Visualization of scattered meteorological data

Considers how rain-gauge data, scattered in two dimensions, aid the study of El Nino-caused rainstorms in normally arid coastal Peru. Continuous realization techniques can extract qualitative information from the data. The techniques described were developed with IBM Visualization Data Explorer, a general-purpose software package for scientific data visualization and analysis. Data Explorer provides tools for both scattered and gridded data     

Visualization of 3D ultrasound data

It is suggested that ultrasound data acquisition will play an increasing role in the future of medical imaging. Unlike magnetic resonance imaging (MRI) and computerized tomography (CT), ultrasound offers interactive visualization of underlying anatomy in real time. Additionally, ultrasound equipment costs far less and does not use ionizing radiation or require specialized facilities. The different methods for multidimensional medical imaging and scientific visualization are reviewed. Several volume visualization algorithms are discussed. They are multiplexer slicing, surface fitting, volume rendering, data classification, and viewing and shading. Three-dimensional ultrasound data display methods are also discussed     

Visualization of complex automotive data.

Making complicated data easier to understand has always been a challenge. Four types of visualization applications (CAD, generalized, specialized, and custom) have successfully been used by automotive manufacturers such as General Motors to help meet this goal. Here are some ways that common processes can be developed for all types of visualization.     

Visualization of spherical data by Yin-Yang grid

Visualization in the spherical geometry is ubiquitous in geophysical data processing. For the spherical visualization, the commonly used spherical polar coordinate system is not ideal due to its grid convergence nature near the poles. We propose to use a spherical overset grid system called Yin-Yang grid as the base grid system of the spherical visualization. The convergence-free nature of the Yin-Yang grid leads to a balanced data distribution and effective visualization processing in a sphere. The Yin-Yang grid is already used in various geophysical simulations including the geodynamo and mantle convection in the spherical geometry. Data produced by the Yin-Yang grid can be, and should be, visualized directly on the same Yin-Yang grid system without any data remapping. Since the component grid of the Yin-Yang grid is a part of (or low latitude region of) the standard spherical polar coordinate system, it is straightforward to convert an existing spherical visualization tool based on the spherical polar coordinates into a tool based on the Yin-Yang grid.     

Visualization of AMR data with multi-level dual-mesh interpolation

We present a new technique for providing interpolation within cell-centered Adaptive Mesh Refinement (AMR) data that achieves C(0) continuity throughout the 3D domain. Our technique improves on earlier work in that it does not require that adjacent patches differ by at most one refinement level. Our approach takes the dual of each mesh patch and generates "stitching cells" on the fly to fill the gaps between dual meshes. We demonstrate applications of our technique with data from Enzo, an AMR cosmological structure formation simulation code. We show ray-cast visualizations that include contributions from particle data (dark matter and stars, also output by Enzo) and gridded hydrodynamic data. We also show results from isosurface studies, including surfaces in regions where adjacent patches differ by more than one refinement level.     

Visualization of scientific video data using KL decomposition

Fast methods are developed for visualizing and classifying certain types of scientific video data. These techniques, which are based on Karhunen-Loe`ve (KL) decomposition, find a best coordinate system for a data set. When the data set represents a temporally ordered collection of images, the best coordinate system leads to approximations that are separable in time and space. Practical methods for computing this best coordinate system are discussed, and physically significant visualizations for experimental video data are developed. The visualization techniques are applied to two experimental systems-one from combustion and the other from neurobiology-to show how relevant information can be quickly extracted from video data. These techniques can be integrated into the video acquisition process to provide real-time feedback to the experimentalist during the operation of an experiment     

Visualization of diversity in large multivariate data sets

Understanding the diversity of a set of multivariate objects is an important problem in many domains, including ecology, college admissions, investing, machine learning, and others. However, to date, very little work has been done to help users achieve this kind of understanding. Visual representation is especially appealing for this task because it offers the potential to allow users to efficiently observe the objects of interest in a direct and holistic way. Thus, in this paper, we attempt to formalize the problem of visualizing the diversity of a large (more than 1000 objects), multivariate (more than 5 attributes) data set as one worth deeper investigation by the information visualization community. In doing so, we contribute a precise definition of diversity, a set of requirements for diversity visualizations based on this definition, and a formal user study design intended to evaluate the capacity of a visual representation for communicating diversity information. Our primary contribution, however, is a visual representation, called the Diversity Map, for visualizing diversity. An evaluation of the Diversity Map using our study design shows that users can judge elements of diversity consistently and as or more accurately than when using the only other representation specifically designed to visualize diversity.     

基于数据管技术的证券数据可视化

数据管技术是一门新的可视化技术，用三维管状图形表示数据集，将数据映射到管状图的内壁，用户可在数据管内移动，并根据颜色来探测数据。介绍了数据管技术的核心部分4种数据转换及其在证券数据中的应用。     

Visualization of time-dependent data with feature tracking and event detection

This paper presents an innovative method to analyze and visualize time-dependent evolution of features. The analysis and visualization of time-dependent data are complicated because of the immense number of data involved. However, if the scientist's main interest is the evolution of certain features, it suffices to show the evolution of these features. The task of the visualization method is to extract the features from all frames, to determine the correspondences between features in successive frames, to detect significant events or stages in the evolution of the features, and, finally, to visualize the results. The method described here performs all these steps, and it is applied to a number of applications.     

Visualization and clustering of categorical data with probabilistic self-organizing map

This paper introduces a self-organizing map dedicated to clustering, analysis and visualization of categorical data. Usually, when dealing with categorical data, topological maps use an encoding stage: categorical data are changed into numerical vectors and traditional numerical algorithms (SOM) are run. In the present paper, we propose a novel probabilistic formalism of Kohonen map dedicated to categorical data where neurons are represented by probability tables. We do not need to use any coding to encode variables. We evaluate the effectiveness of our model in four examples using real data. Our experiments show that our model provides a good quality of results when dealing with categorical data.     

Visualization and 3D data processing in the David restoration

The program of scientific investigations planned in the framework of the restoration of Michelangelo's David produced several useful guidelines for defining and developing innovative ways to process and visualize 3D data in cultural heritage applications. Our ultimate goal was to include 3D graphics among the tools which can help restorers select the proper restoration procedures for the task at hand and objectively assess restoration results. For this, the David restoration was an ideal test bed to demonstrate the usefulness of digital 3D models and visualization tools in a restoration project. Because a complex set of scientific investigations was planned before and after the restoration intervention, we could try various methodologies to support restorers and scientists with visualization tools based on 3D digital models.     

基于Flask框架的疫情数据可视化分析

在新冠肺炎疫情背景下,通过数据爬虫技术获取开源的疫情数据,经数据处理后形成数据集,利用可视化技术进行数据可视化与数据分析.介绍了数据爬取与处理方法,利用Python语言的Flask框架等可视化技术完成疫情数据可视化,从多角度、多方面展示与分析疫情数据.帮助民众充分了解全国各地的疫情情况、疫情发展趋势以及疫苗接种情况.     

Visualization of experimental data at the Naval Research Laboratory

The role of scientific visualization in understanding experimental data sets is examined. The difficulty in extracting parameters of interest from the measurements is described for five diverse application areas: physical oceanography, electronic warfare, molecular modeling, underwater acoustics, and synthetic-aperture radar. The role of digital imaging and signal processing is noted     

基于螺旋图的时间序列数据可视化

阶段性时间序列数据是一种生活中常见数据形式,它描述一个包含多个状态转换的事件,每个状态都具有时间属性,且状态之间的转换存在多条路径。针对现有的可视化方法不能有效展示各个状态之间变化以及状态间路径的时间属性信息的问题,提出一个全新的基于螺旋图的可视化模型。该模型使用一个圆环表示一个状态,一个事件的多个状态采用一组同心圆表示,状态间可达路径采用螺旋线表示,螺旋线的起始位置由其起始时间与起始状态圆环决定,终止位置由其结束时间与结束状态圆环决定。针对路径过多导致路径覆盖较为严重的问题,该模型采用基于长尾函数的透明算法,根据一条路径与其他路径的交叉数,为每条路径分配透明度。该模型还提供了路径的筛选、高亮、查看详细信息、缩放等功能,实现了灵活的交互操作。通过对中国铁路列车站点数据进行实验,实验结果表明该模型能够在有限的空间中有效地展示站点间运行任意时长的列车,并且在列车较多的情况下降低了螺旋线交叉重叠带来的杂乱度,同时有效地保留了列车的运行信息,能够为用户路线的选择提供决策支持,说明了该模型对阶段性时间序列数据可视化的有效性。     

基于递归模式技术的股票数据可视化

可视化技术对于分析和探究大规模的多维数据集变得越来越重要，其中最重要的一种可视化技术是一种面向像素的可视化技术，其基本原理是将数据集中的每个数据值映射成屏幕上的一个像素并对这些像素按一定的规则充分地加以排列，以便将尽可能多的数据对象以人们熟悉的图形图像展现在屏幕上。递归模式技术是面向像素的可视化技术的一种，它基于简单地来回排列，允许用户参与定义结构和设置参数，主要适用于有自然顺序的数据集。在股票数据分析中，利用递归模式技术比较容易描述交易数据库中股票价格的变化情况，并预测股票的走势。     

Visualization of (multimedia) dependencies from big data

Multimedia Tools and Applications - Data dependencies represent one of the key metadata to characterize and profile multimedia and big data sources. With respect to traditional databases, in these...     

Visualization of multivariate data with radial plots using SAS

Data visualization tools can provide very powerful information and insight when performing data analysis. In many situations, a set of data can be adequately analyzed through data visualization methods alone. In other situations, data visualization can be used for preliminary data analysis. In this paper, radial plots are developed as a SAS-based data visualization tool that can improve one's ability to monitor, analyze and control a process. Using the program developed in this research, we present two examples of data analysis using radial plots; the first example is based on data from a particle board manufacturing process and the second example is a business process for monitoring the time-varying level of stock return data.