Visualization Challenge Research Articles

Study on the methods of visualizing bloodstains after thermal exposure.

To establish the correlation between thermal conditions imposed on bloodstains and visualizing effect of enhancement techniques, infrared photography and four chemical enhancement reagents were used to visualize bloodstains following thermal exposure. A black tile was selected as the substrate to intensify the visualization challenge, with a Cone Calorimeter serving as the standardized heating source to control thermal conditions. Compared with standard photography, infrared photography is proven to be a valuable complement to chemical reagents, showing significant advantages in visualizing bloodstains after thermal exposure. However, it is worth noting that infrared image fell short of standard image when bloodstains displayed raised, embossed morphology or when bloodstains almost disappeared under specific conditions. The enhancement effectiveness was found to be strongly correlated with thermal conditions imposed on bloodstains, and the morphology evolution of bloodstains during heating affected the chemical enhancement effect additionally, especially when the bulge morphology was formed, and it was observed that reagents were more effective after removing the dense shell of the bulge. Among the four selected chemical enhancement reagents, fluorescein performed exceptionally well, maintaining its effectiveness even for bloodstains heated at 641°C for 10 min. TMB demonstrated its visualizing ability for bloodstains heated at 396°C for 5 min and heated at 310°C for 20 min. BLUESTAR® followed afterwards, while luminol performed worst. The correlation between thermal conditions imposed on bloodstains and the corresponding visualizing effectiveness of enhancement techniques provides important references for detecting bloodstains at fire scenes.

TrajectoryViz: Interactive visualization of treatment trajectories

Background and objectivesWith the proliferation of real-world or observational health data, there is increasing interest in studying treatment trajectories. The real-life treatment trajectories can be complex, and one has to simplify the patterns to draw any conclusions; however, oversimplification will cause the loss of essential details. Thus, the visualization challenge is to strike a balance between the two extremes. MethodsWe have implemented the observation of treatment trajectories starting from cohort definitions in cooperation with medical specialists, data processing, and then generating the interactive visualizations and detailed data tables derived from input data within an open-source R package as a Shiny dashboard. The created R package called TrajectoryViz (https://github.com/HealthInformaticsUT/TrajectoryViz) enables reproducible visual analysis and visual content generation for various data investigations and explanations. ResultsWe illustrate the use of the tool by assessing the sequence of events present within the data of cervical cancer prevention pathways, as well as the proportions of timely follow-up procedure events. ConclusionBuilding a toolset to access, manage, and analyze observational health data enables more accessible visual analysis of complicated data, adding time dimension to otherwise simplified event sequences that make up trajectories.

Real-Time Big Data Analytics and Proactive Traffic Safety Management Visualization System

Big data and data-driven analysis could be utilized for traffic management to improve road safety and the performance of transportation systems. This paper introduces a web-based proactive traffic safety management (PATM) and real-time big data visualization tool, which is based on an award-winning system that won the US Department of Transportation (USDOT) Solving for Safety Visualization Challenge and was selected as one of the USDOT Safety Data Initiative (SDI) Beta Tools. State-of-the-art research, especially for real-time crash prediction and PATM, are deployed in this study. A significant amount of real-time data is accessed by the system in order to conduct data-driven analysis, such as traffic data, weather data, and video data from closed-circuit television (CCTV) live streams. Based on the data, multiple modules have been developed, including real-time crash/secondary crash prediction, CCTV-based expedited detection, PATM recommendation, data sharing, and report generation. Both real-time data and the system outputs are visualized at the front end using interactive maps and various types of figures to represent the data distribution and efficiently reveal hidden patterns. Evaluation of the real-time crash prediction outputs is conducted based on one-month real-world crash data and the prediction results from the system. The comparison results indicate excellent prediction performance. When considering spatial-temporal tolerance, the sensitivity and false alarm rate of the prediction results [i.e., high crash potential event (HCPE)] are 0.802 and 0.252, respectively. Current and potential implementation are also discussed in this paper.

Dynamical In Situ Study of Morphological Variations on Stainless Steel in a Sour Corrosive Environment

It is still unclear how environmentally assisted cracking, especially sulfide stress cracking (SSC), is caused by corrosion and fracture behavior. In this study, a new in situ technique for an SSC visualization challenge was established and applied for the visualization of microcrack propagation resulting from a single pitting on the steel surface of 13% Cr martensitic stainless steel during four-point bending SSC tests and discussed by combining ex situ x-ray computed tomography (XCT) and electron backscatter diffraction (EBSD). The dynamic behavior of microcracks was visualized successfully, and the microbubbles behavior with the corrosion reaction was also captured. Regarding the relationship between internal structure and microstructure for cracking, it was found that a cavity was formed in the interior of prior to the cracks seen on the surface by XCT, and cracks by EBSD were propagated along prior austenite grain boundaries. On the basis of in situ observations and complementary ex situ analyses, the actual situation of crack on the steel surface was revealed and discussed with both corrosion and fracture over time. This approach provides an opportunity to clarify the SSC occurrence process based on actual SSC tests and contributes to the determination of phenomenological criteria. Furthermore, by combining this in situ technique with commonly known electrochemical measurements such as polarization curves, open-circuit potentials, and electrochemical impedance spectroscopy, it is possible to directly discuss various electrochemical data corresponding to corrosion and fracture behavior, including dissolution and gas evolution.

New Approach to Accelerated Image Annotation by Leveraging Virtual Reality and Cloud Computing.

Three-dimensional imaging is at the core of medical imaging and is becoming a standard in biological research. As a result, there is an increasing need to visualize, analyze and interact with data in a natural three-dimensional context. By combining stereoscopy and motion tracking, commercial virtual reality (VR) headsets provide a solution to this critical visualization challenge by allowing users to view volumetric image stacks in a highly intuitive fashion. While optimizing the visualization and interaction process in VR remains an active topic, one of the most pressing issue is how to utilize VR for annotation and analysis of data. Annotating data is often a required step for training machine learning algorithms. For example, enhancing the ability to annotate complex three-dimensional data in biological research as newly acquired data may come in limited quantities. Similarly, medical data annotation is often time-consuming and requires expert knowledge to identify structures of interest correctly. Moreover, simultaneous data analysis and visualization in VR is computationally demanding. Here, we introduce a new procedure to visualize, interact, annotate and analyze data by combining VR with cloud computing. VR is leveraged to provide natural interactions with volumetric representations of experimental imaging data. In parallel, cloud computing performs costly computations to accelerate the data annotation with minimal input required from the user. We demonstrate multiple proof-of-concept applications of our approach on volumetric fluorescent microscopy images of mouse neurons and tumor or organ annotations in medical images.

On pixel-exact rendering for high-order mesh and solution

With the increasing use of high-order methods and high-order meshes, scientific visualization software need to adapt themselves to reliably render the associated meshes and numerical solutions. In this paper, a novel approach, based on OpenGL 4 framework, enables a GPU-based rendering of high-order meshes as well as an almost pixel-exact rendering of high-order solutions. Several aspects of the OpenGL Shading Language and in particular the use of dedicated shaders (GPU programs) allows to answer this visualization challenge. Fragment shaders are used to compute the exact solution for each pixel, made possible by the transfer of degrees of freedom and shape functions to the GPU with textures. Tessellation shaders, combined with geometric error estimates, allow us to render high-order curved meshes by providing an adaptive subdivision of elements on the GPU directly. A convenient way to compute bounds for high-order solutions is described. The interest of using Bézier basis instead of Lagrange functions lies in the existence of fast and robust evaluation of polynomial functions with de Casteljau algorithm. A technique to plot highly nonlinear isolines and wire frames with a desired thickness is derived. It is based on a finite difference scheme performed on GPU. In comparison with standard techniques, we remove the use of any linear interpolation step and the need to generate a priori a fixed subdivided mesh. This reduces the memory footprint, improves the accuracy and the speed of the rendering. Finally, the method is illustrated with various 3D examples.

DIVA: Natural Navigation Inside 3D Images Using Virtual Reality

As three-dimensional microscopy becomes commonplace in biological research, there is an increasing need for researchers to be able to view experimental image stacks in a natural three-dimensional viewing context. Through stereoscopy and motion tracking, commercial virtual reality headsets provide a solution to this important visualization challenge by allowing researchers to view volumetric objects in an entirely intuitive fashion. With this motivation, we present DIVA, a user-friendly software tool that automatically creates detailed three-dimensional reconstructions of raw experimental image stacks that are integrated in virtual reality. In DIVA's immersive virtual environment, users can view, manipulate and perform volumetric measurements on their microscopy images as they would to real physical objects. In contrast to similar solutions, our software provides high-quality volume rendering with native TIFF file compatibility. We benchmark the software with diverse image types including those generated by confocal, light-sheet and electron microscopy. DIVA is available at https://diva.pasteur.fr and will be regularly updated.

The Explanatory Visualization Framework: An Active Learning Framework for Teaching Creative Computing Using Explanatory Visualizations.

Visualizations are nowadays appearing in popular media and are used everyday in the workplace. This democratisation of visualization challenges educators to develop effective learning strategies, in order to train the next generation of creative visualization specialists. There is high demand for skilled individuals who can analyse a problem, consider alternative designs, develop new visualizations, and be creative and innovative. Our three-stage framework, leads the learner through a series of tasks, each designed to develop different skills necessary for coming up with creative, innovative, effective, and purposeful visualizations. For that, we get the learners to create an explanatory visualization of an algorithm of their choice. By making an algorithm choice, and by following an active-learning and project-based strategy, the learners take ownership of a particular visualization challenge. They become enthusiastic to develop good results and learn different creative skills on their learning journey.

Retinal detachment repair through multifocal intraocular lens- overcoming visualization challenge of the peripheral retina.

Retinal detachment repair through multifocal intraocular lens- overcoming visualization challenge of the peripheral retina.

Visualization of Metabolic Interaction Networks in Microbial Communities Using VisANT 5.0.

The complexity of metabolic networks in microbial communities poses an unresolved visualization and interpretation challenge. We address this challenge in the newly expanded version of a software tool for the analysis of biological networks, VisANT 5.0. We focus in particular on facilitating the visual exploration of metabolic interaction between microbes in a community, e.g. as predicted by COMETS (Computation of Microbial Ecosystems in Time and Space), a dynamic stoichiometric modeling framework. Using VisANT’s unique metagraph implementation, we show how one can use VisANT 5.0 to explore different time-dependent ecosystem-level metabolic networks. In particular, we analyze the metabolic interaction network between two bacteria previously shown to display an obligate cross-feeding interdependency. In addition, we illustrate how a putative minimal gut microbiome community could be represented in our framework, making it possible to highlight interactions across multiple coexisting species. We envisage that the “symbiotic layout” of VisANT can be employed as a general tool for the analysis of metabolism in complex microbial communities as well as heterogeneous human tissues. VisANT is freely available at: http://visant.bu.edu and COMETS at http://comets.bu.edu.

LayerCake: a tool for the visual comparison of viral deep sequencing data.

The advent of next-generation sequencing (NGS) has created unprecedented opportunities to examine viral populations within individual hosts, among infected individuals and over time. Comparing sequence variability across viral genomes allows for the construction of complex population structures, the analysis of which can yield powerful biological insights. However, the simultaneous display of sequence variation, coverage depth and quality scores across thousands of bases presents a unique visualization challenge that has not been fully met by current NGS analysis tools. Here, we present LayerCake, a self-contained visualization tool that allows for the rapid analysis of variation in viral NGS data. LayerCake enables the user to simultaneously visualize variations in multiple viral populations across entire genomes within a highly customizable framework, drawing attention to pertinent and interesting patterns of variation. We have successfully deployed LayerCake to assist with a variety of different genomics datasets. Program downloads and detailed instructions are available at http://graphics.cs.wisc.edu/WP/layercake under a modified MIT license. LayerCake is a cross-platform tool written in the Processing framework for Java. mcorrell@cs.wisc.edu.

Dual Adjacency Matrix: Exploring Link Groups in Dense Networks

AbstractNode grouping is a common way of adding structure and information to networks that aids their interpretation. However, certain networks benefit from the grouping of links instead of nodes. Link communities, for example, are a form of link groups that describe high‐quality overlapping node communities. There is a conceptual gap between node groups and link groups that poses an interesting visualization challenge. We introduce the Dual Adjacency Matrix to bridge this gap. This matrix combines node and link group techniques via a generalization that also enables it to be coordinated with a node‐link‐contour diagram. These methods have been implemented in a prototype that we evaluated with an information scientist and neuroscientist via interviews and prototype walk‐throughs. We demonstrate this prototype with the analysis of a trade network and an fMRI correlation network.

2013 Visualization Challenge

Science and the National Science Foundation present the winners of the 2013 International Science and Engineering Visualization Challenge.

Diffusion Mapping in Living Cells using Camera-Based Correlation Spectroscopy and Phasor Analysis

Diffusion Mapping in Living Cells using Camera-Based Correlation Spectroscopy and Phasor Analysis

VMD as a Software for Visualization and Quantitative Analysis of Super Resolution Imaging and Single Particle Tracking

Super resolution imaging and high-precision single particle tracking are promising techniques to study biomolecular trafficking and localization as well as intracellular structures. The tremendous amount of data acquired from the experiments pose a great visualization and analysis challenge. VMD, a software for visualizing and analyzing trajectories from molecular dynamics simulations, has the ability to handle hundreds of millions of particles and hundreds of thousands of frames in a time-dependent manner. We extended VMD with new functions for handling data from super-resolution imaging and high-precision single particle tracking experiments and performed visualization and data analysis. The analysis can take advantage of VMD's existing capability to display particles in various representations and to compute system properties employing GPUs. The Tcl/Tk interface in VMD adds a layer of flexibility to implement project-specific functionality specified by users. The use of VMD is demonstrated for two examples: (1) employing STORM to reveal the organization of long non-coding RNAs in nuclear bodies; (2) combining single particle tracking and PALM to study AMPA receptor trafficking at live synapses.

Science Podcast: 1 February Show

Listen to stories on the history of carbon cycling, emergent sensing, the Visualization Challenge, and more.

Photography

Science and the National Science Foundation announce the winners in the photography category in the 2012 International Science & Engineering Visualization Challenge.

Illustration

Science and the National Science Foundation announce the winners in the illustration category in the 2012 International Science & Engineering Visualization Challenge.

2012 Visualization Challenge

[2012 International Science & Engineering Visualization Challenge][1] Ten years ago, Science and the National Science Foundation (NSF) launched a unique experiment: an international competition to recognize the best examples of projects that bring scientific information to life. The goal was to

Video

Science and the National Science Foundation announce the winners in the video category in the 2012 International Science & Engineering Visualization Challenge.