Image-Based Visualization: Interactive Multidimensional Data Exploration
Abstract
Our society has entered a data-driven era, one in which not only are enormous amounts of data being generated daily but there are also growing expectations placed on the analysis of this data. Some data have become simply too large to be displayed and some have too short a lifespan to be handled properly with classical visualization or analysis methods. In order to address these issues, this book explores the potential solutions where we not only visualize data, but also allow users to be able to interact with it. Therefore, this book will focus on two main topics: large dataset visualization and interaction.Graphic cards and their image processing power can leverage large data visualization but they can also be of great interest to support interaction. Therefore, this book will show how to take advantage of graphic card computation power with techniques called GPGPUs (general-purpose computing on graphics processing units). As specific examples, this book details GPGPU usages to produce fast enough visualization to be interactive with improved brushing techniques, fast animations between different data representations, and view simplifications (i.e. static and dynamic bundling techniques).Since data storage and memory limitation is less and less of an issue, we will also present techniques to reduce computation time by using memory as a new tool to solve computationally challenging problems. We will investigate innovative data processing techniques: while classical algorithms are expressed in data space (e.g. computation on geographic locations), we will express them in graphic space (e.g., raster map like a screen composed of pixels). This consists of two steps: (1) a data representation is built using straightforward visualization techniques; and (2) the resulting image undergoes purely graphical transformations using image processing techniques. This type of technique is called image-based visualization.The goal of this book is to explore new computing techniques using image-based techniques to provide efficient visualizations and user interfaces for the exploration of large datasets. This book concentrates on the areas of information visualization, visual analytics, computer graphics, and human-computer interaction. This book opens up a whole field of study, including the scientific validation of these techniques, their limitations, and their generalizations to different types of datasets.
... 11.2.1) and also remove small-scale clutter to create a simplified visualisation. For a formal discussion of KDE for trail visualisation, we further refer the reader to (Hurter, 2015). Bundling methods: These methods share their motivation with the density maps described above, aiming to group similar trails to simplify the visualisation. ...
Human migration is an important societal issue with wide-ranging implications, and timely and accurate insights are increasingly needed for understanding the key factors to ensure the well-being of populations. New data sources, such as usage data from mobile phones and applications, remote sensing and satellite images, social media, event and news databases, and financial databases, enable data scientists to collaborate with migration scholars, to equip them with new quantitative tools, to address certain data gaps, and to supply empirical evidence for building and testing theories while complying with ethical requirements. In this book, we provide an overview of the major data sources and link them to migration and mobility in a way accessible to both migration scholars and data scientists, highlighting the relevant issues from multiple aspects, and offering broad social scientific and technical coverage. We describe many case studies about the use of data science in migration and mobility, as well as related areas, such as humanitarian aid. Most importantly, we give a comprehensive treatment of the legal and ethical concerns, discussing surveillance and dataveillance, implications to power structures, and potential misuses of large scale data processing, which need to be addressed to reap the benefits of data science without harming data subjects, or vulnerable groups such as refugees and asylum seekers.
... Trail data can be directly plotted atop of 2D maps, with selected data attributes encoded into visual variables such as color, line thickness, and line style. Besides statically drawing entire trail-sets, these can be also shown by animating particles along their points x i [15,16]. ...
Internet-based technologies such as IoT, GPS-based systems, and cellular networks enable the collection of geolocated mobility data of millions of people in large metropolitan areas. In addition, large, public datasets are made available on the Internet by open government programs, providing ways for citizens, NGOs, scientists, and public managers to perform a multitude of data analysis with the goal of better understanding the city dynamics to provide means for evidence-based public policymaking. However, it is challenging to visualize huge amounts of data from mobility datasets. Plotting raw trajectories on a map often causes data occlusion, impairing the visual analysis. Displaying the multiple attributes that these trajectories come with is an even larger challenge. One approach to solve this problem is trail bundling, which groups motion trails that are spatially close in a simplified representation. In this paper, we augment a recent bundling technique to support multi-attribute trail datasets for the visual analysis of urban mobility. Our case study is based on the travel survey from the São Paulo Metropolitan Area, which is one of the most intense traffic areas in the world. The results show that bundling helps the identification and analysis of various mobility patterns for different data attributes, such as peak hours, social strata, and transportation modes.
... We convert this set of 3D curves (polylines) to a scalar volume by using GPU-accelerated kernel density estimation (KDE) Lhuillier, Hurter, and Telea, 2017. Similar techniques have been used to compute density maps of 2D trail-sets cubu; Hurter, Ersoy, and Telea, 2012;Hurter, 2015. We first explore the density volume (500 3 voxels) using standard DVR (Figure 4.17). ...
L’occlusion est un problème dans la visualisation volumétrique car elle empêche la visualisation directe d’une région d’intérêt. Alors que la plupart des systèmes existants utilisent une combinaison de techniques de rendu en volume direct (DVR) et de leur fonction de transfert (TF) correspondante, nous avons envisagé des techniques d’interaction alternatives pour explorer ces ensembles de données.Tout d’abord, nous avons proposé un nouveau système de visualisation interactive pour les bagages numérisés en 3D, accéléré par les techniques GPGPU, conformément aux besoins que nous avons extraits de l’enquête contextuelle auprès des agents de sécurité de l’aéroport.Deuxièmement, nous avons proposé une nouvelle technique qui associe un rendu volumétrique de haute qualité à une lentille rapide, polyvalente et facile à utiliser pour prendre en charge l’exploration interactive des données occluses dans des volumes.
... Trail data can be directly plotted atop of 2D maps, with selected data attributes encoded into visual variables such as color, line thickness, and line style. Besides statically drawing entire trail-sets, these can be also shown by animating particles along their points x i [14,15]. ...
Internet-based technologies such as IoT, GPS-based systems, and cellular networks enable the collection of geolocated mobility data of millions of people in large metropolitan areas. In addition, large, public datasets are made available on the Internet by open government programs, providing ways for citizens, NGOs, scientists, and public managers to perform a multitude of data analysis with the goal of better understanding the city dynamics to provide means for evidence-based public policymaking. However, it is challenging to visualize huge amounts of data from mobility datasets. Plotting raw trajectories on a map often causes data occlusion, impairing the visual analysis. Displaying the multiple attributes that these trajectories come with is an even larger challenge. One approach to solve this problem is trail bundling, which groups motion trails that are spatially close in a simplified representation. In this paper, we augment a recent bundling technique to support multi-attribute trail datasets for the visual analysis of urban mobility. Our case study is based on the travel survey from the Sao Paulo Metropolitan Area, which is one of the most intense traffic areas in the world. The results show that bundling helps the identification and analysis of various mobility patterns for different data attributes, such as peak hours, social strata, and transportation modes.
... Trail data can be directly plotted atop of 2D maps, with data attributes encoded optionally into visual variables such as color, line thickness, and line style. Besides statically drawing entire trail-sets, these can be also shown by animating particles along their points x i [Hurter 2015]. ...
Visualization of urban mobility data can facilitate the analysis and the decision-making process by public managers. However, mobility datasets tend to be very large and pose several challenges to the use of visualization, such as algorithm scalability and data occlusion. One approach to solve this problem is trail bundling, which groups motion trails that are spatially close in a simplified representation. This paper presents the results of adapting and using a recent bundling technique on a big dataset of urban mobility in São Paulo. The results show that bundling allows the visualization of various mobility patterns in the city.
... Interaction modalities in geovisualization environments are ideally optimized or customizable for the amount of data, display modes, complexity of spaces or phenomena, and diversity of users (e.g., Hoarau and Christophe 2017). Interaction tools and modalities are a core interest in human-computer interaction (e.g., Çöltekin et al. 2017) and, in connection with visualization, they are often investigated with concepts explored in the information visualization domain (Hurter 2015;van Wijk and Nuij 2003), among others. Interaction and how it is designed are especially relevant for virtual and augmented reality approaches to visualization (see the "Immersive Technologies-From Augmented to Virtual Reality" section). ...
... Data-shapes as such are nothing new (Hurter, 2016), but few have tried to use stereoscopically perceivable 3D data-shapes for computer security (Payer & Trossbach, The Application of Virtual Reality for Cyber Information Visualization and Investigation, 2015), while enabling the user to intuitively and / or with a common query language to manipulate the visualization to better understand the underlying dataset. In VDE data-shapes are spatially positioned into a meta-shape (viewed from different angles as shown in Figures 5, 6, 7, 8) to allow the user to take advantage of stereoscopic viewing that VR and MR provide. ...
... Interaction modalities in geovisualization environments are ideally optimized or customizable for the amount of data, display modes, complexity of spaces or phenomena, and diversity of users (e.g., Hoarau and Christophe 2017). Interaction tools and modalities are a core interest in human-computer interaction (e.g., Çöltekin et al. 2017) and, in connection with visualization, they are often investigated with concepts explored in the information visualization domain (Hurter 2015;van Wijk and Nuij 2003), among others. Interaction and how it is designed are especially relevant for virtual and augmented reality approaches to visualization (see the "Immersive Technologies-From Augmented to Virtual Reality" section). ...
In this chapter, we review and summarize the current state of the art in geovisualization and extended reality (i.e., virtual, augmented and mixed reality), covering a wide range of approaches to these subjects in domains that are related to geographic information science. We introduce the relationship between geovisualization, extended reality and Digital Earth, provide some fundamental definitions of related terms, and discuss the introduced topics from a human-centric perspective. We describe related research areas including geovisual analytics and movement visualization, both of which have attracted wide interest from multidisciplinary communities in recent years. The last few sections describe the current progress in the use of immersive technologies and introduce the spectrum of terminology on virtual, augmented and mixed reality, as well as proposed research concepts in geographic information science and beyond. We finish with an overview of “dashboards”, which are used in visual analytics as well as in various immersive technologies. We believe the chapter covers important aspects of visualizing and interacting with current and future Digital Earth applications.
... Data-shapes as such are nothing new (Hurter, 2016), but few have tried to use stereoscopically perceivable 3D data-shapes for computer security (Payer & Trossbach, The Application of Virtual Reality for Cyber Information Visualization and Investigation, 2015), while enabling the user to intuitively and / or with a common query language to manipulate the visualization to better understand the underlying dataset. In VDE data-shapes are spatially positioned into a meta-shape (viewed from different angles as shown in Figures 5, 6, 7, 8) to allow the user to take advantage of stereoscopic viewing that VR and MR provide. ...
US Army C5ISR Center Cyber Security Service Provider (CSSP) is a 24/7 Defensive Cyber Operations (DCO) organization that defends US Department of Defense and US Army networks from hostile cyber activity, as well as develops technologies and capabilities for use by DCO operators within the DoD. In recent years, C5ISR Center CSSP has been researching various advanced data visualization concepts and strategies to enhance the speed and efficiency of cybersecurity analyst's workflow. To achieve these goals Virtual and Mixed Reality (VR/MR) tools have been employed to investigate, whether these mediums would enable useful remote collaboration of DCO operators and whether stereoscopically perceivable 3D data visualizations would enable DCO operators to gain improved hindsight into their datasets. We'll be giving overview of the capabilities being developed as aligned to our research and operational requirements, our expected outcomes of using VR/MR in training and operational cyber environments and our planned path to accomplish these goals.
... Le bundling ajoute des espaces vides au détriment de zones plus denses (Hurter, 2015). ...
Dense and complex data visualizations suffer from occluded items, which hinders insight retrieval. This is especially the case for very large graph or trails set. To address cluttering issues, several techniques propose to visually simplify the representation, often meeting scalability and computational speed limits. Among them, bundling techniques provide a visual simplification of node-link diagrams by spatially grouping similar items. This thesis strives to bridge the gap between the technical complexity of bundling techniques and the end-point user. The first aim of this thesis was to improve the understanding of graph and trail bundling techniques as a clutter reduction method for node-link diagrams of large data-set. To do so, we created a data-based taxonomy that organizes bundling methods on the type of data they work on. From this thorough review and based on a formal definition of path bundling, we propose a unified framework that describes the typical steps of bundling algorithms in terms of high-level operations and show how existing methods classes implement these steps. In addition, we propose a description of tasks that bundling aims to address and demonstrate them through a wide set of applications. Although many techniques exist, handling large data-sets and selectively bundling paths based on attributes is still a challenge. To answer the scalability and computational speed issues of bundling techniques, we propose a new technique which improves both. For this, we shift the bundling process from the image to the spectral space, thereby increasing computational limits. We address the later by proposing a streaming scheme allowing bundling of extremely large data-sets. Finally, as an application domain, we studied how bundling can be used as an efficient visualization technique for societal health challenges. In the context of a national study on Alzheimer disease, we focused our research on the analysis of the mental representation of geographical space for elderly people. We show that using bundling to compare the cognitive maps of dement and non-dement subjects helped neuro-psychologist to formulate new hypotheses on the evolution of Alzheimer disease. These new hypotheses led us to discover a potential marker of the disease years before the actual diagnosis.
... Le bundling ajoute des espaces vides au détriment de zones plus denses (Hurter, 2015). ...
Le big data est un challenge majeur de la visualisation ; l’augmentation du nombre de données à visualiser augmentela densité et l’occultation des graphes et il devient difficile de distinguer les éléments qui le compose. Pour résoudrece challenge, plusieurs techniques de visualisation se focalisent sur la simplification visuelle ; parmi elles, l’agréga-tion visuelle (bundling) permet l’agrégation des liens pour créer des zones de fortes densités au profit d’espacesplus clairsemés faisant ainsi émerger des structures visuelles. Cette thèse s’efforce à faire le trait d’union entre lacomplexité technique des algorithmes de bundling et les utilisateurs finaux.Dans un premier temps, nous avons formalisé l’espace de design des techniques de bundling afin d’améliorer lacompréhension des chercheurs et des utilisateurs. Notre formalisation se fonde sur une taxonomie centrée utilisateurorganisant l’ensemble des techniques d’agrégation en fonction des données d’entrée. Ensuite, à partir d’une définitionformelle du bundling, nous proposons un modèle générique décrivant l’ensemble des étapes usuelles des algorithmesde bundling et montrons comment les techniques existantes implémentent chaque étape. Enfin, à travers une analysedes tâches, nous exposons des cas d’utilisation avérés.Notre analyse de l’espace des techniques de bundling nous a montré les limites actuelles du bundling quant au trai-tement de grande quantité de données tant en terme de rapidité de calcul qu’en terme de taille des jeux de données.Ainsi, nous avons résolu ces limites en introduisant une nouvelle technique plus rapide et sans limitation de taille :FFTEB (Fast Fourier Transform Edge Bundling Technique). Notre technique déplace le processus d’agrégation del’espace pixelaire vers l’espace spectral. Enfin, grâce à un processus de transfert des données, FFTEB résout lesproblèmes de taille de jeux de données.En dernier lieu, dans le cadre d’une application à la maladie d’Alzheimer, cette thèse démontre l’efficacité destechniques de bundling comme outil d’exploration visuelle. Dans le contexte d’une étude nationale sur la maladied’Alzheimer, nous avons focalisé notre recherche sur l’analyse de la représentation mentale de l’espace géographiquechez les personnes âgées. Nous montrons que l’utilisation du bundling pour comparer les cartes mentales despopulations démentes et non-démentes a permis à des neuropsychologues de formuler de nouvelles hypothèses surl’évolution de la maladie d’Alzheimer. Ces nouvelles hypothèses nous ont permis de montrer l’émergence d’unpotentiel marqueur de la maladie près de douze ans avant que les patients ne soient diagnostiqués comme atteintsde cette maladie.
... computers) are positioned according to their logical topology (e.g. computer or server groups and not only physical or functional topology) so, that the resulting 3D structure(s) would relate to a SOC/NOC analyst's task, which in this LS16 example would be to detect prohibited connections between Blue Team's network devices. Data-shapes as such are nothing new (Hurter, 2016), but few have tried to use stereoscopically perceivable 3D data-shapes for computer security (Payer & Trossbach, 2015). ...
The human visual system is generally more adept at inferring meaning from graphical objects and natural scene elements than reading alphanumeric characters. Graphical objects like charts and graphs in cybersecurity dashboards often lack the requisite numbers of features to depict behaviors of complex network data. For example, bar charts afford few features to encode a panoply of parameters in network data. Furthermore, dashboard visualizations seldom support the transition of human work from situation awareness building to requisite responses during intrusion detection events. This research effort aims to identify how graphical objects (also referred as data-shapes) depicted in Virtual Reality tools, developed in accordance with an analyst’s mental model of an intrusion detection event, can enhance analyst’s situation awareness. We demonstrate the proposed approach using Locked Shields 16 CDX network traffic. Implications of this study and future case study are discussed.
... with the space-time cube (Hägerstrand 1970 (Ersoy et al. 2011;Hurter 2016). ...
How to effectively and efficiently represent the dynamics of spatial phenomena and processes has been a long-standing research question in geographic information science (GIScience). In a digital information age, computer-generated animations that depict movement data have become increasingly popular, as they apparently visualize real-world spatio-temporal movement changes with corresponding changes over time in a moving display. Animation thus seems to be a suitable display method for facilitating the recognition of spatio-temporal movement patterns and the prediction of future spatio-temporal events.
However, the manner by which animations are designed may limit the effectiveness and efficiency of visuospatial decision-making.
Furthermore, the specific decision-making task or context of use, as well as the viewer’s perceptual, cognitive and affective background might also influence visuospatial decision-making with animations. These factors are not well understood to date. More empirical studies, as well as new methods to evaluate animations, are thus needed.
This work proposes a user-centred empirical approach to evaluate animation design characteristics for space-time decision-making with movement data. Two experiments are conducted with the overall aim of answering the following main research question: How should animations of real-time movement data be designed considering the task and/or use contexts, and user characteristics? More specifically, we test the influence of the three main visual analytics (VA) dimensions on viewer spatio-temporal decision-making with animations: (1) the use context and respective task characteristics, (2) the animation display design, and (3) user characteristics. To test each respective dimension, we undertook the following investigations:
(1) Using current air traffic control (ATC) scenarios and existing ATC displays we empirically investigated how aircraft movement changes and future aircraft movement patterns can be visualized for effective and efficient decision-making in ATC. (2) We empirically investigated how movement characteristics (i.e., acceleration, heading direction, etc.) can be depicted, and how animation design (i.e., continuous vs. semi-static animations) might influence viewer task performances.
(3) We empirically investigated how perceptual, cognitive, and affective characteristics of viewers (i.e., expertise, spatial abilities, stress or motivation) might influence visuospatial decision-making with animations.
We approached these questions through novel empirical data triangulation that integrates psychophysical sensing (i.e., electrodermal responses (EDA)), brain activity (i.e., electroencephalography (EEG)), and eye tracking (ET) with standardized questionnaires.
The results of the experiments showed that these three factors (i.e., the use context and respective task characteristics, the animation display design, and the user characteristics) indeed influence visuospatial decision-making using animations of aircraft movement data. We found that viewer decision-making was affected by animation design depending on expertise and task type. Unsurprisingly, ATC experts performed typical ATC tasks more accurately compared to novices. However, the task performance of the experts differed between continuous animation and semi-static animation designs depending on the ATC task. Surprisingly, experts responded more accurately with the novel continuous animation designs compared to the semi-static animations that are more familiar to them in critical ATC tasks for predicting future aircraft movements. In apprehension tasks of aircraft movement changes, experts performed in similar ways with both animation designs. Moreover, viewer characteristics, such as spatial abilities and emotional aspects including engagement or motivation, seemed to affect viewer task performances as well. Higher-spatial and more engaged (or more motivated) viewers performed both tasks more effectively than lower-spatial decision makers and less-engaged (or less-motivated) viewers.
Overall, our unique empirical results related to the depiction of real-time movement data contribute to GIScience and cartography in two important ways. First, we are beginning to better understand how viewer mental processes, including perception and cognition, as well as their affective states might influence the effectiveness and efficiency of visuospatial decision-making with animations. Second, we are now able to derive empirically validated design guidelines for perceptually salient, affectively engaging, and cognitively inspired animations.
... Such animations have been applied to large element-based plots such as bundled graphs and scatterplots [6,58]. Smooth real-time animations of large datasets have been made possible by using GPU-based techniques [59]. For multidimensional projections, we have the following direct manipulation techniques. ...
Understanding large multidimensional datasets is one of the most challenging problems in visual data exploration. One key challenge that increases the size of the exploration space is the number of views that one can generate from a single dataset, based on the use of multiple parameter values and exploration paths. Often, no such single view contains all needed insights. The question thus arises of how we can efficiently combine insights from multiple views of a dataset. We propose a set of techniques that considerably reduce the exploration effort for such situations, based on the explicit depiction of the view space, using a small multiple metaphor. We leverage this view space by offering interactive techniques that enable users to explicitly create, visualize, and follow their exploration path. This way, partial insights obtained from each view can be efficiently and effectively combined. We demonstrate our approach by applications using real-world datasets from air traffic control, software maintenance, and machine learning.
... However, the rapid development of the field, coupled with the diversity of its application domains, data types handled (e.g., graphs, vehicle trails, eye tracking data, vector and tensor fields, all of them attributed or not and time-dependent or not), and a plethora of algorithmic approaches, make it hard for users to choose the suitable method for a given use-case, and for researchers to focus on important areas of improvement. Bundling is featured, though with limited detail, in a survey on image-based information visualization [Hur15], and has gained a prominent place in the set of practical clutter-reduction methods for large graph visualization [SH13]. Another recent survey on large graph visualization [LKS * 11] only tangentially touches graph bundling. ...
Bundling techniques provide a visual simplification of a graph drawing or trail set, by spatially grouping similar graph edges or trails. This way, the structure of the visualization becomes simpler and thereby easier to comprehend in terms of assessing relations that are encoded by such paths, such as finding groups of strongly interrelated nodes in a graph, finding connections between spatial regions on a map linked by a number of vehicle trails, or discerning the motion structure of a set of objects by analyzing their paths. In this state of the art report, we aim to improve the understanding of graph and trail bundling via the following main contributions. First, we propose a data-based taxonomy that organizes bundling methods on the type of data they work on (graphs vs trails, which we refer to as paths). Based on a formal definition of path bundling, we propose a generic framework that describes the typical steps of all bundling algorithms in terms of high-level operations and show how existing method classes implement these steps. Next, we propose a description of tasks that bundling aims to address. Finally, we provide a wide set of example applications of bundling techniques and relate these to the above-mentioned taxonomies. Through these contributions, we aim to help both researchers and users to understand the bundling landscape as well as its technicalities.
Interactive Data Visualizations (IDV) can be useful for cybersecurity subject matter experts (CSMEs) while they are exploring new data or investigating familiar datasets for anomalies, correlating events, etc. For an IDV to be useful to a CSME, interaction with that visualization should be simple and intuitive (free of additional mental tasks) and the visualization’s layout must map to a CSME’s understanding. While CSMEs may learn to interpret visualizations created by others, they should be encouraged to visualize their datasets in ways that best reflect their own ways of thinking. Developing their own visual schemes makes optimal use of both the data analysis tools and human visual cognition.
In this article, we focus on a currently available interactive stereoscopically perceivable multidimensional data visualization solution, as such tools could provide CSMEs with better perception of their data compared to interpreting IDV on flat media (whether visualized as 2D or 3D structures).
Time-series data–usually presented in the form of lines–plays an important role in many domains such as finance, meteorology, health, and urban informatics. Yet, little has been done to support interactive exploration of large-scale time-series data, which requires a clutter-free visual representation with low-latency interactions. In this paper, we contribute a novel line-segment-based KD-tree method to enable interactive analysis of many time series. Our method enables not only fast queries over time series in selected regions of interest but also a line splatting method for efficient computation of the density field and selection of representative lines. Further, we develop KD-Box, an interactive system that provides rich interactions, e.g., timebox, attribute filtering, and coordinated multiple views. We demonstrate the effectiveness of KD-Box in supporting efficient line query and density field computation through a quantitative comparison and show its usefulness for interactive visual analysis on several real-world datasets.
Eye-tracking tools estimate the locations in a scene where a user is fixating on. They are used in various domains including human-computer interaction (HCI) and learning transfer. As an example, gaze-based text entry allows interacting with computing systems remotely without touching the interface. They are also used to comprehend the visual behaviors of a pilot searching for information in a cockpit. However, a number of barriers still exists and makes these devices less accurate and difficult to use in daily activities. One of these problems is the shift between the actual and the estimated position of the user’s point-of-regard, which systematically comes from the eye-tracking systems’ accuracy. Following recent advances, there is an increasing interest in affordable systems that have the potential to be more accurate and, researchers are continually investigating novel approaches.This thesis covers different issues of eye movement research. It proposes the use of novel approaches as a step towards overcoming these accuracy issues. More specifically, we introduce novel strategies for detecting mapping functions for gaze estimation and calibration-free gaze interaction. In addition to proposing frameworks and strategies for improving accuracy, new calibration procedures and patterns are also revealed and discussed. In this thesis, we address these issues in three different ways: calibration and mapping functions, Human-computer Interaction using the eyes, visualization and exploration. We present four main contributions. First, we present a new method for calibrating state-of-the-art eye trackers with better accuracy. Second, we present a new gaze-based authentication method which works without any prior calibration, and can be extended to any alphanumeric-based input modality. Third, we present an uncertainty visualization approach. Finally, a method of analyzing eyemovements data and aircraft trajectories using a novel brushing technique is proposed.
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.
Cybersecurity analysts ingest and process significant amounts of data from diverse sources in order to acquire network situation awareness. Visualizations can enhance the efficiency of analysts' workflow by providing contextual information, various sets of cybersecurity related data, information regarding alerts, among others. However, textual displays and 2D visualizations have limited capabilities in displaying complex, dynamic and multidimensional information. There have been many attempts to visualize data in 3D, while being displayed on 2D displays, but success has been limited. We propose that customized, stereoscopically perceivable 3D visualizations aligned with analysts' internal representations of network topology, may enhance their capability to understand their networks' state in ways that 2D displays cannot afford. These 3D visualizations may also provide a path for users who are trained and comfortable with textual and 2D representations of data to assess visualization methods that may be suitably aligned to implicit knowledge of their networks. Thus, the premise of custom data-visualizations forms the foundation for this study. Herein, we report on findings from a comparative, qualitative, within-subjects usability analysis between 2D and 3D representations of the same network traffic dataset. Study participants (analysts) provided information on: 1.) ability to create an initial understanding of the network, 2.) ease of finding task-relevant information in the representation, and 3.) overall usability. Results indicated that interviewees indicated a preference for 3D visualizations over the 2D alternatives and we discuss possible explanations for this preference.
Visualizing large, multiply-attributed, and time-dependent graphs is one of the grand challenges of information visualization. In recent years, image-based techniques have emerged as a strong competitor in the arena of solutions for this task. While many papers on this topic have been published, the precise advantages and limitations of such techniques, and also how they relate to similar techniques in the more traditional fields of scientific visualization (scivis) and image processing, have not been sufficiently outlined. In this paper, we aim to provide such an overview and comparison. We highlight the main advantages of image-based graph visualization and propose a simple taxonomy for such techniques. Next, we highlight the differences between graph and scivis/image datasets that lead to limitations of current image-based graph visualization techniques. Finally, we consider these limitations to propose a number of future work directions for extending the effectiveness and range of image-based graph visualization.
Bundling visually aggregates curves to reduce clutter and help finding important patterns in trail-sets or graph drawings. We propose a new approach to bundling based on functional decomposition of the underling dataset. We recover the functional nature of the curves by representing them as linear combinations of piecewise-polynomial basis functions with associated expansion coefficients. Next, we express all curves in a given cluster in terms of a centroid curve and a complementary term, via a set of so-called principal component functions. Based on the above, we propose a two-fold contribution: First, we use cluster centroids to design a new bundling method for 2D and 3D curve-sets. Secondly, we deform the cluster centroids and generate new curves along them, which enables us to modify the underlying data in a statistically-controlled way via its simplified (bundled) view. We demonstrate our method by applications on real-world 2D and 3D datasets for graph bundling, trajectory analysis, and vector field and tensor field visualization.
An interactive visualization system can support volumetric data exploration in airport security screenings by addressing the challenges unique to the baggage inspection. The proposed system includes a set of interaction techniques that combine the direct manipulation of voxels and their interactive visualization. The system's final tools and GUI design incorporate feedback from airport personnel and were validated by real-world users in terms of effectiveness and ease of use.
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