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At least 253 records · Page 14

The Importance of Data Visualization: Incorporating Storytelling into the Scientific Presentation

From its inception in 2000, one of the primary tasks of the Biomedical Data Reduction Analysis (BDRA) group has been translation of large amounts of data into information that is relevant to the audience receiving it. BDRA helps translate data into an integrated model that supports both operational and research activities. This data integrated model and subsequent visual data presentations have contributed to BDRA's success in delivering the message (i.e., the story) that its customers have needed to communicate. This success has led to additional collaborations among groups that had previously not felt they had much in common until they worked together to develop solutions in an integrated fashion. As more emphasis is placed on working with "big data" and on showing how NASA's efforts contribute to the greater good of the American people and of the world, it becomes imperative to visualize the story of our data to communicate the greater message we need to share. METHODS To create and expand its data integrated model, BDRA has incorporated data from many different collaborating partner labs and other sources. Data are compiled from the repositories of the Lifetime Surveillance of Astronaut Health and the Life Sciences Data Archive, and from the individual laboratories at Johnson Space Center that support collection of data from medical testing, environmental monitoring, and countermeasures, as designated in the Medical Requirements Integration Documents. Ongoing communication with the participating collaborators is maintained to ensure that the message and story of the data are retained as data are translated into information and visual data presentations are delivered in different venues and to different audiences. RESULTS We will describe the importance of storytelling through an integrated model and of subsequent data visualizations in today's scientific presentations and discuss the collaborative methods used. We will illustrate the discussion with examples of graphs from BDRA's past work supporting operations and/or research efforts.

Babiak-Vazquez, A.↗

Fostering Remote Visualization: Experiences in Two Different HPC Sites

Visualization of scientific data is crucial for scientific discovery to gain insight into the results of simulations and experiments. Remote visualization is of crucial importance to access infrastructure, data and computational resources and, to avoid data movement from where data is produced and to where data will be analyzed. Remote visualization enables geographically diverse collaboration and enhances user experience through graphical user interfaces. This paper presents two approaches deployed by two different HPC centers: The SC3 - Supercomputación y Cálculo Científico Center in Colombia and the Oak Ridge Leadership Computing Facility in USA. We overview our remote visualization experiences, adopted technologies, use cases, and challenges encountered. Our contribution is to signal the commonality between approaches in terms of the end goal, showing their fitness for their contexts, while not focusing only on attempting to provide a general picture of remote visualization, given the differences between centers in terms of purposes, needs, resources, and national impact.

Gelvez Cortes, Sergio Augusto↗

Interactive Visualization of Complex Seismic Data and Models Using Bokeh

Visualizing multidimensional data and models becomes more challenging as the volume and resolution of seismic data and models increase. But thanks to the development of powerful and accessible computer systems, a model web browser can be used to visualize complex scientific data and models dynamically. In this paper, we present four examples of seismic model visualization using an open-source Python package Bokeh. One example is a visualization of a surface-wave dispersion data set, another presents a view of three-component seismograms, and two illustrate methods to explore a 3D seismic-velocity model. Unlike other 3D visualization packages, our visualization approach has a minimum requirement on users and is relatively easy to develop, provided you have reasonable programming skills. Finally, utilizing familiar web browsing interfaces, the dynamic tools provide us an effective and efficient approach to explore large data sets and models.

58 GEOSCIENCES↗

Visualization Quality Assessment

Understanding how inaccuracies in visualizations affect users’ perception and understanding of scientific data is hard. Inaccuracies in visualizations are quite common and could arise from a range of sources such as errors in the original dataset arising from compression artifacts, errors in the capturing device, noise during transmission of the data, effects due to the algorithm being used to convert data to visualization images, images generated from neural networks, and sources we have yet to discover. Many image quality assessment metrics have been developed to quantify image errors. However, these are usually focused on “natural images” rather than visualizations of scientific data. Common image quality assessment metrics (IQAs) include MSE, PSNR, perceptual metrics such SSIM, FSIM as well as perceptual metrics using deep learning approaches. However, a critical part of understanding how errors are perceived by humans, and subsequently developing more accurate quality assessment metrics, is through user evaluation studies. The goal of this software is to develop a visualization quality assessment (VQA) process that will enable the generation of VQAs that can be used to quantify errors in scientific data visualizations. The VQA development process will include software to support user evaluation experimental design, analysis of visualization differences against standard quality metrics, and the ability to develop additional VQA metrics specific to scientific visualization images.

Grosset, Andre↗

Improving Scientific Data Analysis Through Multi-touch Enabled Interactive Data Visualization with Applications to Neutron Science

Scientific data analysis is an inherently exploratory process that requires flexible human interaction with data visualization and anal- ysis tools. In this paper, we describe challenges in neutron scattering data analysis and present our approach for allowing more effective human interaction. In addition to multi-touch enabled data visualiza- tion techniques, we describe color scale enhancements, layouts, and visual analytics approaches for 3D volume slicing. Since challenges in neutron science are echoed in most scientific fields, we generalize the project objective and present a case for bridging the gap between the latest advances in interactive data visualization and practical scientific scenarios where new critical knowledge is buried in large volumes of complex data.

Steed, Chad↗

ExaWind at NREL: Upping the Ante

The objective of the ExaWind component of the Exascale Computing Project is to deliver many-turbine blade-resolved simulations in complex terrain. These simulations bring new challenges to both compute and analysis of the resulting data. In this paper/video, we visually explore the impact of ExaWind on wind simulations through two studies of a small wind farm under two atmospheric conditions. We then turn to analysis and review tools that visualization researchers at NREL use to answer the challenges that ExaWind brings.

collaborative visualization↗

State of the Art of Molecular Visualization in Immersive Virtual Environments

Abstract Visualization plays a crucial role in molecular and structural biology. It has been successfully applied to a variety of tasks, including structural analysis and interactive drug design. While some of the challenges in this area can be overcome with more advanced visualization and interaction techniques, others are challenging primarily due to the limitations of the hardware devices used to interact with the visualized content. Consequently, visualization researchers are increasingly trying to take advantage of new technologies to facilitate the work of domain scientists. Some typical problems associated with classic 2D interfaces, such as regular desktop computers, are a lack of natural spatial understanding and interaction, and a limited field of view. These problems could be solved by immersive virtual environments and corresponding hardware, such as virtual reality head‐mounted displays. Thus, researchers are investigating the potential of immersive virtual environments in the field of molecular visualization. There is already a body of work ranging from educational approaches to protein visualization to applications for collaborative drug design. This review focuses on molecular visualization in immersive virtual environments as a whole, aiming to cover this area comprehensively. We divide the existing papers into different groups based on their application areas, and types of tasks performed. Furthermore, we also include a list of available software tools. We conclude the report with a discussion of potential future research on molecular visualization in immersive environments.

97 MATHEMATICS AND COMPUTING↗

Advanced visualization techniques

The scientific computing needs of the Earth Science and Application Division (ESAD) were evaluated, and it was determined whether the existing visualization environment provides the proper tools for meeting those needs. Some of the deficiencies were corrected using off-the-shelf software. The following subject areas are covered: (1) evaluation of visualization environment at ESAD; (2) definition of science needs; (3) evaluation of available sortware/hardware; and (4) definition of software development environment.

Botts, Mike↗

Visualization of Jet Impingement and Ignition in a Piston-Cylinder Chamber

The transportation sector accounts for almost a third of the United States energy consumption. We are developing predictive simulations of the complex in-cylinder processes of internal combustion engines to improve performance and decrease pollutant emissions. Using volume rendering, we provide a first look at the jet impingement and ignition inside a piston-cylinder chamber. Through the visualization, we were able to construct a complete 3D picture of the jet impingement on the piston-bowl walls leading to the formation of pockets of auto-ignition of fuel-air mixture. These auto-ignition pockets subsequently lead to flame stabilization releasing the chemical energy for conversion to useful work. A detailed physical picture of flame stabilization as provided by the visualization techniques presented in this study help in the design next-generation internal combustion engines.

91 SC - Advanced Scientific Computing Reseach (ASC↗

Visualization of Jet Impingement and Ignition in a Piston-Cylinder Chamber

The transportation sector accounts for almost a third of the United States' energy consumption. We are developing predictive simulations of the complex in-cylinder processes of internal combustion engines to improve performance and decrease pollutant emissions. We provide a first look at the jet impingement and ignition inside a piston-cylinder chamber using volume rendering. Through the visualization, we constructed a complete 3D picture of the jet impingement on the piston-bowl walls leading to the formation of pockets of auto-ignition of the fuel-air mixture. These auto-ignition pockets subsequently lead to flame stabilization, releasing the chemical energy for conversion to useful work. A detailed physical picture of flame stabilization, as provided by the visualization techniques presented in this study, help in the design of next-generation internal combustion engines.

91 SC - Advanced Scientific Computing Reseach (ASC↗

DataHub--Knowledge-Based Science Data Management for Exploratory Data Analysis

It is our belief that new modes of research and new tools will be required to handle the massive amount of diverse data that is to be stored, organized, accessed, distributed, visualized, and analyzed. The fundamental innovation required is the integration of three automation technologies, videlicet knowledge-based expert systems, science visualization and science data management. This integration is based on a concept caled the DataHub, which we describe here.

DataHub↗

A distributed analysis and visualization system for model and observational data

Software was developed with NASA support to aid in the analysis and display of the massive amounts of data generated from satellites, observational field programs, and from model simulations. This software was developed in the context of the PATHFINDER (Probing ATmospHeric Flows in an Interactive and Distributed EnviRonment) Project. The overall aim of this project is to create a flexible, modular, and distributed environment for data handling, modeling simulations, data analysis, and visualization of atmospheric and fluid flows. Software completed with NASA support includes GEMPAK analysis, data handling, and display modules for which collaborators at NASA had primary responsibility, and prototype software modules for three-dimensional interactive and distributed control and display as well as data handling, for which NSCA was responsible. Overall process control was handled through a scientific and visualization application builder from Silicon Graphics known as the Iris Explorer. In addition, the GEMPAK related work (GEMVIS) was also ported to the Advanced Visualization System (AVS) application builder. Many modules were developed to enhance those already available in Iris Explorer including HDF file support, improved visualization and display, simple lattice math, and the handling of metadata through development of a new grid datatype. Complete source and runtime binaries along with on-line documentation is available via the World Wide Web at: http://redrock.ncsa.uiuc.edu/ PATHFINDER/pathre12/top/top.html.

Wilhelmson, Robert B.↗

Scanning Probe Microscopy in the Information Age

Scanning probe microscopy (SPM) has brought scientific exploration, visualization, and control to nanoscale. A plethora of measurement approaches and techniques devised around SPM enabled probing structure and functionalities crucial for virtually all areas of science. While high-resolution electron microscopy techniques preceded scanning probes, SPM effectively opened the door to probing the structure–property relationship on length scales spanning 100s of micrometers down to a single atom. As the complexity of the material systems and the scientific questions increased, so too did the SPM techniques. Substantial efforts have been dedicated toward the development of better instrumentation platforms, probes, and novel spectroscopic measurements; however, many opportunities related to data processing and acquisition in SPM are just being realized now. This chapter will describe the recent progress in data-driven SPM by giving a broad overview of the field, the foundation of the scanning tunneling microscope (STM) and the atomic force microscope (AFM), as well as a description behind the operating principles and dynamic modes. A comprehensive overview of the multi-frequency techniques, Band excitation, and general acquisition mode SPM is given, setting the context for the application of big data, machine learning, and artificial intelligence in the field of dynamic SPM.

Collins, Liam↗

Preparing for In Situ Processing on Upcoming Leading-edge Supercomputers

High performance computing applications are producing increasingly large amounts of data and placing enormous stress on current capabilities for traditional post-hoc visualization techniques. Because of the growing compute and I/O imbalance, data reductions, including in situ visualization, are required. These reduced data are used for analysis and visualization in a variety of different ways. Many of he visualization and analysis requirements are known a priori, but when they are not, scientists are dependent on the reduced data to accurately represent the simulation in post hoc analysis. The contributions of this paper is a description of the directions we are pursuing to assist a large scale fusion simulation code succeed on the next generation of supercomputers. Finally, these directions include the role of in situ processing for performing data reductions, as well as the tradeoffs between data size and data integrity within the context of complex operations in a typical scientific workflow.

97 MATHEMATICS AND COMPUTING↗

View-Dependent Streamline Deformation and Exploration

Occlusion presents a major challenge in visualizing 3D flow and tensor fields using streamlines. Displaying too many streamlines creates a dense visualization filled with occluded structures, but displaying too few streams risks losing important features. We propose a new streamline exploration approach by visually manipulating the cluttered streamlines by pulling visible layers apart and revealing the hidden structures underneath. Here this paper presents a customized view-dependent deformation algorithm and an interactive visualization tool to minimize visual cluttering for visualizing 3D vector and tensor fields. The algorithm is able to maintain the overall integrity of the fields and expose previously hidden structures. Our system supports both mouse and direct-touch interactions to manipulate the viewing perspectives and visualize the streamlines in depth. By using a lens metaphor of different shapes to select the transition zone of the targeted area interactively, the users can move their focus and examine the vector or tensor field freely.

97 MATHEMATICS AND COMPUTING↗