Using visual design experts in critique-based evaluation of 2D vector visualization methods

We describe an experiment in which art and illustration experts evaluated six 2D vector visualization methods. We found that these expert critiques mirrored previously recorded experimental results; these findings support that using artists, visual designers and illustrators to critique scientific visualizations can be faster and more productive than quantitative user studies. Our participants successfully evaluated how well the given methods would let users complete a given set of tasks. Our results show a statistically significant correlation with a previous objective study: designers' subjective predictions of user performance by these methods match users measured performance. The experts improved the evaluation by providing insights into the reasons for the effectiveness of each visualization method and suggesting specific improvements.     

Visualization of myocardial perfusion derived from coronary anatomy

Visually assessing the effect of the coronary artery anatomy on the perfusion of the heart muscle in patients with coronary artery disease remains a challenging task. We explore the feasibility of visualizing this effect on perfusion using a numerical approach. We perform a computational simulation of the way blood is perfused throughout the myocardium purely based on information from a three-dimensional anatomical tomographic scan. The results are subsequently visualized using both three-dimensional visualizations and bull's eye plots, partially inspired by approaches currently common in medical practice. Our approach results in a comprehensive visualization of the coronary anatomy that compares well to visualizations commonly used for other scanning technologies. We demonstrate techniques giving detailed insight in blood supply, coronary territories and feeding coronary arteries of a selected region. We demonstrate the advantages of our approach through visualizations that show information which commonly cannot be directly observed in scanning data, such as a separate visualization of the supply from each coronary artery. We thus show that the results of a computational simulation can be effectively visualized and facilitate visually correlating these results to for example perfusion data.     

Pathline glyphs

Visualization of pathlines is common and highly relevant for the analysis of unsteady flow. However, pathlines can intersect, leading to visual clutter and perceptual issues. This makes it intrinsically difficult to provide expressive visualizations of the entire domain by an arrangement of multiple pathlines, in contrast to well‐established streamline placement techniques. We present an approach to reduce these problems. It is inspired by glyph‐based visualization and small multiples: we partition the domain into cells, each corresponding to a downscaled version of the entire domain. Inside these cells, a single downscaled pathline is drawn. On the overview scale, our pathline glyphs lead to emergent visual patterns that provide insight into time‐dependent flow behavior. Zooming‐in allows us to analyze individual pathlines in detail and compare neighboring lines. The overall approach is complemented with a context‐preserving zoom lens and interactive pathline‐based exploration. While we primarily target the visualization of 2D flow, we also address the extension to 3D. Our evaluation includes several examples, comparison to other flow visualization techniques, and a user study with domain experts.     

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.     

Proof-of-concept of an information visualization classification approach based on their fine-grained features

The misinformation problem affects the development of the society. Misleading content and unreliable information overwhelm social networks and media. In this context, the use of data visualizations to support news and stories is increasing. The use of misleading visualizations both intentionally or accidentally influence in the audience perceptions, which usually are not visualization and domain experts. Several factors influence o accurately tag a visualization as confusing or misleading. In this paper, we present a machine learning approach to detect if an information visualization can be potentially confusing and misunderstood based on the analytic task it tries to support. This approach is supported by fine-grained features identified through domain engineering and meta modelling on the information visualization and dashboards domain. We automatically generated visualizations from a tri-variate dataset through the software product line paradigm and manually labelled them to obtain a training dataset. The results support the viability of the proposal as a tool to support journalists, audience and society in general, not only to detect confusing visualizations, but also to select the visualization that supports a previous defined task according to the data domain.     

Multi-touch table system for medical visualization: application to orthopedic surgery planning

Medical imaging plays a central role in a vast range of healthcare practices. The usefulness of 3D visualizations has been demonstrated for many types of treatment planning. Nevertheless, full access to 3D renderings outside of the radiology department is still scarce even for many image-centric specialties. Our work stems from the hypothesis that this under-utilization is partly due to existing visualization systems not taking the prerequisites of this application domain fully into account. We have developed a medical visualization table intended to better fit the clinical reality. The overall design goals were two-fold: similarity to a real physical situation and a very low learning threshold. This paper describes the development of the visualization table with focus on key design decisions. The developed features include two novel interaction components for touch tables. A user study including five orthopedic surgeons demonstrates that the system is appropriate and useful for this application domain.     

Evaluating View Management for Situated Visualization in Web-based Handheld AR

As visualization makes the leap to mobile and situated settings, where data is increasingly integrated with the physical world using mixed reality, there is a corresponding need for effectively managing the immersed user's view of situated visualizations. In this paper we present an analysis of view management techniques for situated 3D visualizations in handheld augmented reality: a shadowbox, a world-in-miniature metaphor, and an interactive tour. We validate these view management solutions through a concrete implementation of all techniques within a situated visualization framework built using a web-based augmented reality visualization toolkit, and present results from a user study in augmented reality accessed using handheld mobile devices.     

基于Radviz及其优化的可视化故障诊断方法*

阐述了Radviz（radial visualization）技术,即将高维数据样本非线性的投影到二维目标空间。Vizrank优化能够从数以万计的投影图中评价和确定最好的投影方式;能够快速找到容易被领域专家认可的可视化模型,只需少量输入变量（27）就能够做到数据的可视化,并且有很好的分类效果。在TEP仿真系统中的应用,表明了Radviz及其优化的可视化故障诊断方法可以将正常与故障状态有效地分开。该可视化故障诊断方法具有简单而不失精确性、易于利用领域专家知识、诊断结果直观形象并容易理解等显著优点。     

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.     

Automatic Transfer Function Specification for Visual Emphasis of Coronary Artery Plaque

Cardiovascular imaging with current multislice spiral computed tomography (MSCT) technology enables a non-invasive evaluation of the coronary arteries. Contrast-enhanced MSCT angiography with high spatial resolution allows for a segmentation of the coronary artery tree. We present an automatically adapted transfer function (TF) specification to highlight pathologic changes of the vessel wall based on the segmentation result of the coronary artery tree. The TFs are combined with common visualization techniques, such as multiplanar reformation and direct volume rendering for the evaluation of coronary arteries in MSCT image data. The presented TF-based mapping of CT values in Hounsfield Units (HU) to color and opacity leads to a different color coding for different plaque types. To account for varying HU values of the vessel lumen caused by the contrast medium, the TFs are adapted to each dataset by local histogram analysis. We describe an informal evaluation with three board-certified radiologists which indicates that the represented visualizations guide the user's attention to pathologic changes of the vessel wall as well as provide an overview about spatial variations.     

Visual mining of time series using a tubular visualization

In this paper, we study the visual mining of time series, and we contribute to the study and evaluation of 3D tubular visualizations. We describe the state of the art in the visual mining of time-dependent data, and we concentrate on visualizations that use a tubular shape to represent data. After analyzing the motivations for studying such a representation, we present an extended tubular visualization. We propose new visual encodings of the time and data, new interactions for knowledge discovery, and the use of rearrangement clustering. We show how this visualization can be used in several real-world domains and that it can address large datasets. We present a comparative user study. We conclude with the advantages and the drawbacks of our method (especially the tubular shape).     

Evaluating the Impact of User Characteristics and Different Layouts on an Interactive Visualization for Decision Making

There is increasing evidence that user characteristics can have a significant impact on visualization effectiveness, suggesting that visualizations could be designed to better fit each user's specific needs. Most studies to date, however, have looked at static visualizations. Studies considering interactive visualizations have only looked at a limited number of user characteristics, and consider either low‐level tasks (e.g., value retrieval), or high‐level tasks (in particular: discovery), but not both. This paper contributes to this line of work by looking at the impact of a large set of user characteristics on user performance with interactive visualizations, for both low and high‐level tasks. We focus on interactive visualizations that support decision making, exemplified by a visualization known as Value Charts. We include in the study two versions of ValueCharts that differ in terms of layout, to ascertain whether layout mediates the impact of individual differences and could be considered as a form of personalization. Our key findings are that (i) performance with low and high‐level tasks is affected by different user characteristics, and (ii) users with low visual working memory perform better with a horizontal layout. We discuss how these findings can inform the provision of personalized support to visualization processing.     

VizAssist: an interactive user assistant for visual data mining

We study in this work how a user can be guided to find a relevant visualization in the context of visual data mining. We present a state of the art on the user assistance in visual and interactive methods. We propose a user assistant called VizAssist, which aims at improving the existing approaches along three directions: it uses simpler computational models of the visualizations and the visual perception guidelines, in order to facilitate the integration of new visualizations and the definition of a mapping heuristic. VizAssist allows the user to provide feedback in a visual and interactive way, with the aim of improving the data to visualization mapping. This step is performed with an interactive genetic algorithm. Finally, VizAssist aims at proposing a free on-line tool (www.vizassist.fr) that respects the privacy of the user data. This assistant can be viewed as a global interface between the user and some of the many visualizations that are implemented with D3js.     

Glyph-based SPECT visualization for the diagnosis of coronary artery disease

Myocardial perfusion imaging with single photon emission computed tomography (SPECT) is an established method for the detection and evaluation of coronary artery disease (CAD). State-of-the-art SPECT scanners yield a large number of regional parameters of the left-ventricular myocardium (e.g., blood supply at rest and during stress, wall thickness, and wall thickening during heart contraction) that all need to be assessed by the physician. Today, the individual parameters of this multivariate data set are displayed as stacks of 2D slices, bull's eye plots, or, more recently, surfaces in 3D, which depict the left-ventricular wall. In all these visualizations, the data sets are displayed side-by-side rather than in an integrated manner, such that the multivariate data have to be examined sequentially and need to be fused mentally. This is time consuming and error-prone. In this paper we present an interactive 3D glyph visualization, which enables an effective integrated visualization of the multivariate data. Results from semiotic theory are used to optimize the mapping of different variables to glyph properties. This facilitates an improved perception of important information and thus an accelerated diagnosis. The 3D glyphs are linked to the established 2D views, which permit a more detailed inspection, and to relevant meta-information such as known stenoses of coronary vessels supplying the myocardial region. Our method has demonstrated its potential for clinical routine use in real application scenarios assessed by nuclear physicians.     

Comparing Node‐Link and Node‐Link‐Group Visualizations From An Enjoyment Perspective

While evaluation studies in visualization often involve traditional performance measurements, there has been a concerted effort to move beyond time and accuracy. Of these alternative aspects, memorability and recall of visualizations have been recently considered, but other aspects such as enjoyment and engagement are not as well explored. We study the enjoyment of two different visualization methods through a user study. In particular, we describe the results of a three‐phase experiment comparing the enjoyment of two different visualizations of the same relational data: node‐link and node‐link‐group visualizations. The results indicate that the participants in this study found node‐link‐group visualizations more enjoyable than node‐link visualizations.     

Map‐based Visualizations Increase Recall Accuracy of Data

We investigate the memorability of data represented in two different visualization designs. In contrast to recent studies that examine which types of visual information make visualizations memorable, we examine the effect of different visualizations on time and accuracy of recall of the displayed data, minutes and days after interaction with the visualizations. In particular, we describe the results of an evaluation comparing the memorability of two different visualizations of the same relational data: node‐link diagrams and map‐based visualization. We find significant differences in the accuracy of the tasks performed, and these differences persist days after the original exposure to the visualizations. Specifically, participants in the study recalled the data better when exposed to map‐based visualizations as opposed to node‐link diagrams. We discuss the scope of the study and its limitations, possible implications, and future directions.     

Methods for Compensating Contrast Effects in Information Visualization

Color, as one of the most effective visual variables, is used in many techniques to encode and group data points according to different features. Relations between features and groups appear as visual patterns in the visualization. However, optical illusions may bias the perception at the first level of the analysis process. For instance, in pixel‐based visualizations contrast effects make pixels appear brighter if surrounded by a darker area, which distorts the encoded metric quantity of the data points. Even if we are aware of these perceptual issues, our visual cognition system is not able to compensate these effects accurately. To overcome this limitation, we present a color optimization algorithm based on perceptual metrics and color perception models to reduce physiological contrast or color effects. We evaluate our technique with a user study and find that the technique doubles the accuracy of users comparing and estimating color encoded data values. Since the presented technique can be used in any application without adaption to the visualization itself, we are able to demonstrate its effectiveness on data visualizations in different domains.     

Interactive visualization of dependencies

We present an interactive tool for browsing course requisites as a case study of dependency visualization. This tool uses multiple interactive visualizations to allow the user to explore the dependencies between courses. A usability study revealed that the proposed browser provides significant advantages over traditional methods, in terms of learnability, efficiency and user confidence. The results are discussed within a general framework for interactive visualization of dependencies.     

Illustrative Multivariate Visualization for Geological Modelling

In this paper, we present a novel illustrative multivariate visualization for geological modelling to assist geologists and reservoir engineers in visualizing multivariate datasets in superimposed representations, in contrast to the single‐attribute visualizations supported by commercial software. Our approach extends the use of decals from a single surface to 3D irregular grids, using the layering concept to represent multiple attributes. We also build upon prior work to augment the design and implementation of different geological attributes (namely, rock type, porosity, and permeability). More specifically, we propose a new sampling strategy to generate decals for porosity on the geological grid, a hybrid visualization for permeability which combines 2D decals and 3D ellipsoid glyphs, and a perceptually‐based design that allows us to visualize additional attributes (e.g., oil saturation) while avoiding visual interference between layers. Furthermore, our visual design draws from traditional geological illustrations, facilitating the understanding and communication between interdisciplinary teams. An evaluation by domain experts highlights the potential of our approach for geological modelling and interpretation in this complex domain.