modal visualization applications based on the modalities used and the visualization techniques employed. Additionally, we identify unsolved problems as potential future research directions.     

Comprehensible Visualization for Augmented Reality

This article presents interactive visualizations to support the comprehension of spatial relationships between virtual and real world objects for augmented reality (AR) applications. To enhance the clarity of such relationships we discuss visualization techniques and their suitability for AR. We apply them on different AR applications with different goals, e.g. in X-Ray vision or in applications which draw a user's attention to an object of interest. We demonstrate how Focus and Context (F+C) visualizations are used to affect the user's perception of hidden or nearby objects by presenting contextual information in the area of augmentation. We discuss the organization and the possible sources of data for visualizations in augmented reality and present cascaded and multi level F+C visualizations to address complex, cluttered scenes that are inevitable in real environments. This article also shows filters and tools to interactively control the amount of augmentation. It compares the impact of real world context preserving to a pure virtual and uniform enhancement of these structures for augmentations of real world imagery. Finally this paper discusses the stylization of sparse object representations for AR to improve x-ray vision.     

Mobile augmented reality for environmental monitoring

In response to dramatic changes in the environment, and supported by advances in wireless networking, pervasive sensor networks have become a common tool for environmental monitoring. However, tools for on-site visualization and interactive exploration of environmental data are still inadequate for domain experts. Current solutions are generally limited to tabular data, basic 2D plots, or standard 2D GIS tools designed for the desktop and not adapted to mobile use. In this paper, we introduce a novel augmented reality platform for 3D mobile visualization of environmental data. Following a user-centered design approach, we analyze processes, tasks, and requirements of on-site visualization tools for environmental experts. We present our multilayer infrastructure and the mobile augmented reality platform that leverages visualization of georeferenced sensor measurement and simulation data in a seamless integrated view of the environment.     

Teru Teru Bōzu: Defensive Raincloud Plots

Univariate visualizations like histograms, rug plots, or box plots provide concise visual summaries of distributions. However, each individual visualization may fail to robustly distinguish important features of a distribution, or provide sufficient information for all of the relevant tasks involved in summarizing univariate data. One solution is to juxtapose or superimpose multiple univariate visualizations in the same chart, as in Allen et al.'s [APW^*19] “raincloud plots.” In this paper I examine the design space of raincloud plots, and, through a series of simulation studies, explore designs where the component visualizations mutually “defend” against situations where important distribution features are missed or trivial features are given undue prominence. I suggest a class of “defensive” raincloud plot designs that provide good mutual coverage for surfacing distributional features of interest.     

Visualization of Eye Tracking Data: A Taxonomy and Survey

This survey provides an introduction into eye tracking visualization with an overview of existing techniques. Eye tracking is important for evaluating user behaviour. Analysing eye tracking data is typically done quantitatively, applying statistical methods. However, in recent years, researchers have been increasingly using qualitative and exploratory analysis methods based on visualization techniques. For this state‐of‐the‐art report, we investigated about 110 research papers presenting visualization techniques for eye tracking data. We classified these visualization techniques and identified two main categories: point‐based methods and methods based on areas of interest. Additionally, we conducted an expert review asking leading eye tracking experts how they apply visualization techniques in their analysis of eye tracking data. Based on the experts' feedback, we identified challenges that have to be tackled in the future so that visualizations will become even more widely applied in eye tracking research.     

Mobile augmented reality based context-aware library management system

Mobile augmented reality has gained popularity in recent years due to the technological advances of smartphones and other mobile devices. One particular area in which mobile augmented reality is being used is library management. However, current mobile augmented reality solutions in this domain are lacking in context-awareness. It has been suggested in the literature that agent programming may be suitable at overcoming this problem, but little research has been conducted using modern mobile augmented reality applications with agents. This paper aims to bridge this gap through the development of an agent-based, mobile augmented reality prototype, titled Libagent. Libagent was subjected to five experiments to determine its suitability, efficiency, and accuracy for library management. The results of these experiments indicate that agent-based mobile augmented reality is a promising tool for context-aware library management.     

Stardust: Accessible and Transparent GPU Support for Information Visualization Rendering

Web‐based visualization libraries are in wide use, but performance bottlenecks occur when rendering, and especially animating, a large number of graphical marks. While GPU‐based rendering can drastically improve performance, that paradigm has a steep learning curve, usually requiring expertise in the computer graphics pipeline and shader programming. In addition, the recent growth of virtual and augmented reality poses a challenge for supporting multiple display environments beyond regular canvases, such as a Head Mounted Display (HMD) and Cave Automatic Virtual Environment (CAVE). In this paper, we introduce a new web‐based visualization library called Stardust, which provides a familiar API while leveraging GPU's processing power. Stardust also enables developers to create both 2D and 3D visualizations for diverse display environments using a uniform API. To demonstrate Stardust's expressiveness and portability, we present five example visualizations and a coding playground for four display environments. We also evaluate its performance by comparing it against the standard HTML5 Canvas, D3, and Vega.     

Archeoguide: an augmented reality guide for archaeological sites

The paper discusses Archeoguide which offers personalized augmented reality tours of archaeological sites. It uses outdoor tracking, mobile computing, 3D visualization and augmented reality techniques to enhance information presentation, reconstruct ruined sites, and simulate ancient life     

Provision of awareness of learners’ emotions through visualizations in a computer interaction-based environment

One of the challenges of intelligent systems for education is to use low-level data collected in computer environments in the form of events or interactions to infer information with high-level significance using artificial intelligence techniques, and present it through visualizations in a meaningful and effective way. Among this information, emotional data is gaining track in by instructors in their educational activities. Many benefits can be obtained if an intelligent systems can bring teachers with knowledge about their learner’s emotions, learning causes, and learning relationships with emotions. In this paper, we propose and justify a set of visualizations for an intelligent system to provide awareness about the emotions of the learners to the instructor based on the learners’ interactions in their computers. We apply these learner’s affective visualizations in a programming course at University level with more than 300 students, and analyze and interpret the student’s emotional results in connection with the learning process.     

Interactive visualization of large state spaces

Insight into the global structure of a state space is of great help in the analysis of the underlying process. We advocate the use of visualization for this purpose and present a method to visualize the structure of very large state spaces with millions of nodes. The method uses a clustering based on an equivalence relation to obtain a simplified representation, which is used as a backbone for the display of the entire state space. With this visualization we are able to answer questions about the global structure of a state space that cannot easily be answered by conventional methods. We show this by presenting a number of visualizations of real-world protocols .     

Visualization and Analysis of Clickstream Data of Online Stores for Understanding Web Merchandising

Clickstreams are visitors' paths through a Web site. Analysis of clickstreams shows how a Web site is navigated and used by its visitors. Clickstream data of online stores contains information useful for understanding the effectiveness of marketing and merchandising efforts, such as how customers find the store, what products they see, and what products they purchase. In this paper, we present an interactive visualization system that provides users with greater abilities to interpret and explore clickstream data of online stores. This system visualizes the effectiveness of Web merchandising from two different points of view by using two different visualization techniques: visualization of sessions by using parallel coordinates and visualization of product performance by using starfield graphs. Furthermore, this system provides facilities for zooming, filtering, color-coding, dynamic querying and data sampling. It also provides summary information along with visualizations, and by maintaining a connection between visualizations and the source database, it dynamically updates the summary information. To demonstrate how the presented visualization system provides capabilities for examining online store clickstreams, we present a series of parallel coordinates and starfield visualizations that display clickstream data from an operating online retail store. A framework for understanding Web merchandising is briefly explained. A set of metrics referred to as micro-conversion rates, which are defined for Web merchandising analysis in our previous work (Lee et al., Electronic Markets, 2000), is also explained and used for the visualizations of online store effectiveness.     

Data Stories of Water: Studying the Communicative Role of Data Visualizations within Long-form Journalism

We present a methodology for making sense of the communicative role of data visualizations in journalistic storytelling and share findings from surveying water-related data stories. Data stories are a genre of long-form journalism that integrate text, data visualization, and other visual expressions (e.g., photographs, illustrations, videos) for the purpose of data-driven storytelling. In the last decade, a considerable number of data stories about a wide range of topics have been published worldwide. Authors use a variety of techniques to make complex phenomena comprehensible and use visualizations as communicative devices that shape the understanding of a given topic. Despite the popularity of data stories, we, as scholars, still lack a methodological framework for assessing the communicative role of visualizations in data stories. To this extent, we draw from data journalism, visual culture, and multimodality studies to propose an interpretative framework in six stages. The process begins with the analysis of content blocks and framing elements and ends with the identification of dimensions, patterns, and relationships between textual and visual elements. The framework is put to the test by analyzing 17 data stories about water-related issues. Our observations from the survey illustrate how data visualizations can shape the framing of complex topics.     

Multi-view visualizations for emergency communities of volunteers

Information and communication technologies might empower emergency communities of volunteers by assisting community participation and improving their capacity to respond to unexpected events. However, designing technology for such purpose places unique visualization challenges that go beyond the current state of research on public participation tools and related technologies. Empowering these communities requires developing representations that enable collaborative reflection, promote mutual visibility of volunteers’ efforts and sustain a shared view of the community. Similarly, it is necessary to envision visualizations that facilitate sense making of large, simultaneous and distributed pieces of heterogeneous information with different levels of credibility and priority. Accordingly, this paper identifies and characterizes these challenges to propose a multi-view and multi-abstraction-level visualization approach for emergency communities of volunteers. In particular, it combines time-oriented visualizations, space-filling visualization techniques, interaction mechanisms and coordinated maps to support community participation as well as collaborative and individual sense making. The application of these visualization techniques is discussed through the development of a set of design prototypes.     

Augmented reality navigation systems

The augmented reality (AR) research community has been developing a manifold of ideas and concepts to improve the depiction of virtual objects in a real scene. In contrast, current AR applications require the use of unwieldy equipment which discourages their use. In order to essentially ease the perception of digital information and to naturally interact with the pervasive computing landscape, the required AR equipment has to be seamlessly integrated into the user’s natural environment. Considering this basic principle, this paper proposes the car as an AR apparatus and presents an innovative visualization paradigm for navigation systems that is anticipated to enhance user interaction.     

CoViCAD: comprehensive visualization of coronary artery disease

We present novel, comprehensive visualization techniques for the diagnosis of patients with Coronary Artery Disease using segmented cardiac MRI data. We extent an accepted medical visualization technique called the bull's eye plot by removing discontinuities, preserving the volumetric nature of the left ventricular wall and adding anatomical context. The resulting volumetric bull's eye plot can be used for the assessment of transmurality. We link these visualizations to a 3D view that presents viability information in a detailed anatomical context. We combine multiple MRI scans (whole heart anatomical data, late enhancement data) and multiple segmentations (polygonal heart model, late enhancement contours, coronary artery tree). By selectively combining different rendering techniques we obtain comprehensive yet intuitive visualizations of the various data sources.     

Guidelines for Quantitative Evaluation of Medical Visualizations on the Example of 3D Aneurysm Surface Comparisons

Medical visualizations are highly adapted to a specific medical application scenario. Therefore, many researchers conduct qualitative evaluations with a low number of physicians or medical experts to assess the benefits of their visualization technique. Although this type of research has advantages, it is difficult to reproduce and can be subjectively biased. This makes it problematic to quantify the benefits of a new visualization technique. Quantitative evaluation can objectify research and help bringing new visualization techniques into clinical practice. To support researchers, we present guidelines to quantitatively evaluate medical visualizations, considering specific characteristics and difficulties. We demonstrate the adaptation of these guidelines on the example of comparative aneurysm surface visualizations. We developed three visualization techniques to compare aneurysm volumes. The visualization techniques depict two similar, but not identical aneurysm surface meshes. In a user study with 34 participants and five aneurysm data sets, we assessed objective measures (accuracy and required time) and subjective ratings (suitability and likeability). The provided guidelines and presentation of different stages of the evaluation allow for an easy adaptation to other application areas of medical visualization.     

A Comparative Evaluation of Visual Summarization Techniques for Event Sequences

Real-world event sequences are often complex and heterogeneous, making it difficult to create meaningful visualizations using simple data aggregation and visual encoding techniques. Consequently, visualization researchers have developed numerous visual summarization techniques to generate concise overviews of sequential data. These techniques vary widely in terms of summary structures and contents, and currently there is a knowledge gap in understanding the effectiveness of these techniques. In this work, we present the design and results of an insight-based crowdsourcing experiment evaluating three existing visual summarization techniques: CoreFlow, SentenTree, and Sequence Synopsis. We compare the visual summaries generated by these techniques across three tasks, on six datasets, at six levels of granularity. We analyze the effects of these variables on summary quality as rated by participants and completion time of the experiment tasks. Our analysis shows that Sequence Synopsis produces the highest-quality visual summaries for all three tasks, but understanding Sequence Synopsis results also takes the longest time. We also find that the participants evaluate visual summary quality based on two aspects: content and interpretability. We discuss the implications of our findings on developing and evaluating new visual summarization techniques.