Visual Debugging Techniques for Reactive Data Visualization

Interaction is critical to effective visualization, but can be difficult to author and debug due to dependencies among input events, program state, and visual output. Recent advances leverage reactive semantics to support declarative design and avoid the “spaghetti code” of imperative event handlers. While reactive programming improves many aspects of development, textual specifications still fail to convey the complex runtime dynamics. In response, we contribute a set of visual debugging techniques to reveal the runtime behavior of reactive visualizations. A timeline view records input events and dynamic variable updates, allowing designers to replay and inspect the propagation of values step‐by‐step. On‐demand annotations overlay the output visualization to expose relevant state and scale mappings in‐situ. Dynamic tables visualize how backing datasets change over time. To evaluate the effectiveness of these techniques, we study how first‐time Vega users debug interactions in faulty, unfamiliar specifications; with no prior knowledge, participants were able to accurately trace errors through the specification.     

医学体数据三维可视化技术

医学体数据的可视化是科学计算可视化的重要研究领域,其处理过程包括体数据的获取、模型的建立、数据的映射、绘制等操作。论文对医学体数据可视化的相关技术进行了综述,讨论了医学体数据的结构模型和表示方法,全面地分析了医学体数据可视化中各种算法和技术的特点,及相关的加速技术,探讨了目前医学体数据可视化存在的问题及发展趋势。     

Open-Source Tools for Immersive Environmental Visualization

Scientists of the Desert Research Institute's atmospheric, hydrological, and earth and ecosystem science divisions sift through vast amounts of data gathered from sophisticated instrumentation and computational models. To help address the data analysis needs that stem from the growing volume of data, DRI established the center for advanced visualization, computation, and modeling (CAVCaM) to foster DRI's move into interactive, large-scale, 3D visualization of these and other environmental research issues. Our mission is two-pronged. First, we seek to partner with our researcher collaborators at DRI and the larger scientific communities through the development and use of better visualization tools. Second, we work with research sponsors to create visualization applications for training and simulation     

Phase Ambiguity Correction and Visualization Techniques for Complex-Valued ICA of Group fMRI Data

Analysis of functional magnetic resonance imaging (fMRI) data in its native, complex form has been shown to increase the sensitivity both for data-driven techniques, such as independent component analysis (ICA), and for model-driven techniques. The promise of an increase in sensitivity and specificity in clinical studies, provides a powerful motivation for utilizing both the phase and magnitude data; however, the unknown and noisy nature of the phase poses a challenge. In addition, many complex-valued analysis algorithms, such as ICA, suffer from an inherent phase ambiguity, which introduces additional difficulty for group analysis. We present solutions for these issues, which have been among the main reasons phase information has been traditionally discarded, and show their effectiveness when used as part of a complex-valued group ICA algorithm application. The methods we present thus allow the development of new fully complex data-driven and semi-blind methods to process, analyze, and visualize fMRI data.We first introduce a phase ambiguity correction scheme that can be either applied subsequent to ICA of fMRI data or can be incorporated into the ICA algorithm in the form of prior information to eliminate the need for further processing for phase correction. We also present a Mahalanobis distance-based thresholding method, which incorporates both magnitude and phase information into a single threshold, that can be used to increase the sensitivity in the identification of voxels of interest. This method shows particular promise for identifying voxels with significant susceptibility changes but that are located in low magnitude (i.e. activation) areas. We demonstrate the performance gain of the introduced methods on actual fMRI data.     

Requirements-Based Visualization Tools for Software Maintenance and Evolution

Developing well-formed software visualization tools requires increased empirical study of programmers' information requirements.     

Visualization Techniques for Schedule Comparison

Project schedules are effectively represented by Gantt charts, but comparing multiple versions of a schedule is difficult. To compare versions with current methods, users must search and navigate through multiple large documents, making it difficult to identify differences. We present two novel visualization techniques to support the comparison of Gantt charts. First, we encode two Gantt charts in one view by overlapping them to show differences. Second, we designed an interactive visual technique, the 'TbarView', that allows users to compare multiple schedules within one single view. We evaluated the overlap and TbarView techniques via a user study. The study results showed that our design provided a quick overview of the variances among two or more schedules, and the techniques also improved efficiency by minimizing view switching. Our visual techniques for schedule comparison could be combined with other resource analysis tools to help project teams identify and resolve errors and problems in project schedules.     

数据可视化技术及其在过程冶金中的CFD应用

数据可视化是计算机学科的一个重要研究方向,文章简要介绍了数据可视化的概念、研究现状,结合数据可视化技术在过程冶金中的CFD(Computational Fluid Dynamic)应用,详细介绍了计算数据(速度场、温度场、浓度场等)的可视化方法、程序实现及其特点。     

Data, Information, and Knowledge in Visualization

In visualization, we use the terms data, information and knowledge extensively, often in an interrelated context. In many cases, they indicate different levels of abstraction, understanding, or truthfulness. For example, "visualization is concerned with exploring data and information," "the primary objective in data visualization is to gain insight into an information space," and "information visualization" is for "data mining and knowledge discovery." In other cases, these three terms indicate data types, for instance, as adjectives in noun phrases, such as data visualization, information visualization, and knowledge visualization. These examples suggest that data, information, and knowledge could serve as both the input and output of a visualization process, raising questions about their exact role in visualization.     

Deformable Surface Techniques for Field Visualization

Surface extraction from data fields is often used in scientific visualization, as surfaces can represent meaningful information and they are well suited for display. This paper describes a general method for localized surface extraction from scalar and vector fields. An initial polygonal surface is placed within the field, and the shape of the surface is adapted to the field by iterative displacement of surface nodes according to a displacement criterion. To achieve a good approximation of a smooth surface, the polygon mesh can be locally refined during iteration. The type of surface extracted depends on the displacement criterion, which can be any function of the available field variables. Techniques for displacement and mesh refinement are discussed in detail. The results we show are generation of a local isosurface and extraction of a vortex tube. Finally, we will draw conclusions and discuss some issues for further development.     

一种多维数据的可视化技术及其实现

引入了数据可视化概念,以聚类挖掘K-Means算法为例,实现了一种将N维数据向3维空间点坐标转换的方法;并利用图形软件开发包DirectX8.1将得到的点集合在屏幕上绘制出来,描述了挖掘结果,最终实现了结果的可视化;此外,也对本实验方法的优点和有待改进的地方做了总结.     

Adaptive Scientific Visualization Tools for a Smart Paleontological Museum

Programming and Computer Software - This paper is devoted to the development of tools that allow museum workers to create interactive exhibits by using the Internet of Things (IoT) technology. We...     

数据挖掘工具的分类与挖掘

随着数据挖掘技术的发展,各种各样的数据挖掘工具不断开发出来,如何把握这些工具的功能、挖掘技术和未来发展趋势,是一个非常困难的事情。文中借助数据挖掘技术提出了数据挖掘软件工具的一个多维立方体分类模型,给出了一个具体分类实例,总结出数据挖掘工具的技术发展路线和未来发展趋势,并通过对三个不同阶段的数据挖掘工具的深入比较,进一步验证了文中的结论。     

数据挖掘工具的分类与挖掘

随着数据挖掘技术的发展，各种各样的数据挖掘工具不断开发出来，如何把握这些工具的功能、挖掘技术和未来发展趋势，是一个非常困难的事情。文中借助数据挖掘技术提出了数据挖掘软件工具的一个多维立方体分类模型，给出了一个具体分类实例，总结出数据挖掘工具的技术发展路线和未来发展趋势，并通过对三个不同阶段的数据挖掘工具的深入比较，进一步验证了文中的结论。     

一种多维数据的聚类算法及其可视化研究

提出了一种基于主次属性划分的聚类方法和一种新的数据可视化方法.首先,利用数据的主属性和次属性的特征值对数据集进行聚类;然后,采用彩色刺激光谱投影到RGB颜色空间的原理,通过色度学中麦克斯韦的三角平面坐标色度图对各聚类结果进行可视化显示.实验证明了文中方法算法简单、容易实现,可视化结果有利于用户全面地理解数据,为数据的预测、决策起到重要作用.     

Empirical Study of a 3D Visualization for Information Retrieval Tasks

There are many challenges to visualizing information including choosing between 2D and 3D interfaces, navigation and interaction methods, and selecting an appropriate level of detail. Visualizing information retrieval (IR) search results, including Web search engine results, poses additional challenges, notably the determination of appropriate relative locations for terms and document in a visual display. Latent Semantic Indexing (LSI) and related techniques offer approaches to visualizing relations among terms and documents. In this work, information space is presented as a framework for discussing relations among terms and documents, and a technique related to LSI is utilized to generate information spaces from IR search results. This paper provides an overview of more than three decades of work on information visualization, identifying several trends and some relatively unexplored areas. An experimental evaluation of a prototype interface for visualizing IR results is described. Results indicate that the 3D navigation interface for IR search results was usable, but that subjects had difficulty with some aspects. Further study and development of 2D and 3D methods for interacting with retrieval search results is suggested.     

Tools for Analyzing Microarray Expression Data

Microarray technologies have emerged as key tools for genomic expression analysis for the purposes of studying disease states, identifying drug targets, and profiling time-, tissue- or stage-dependent changes. The resulting volume of data generated necessitates the use of bioinformatics tools to find interesting gene expression patterns, to identify statistically significant changes across experiments, and to provide additional tools relevant to data mining.We have developed a comprehensive workbench solution, GeneSpring™, which (1) comes with an intuitive interface incorporating organized file management, (2) handles data from multiple array formats, (3) includes multiple data display formats, (4) includes a suite of statistical clustering tools, and (5) incorporates automated annotation and cross-referencing.We will discuss the set of algorithms collectively designed to facilitate gene function identification from large scale genomic expression experiments.     

Four-Dimensional Processing Tools for Cardiovascular Data

A system capable of displaying animated, interactive, 3-D images of the human cardiovascular system is nearing completion?a system that uses only well-established technologies.     

船舶海浪中非线性随机运动的可视化技术

研究船舶海浪中运动的可视化技术.通过采用船舶在海浪中运动的可视化技术,可以使船舶设计人员能够更直观地了解船舶的运动性能.采用具有平台独立性的OpenGL图形库对船舶在波浪中运动的可视化进行描述,讨论了建立船舶模型的可行方法和如何建立三维波浪的数学模型.考虑随机波浪及船舶的非线性阻尼、非线性恢复力矩,建立船舶横摇运动的非线性微分方程.采用Runge-Kutta方法求解非线性微分方程,根据数值模拟结果,应用OpenGL中的函数来生成船舶在海浪中运动的动画.所开发的程序模拟的船舶和波浪是三维的,可以对不同有义波高的波浪和不同船舶的运动进行模拟.