NodeTrix: a hybrid visualization of social networks

The need to visualize large social networks is growing as hardware capabilities make analyzing large networks feasible and many new data sets become available. Unfortunately, the visualizations in existing systems do not satisfactorily resolve the basic dilemma of being readable both for the global structure of the network and also for detailed analysis of local communities. To address this problem, we present NodeTrix, a hybrid representation for networks that combines the advantages of two traditional representations: node-link diagrams are used to show the global structure of a network, while arbitrary portions of the network can be shown as adjacency matrices to better support the analysis of communities. A key contribution is a set of interaction techniques. These allow analysts to create a NodeTrix visualization by dragging selections to and from node-link and matrix forms, and to flexibly manipulate the NodeTrix representation to explore the dataset and create meaningful summary visualizations of their findings. Finally, we present a case study applying NodeTrix to the analysis of the InfoVis 2004 coauthorship dataset to illustrate the capabilities of NodeTrix as both an exploration tool and an effective means of communicating results.     

一个基于Web的轻量级大数据处理与可视化工具

科研人员在日常研究中经常使用Excel,Spss等工具对数据进行分析加工来获得相关领域知识。然而随着大数据时代的到来,常用的数据处理软件因单机性能的限制已经不能满足科研人员对大数据分析处理的需求。大数据的处理和可视化离不开分布式计算环境。因此,为了完成对大数据的快速处理和可视化,科研人员不仅需要购置、维护分布式集群环境,还需要具备分布式环境下的编程能力和相应的前端数据可视化技术。这对很多非计算机科班的数据分析工作者而言是非常困难且不必要的。针对上述问题,提出了一种基于Web的轻量级大数据处理和可视化工具。通过该工具,数据分析工作者只需通过简单的点击和拖动,便可以在浏览器中轻松地打开大型数据文件(GB级别)、快速地对文件进行定位(跳转到文件某一行)、方便地调用分布式计算框架来对文件内容进行排序或求极大值、便捷地对数据进行可视化等。 实证研究证明,该解决方案是有效的。     

网格环境下银河系铁元素丰度梯度的统计分析

铁元素丰度梯度统计分析是网格环境下银河系化学演化研究的一个重要内容,作为虚拟天文台应用系统中在大量数据资源的基础上开展深层次的分析和处理的一个示例。网格环境下银河系铁元素丰度梯度的统计分析实现包括注册服务、数据服务、恒星轨道计算服务和可视化服务等网格服务,组成一个完整的网格应用系统。该文详细描述了数据服务、轨道计算服务和可视化服务的设计和实现,示例展示了在分布、异构和动态的网格环境下,如何通过网格服务的方式有效地实现资源共享和科学数据的高效利用。     

A scene graph based visualization method for representing continuous simulation data

This paper proposes a scene graph based visualization method that can verify time-varying continuous analysis simulation in a virtual reality (VR) environment by using the computer-aided engineering (CAE) data of structural analysis in product development. In previous research, the use of CAE analysis data has been problematic because of the lack of any interactive simulation controls for visualizing continuous simulation data. Moreover, the research on post-processing methods for real-time evaluation of CAE analysis data has not been sufficient. We therefore propose a scene graph based visualization method for representing continuous simulation data. The method can continuously visualize static analysis data independently of any timeline; it can also continuously visualize dynamic analysis data that varies in relation to the timeline. The visualization system for continuous simulation data, which includes CAE2VR Middleware that interfaces with various formats of CAE analysis data as well as functions for visualizing continuous simulation data and operational functions, enables users to verify simulation results with more realistic scenes.     

Designing for social data analysis

The NameVoyager, a Web-based visualization of historical trends in baby naming, has proven remarkably popular. We describe design decisions behind the application and lessons learned in creating an application that makes do-it-yourself data mining popular. The prime lesson, it is hypothesized, is that an information visualization tool may be fruitfully viewed not as a tool but as part of an online social environment. In other words, to design a successful exploratory data analysis tool, one good strategy is to create a system that enables "social" data analysis. We end by discussing the design of an extension of the NameVoyager to a more complex data set, in which the principles of social data analysis played a guiding role.     

一种环境质量数据可视化与可视分析系统

随着全球环境气候的日益严峻,迫切需要通过环境信息化手段来为政府相关部门在保护环境、规划社会发展等方面提供决策支持,环境质量数据可视化与可视分析技术在环境信息化过程中起着举足轻重的作用。本文主要从可视化和可视分析的角度介绍所设计和实现的系统的体系结构和功能,并对系统的关键技术进行重点讨论。实例结果表明,该系统在多源环境质量数据的可视化建模、组织方式和数据的二三维可视化展现以及数据的动态调度、三维场景的实时渲染等方面都有独特的解决方案,系统可以全方位地展现环境质量数据中的信息,实现对综合多源环境质量数据进行分析。     

地热资源管理信息系统的设计与实现

地热资源是一种宝贵的清洁能源。为了地热资源开发和管理的科学性,实现地热资源的可持续开发利用,该文设计并实现一个集办公自动化、MIS、三维、2.5维、二维GIS于一体,集成地热各种评价和预测模型,实现地热资源数据的采集、处理、表达、解释、分析和决策的混合型(GIS)地理信息系统。     

Data Visualization: Featuring Interactive Visual Analysis

Data visualization is an application‐driven field, that is always trying to satisfy its customers and to adapt to the demands, cultures, and workflows of many application areas. Therefore, it is difficult to keep focus on techniques and approaches that are not too application specific. A lot of good work on data visualization consists of single‐problem solutions, that cannot be easily merged into general‐purpose systems. In this talk, I will briefly review some current trends and issues, and identify some approaches that are common to many applications. One such approach in data visualization that has attracted interest from the early days is the detection of salient features, or patterns of interest in a data set. The main idea is to extract information at a higher level of abstraction from a mass of data, that is richer in semantics but much smaller in size, and that can help to define scenes and objects for visualization. This idea was pioneered in areas such as flow visualization, but is now more widely applied. It is often considered to be necessity to keep up with the ever rapidly increasing size of data sets, and the demand for interactivity in data visualization and analysis. Another generic approach in data visualization is called interactive visual analysis (TVA), consisting of a strongly interactive multiple‐linked‐view interfaces with integrated, powerful data analysis techniques taken from statistical analysis, pattern recognition, machine learning, and other fields. This is built on the assumptions that a single 2D or 3D visualization is often not enough, and spatial views can be augmented with abstract, derived data spaces; that strong interaction helps to promote insight; and that a better balance is needed between human visual inspection and computer‐based analysis and reasoning. Interestingly, an IVA interface can serve not only as an environment for exploration of low‐level data, but also for defining the high‐level features to be extracted, that should summarize the essence of the data. The high‐level features are usually highly application specific, and can only be found using theories from the application domains. The big challenge is to create environments for general purpose visual data analysis, and yet allow users to introduce advanced theories and methods from many application domains. The trend towards more integration in data visualization will be illustrated with cross‐links between very different areas, such as medical and flow visualization, and the combined use of techniques from scientific visualization and information visualization, and the absorption of other data analysis techniques. Also, historic and contemporary examples of feature extraction and interactive visual analysis will be shown.     

Research on environmental landscape design based on virtual reality technology and deep learning

Virtual Reality (VR) provides immersive visualization and intuitive interaction. The VR is used to enable any biomedical profession to develop a deep learning (DL) model for image classification. The Deep Neural Network (DNN) models can be used as a powerful tool for data analysis, but they are also challenging to understand and develop. To make deep learning more convenient and fast operation, it have established a landscape of DNN development environment based on virtual reality. In this environment, users can move concrete objects only to build neural networks with their own hands. It automatically transforms these configurations into a trainable model and reports on the real-time test dataset. In addition to realizing the insights users are developing into DNN models, it has also visually enriched the virtual environmental landscape objects with the parts of the model. In this way bridge the gap between professionals in different disciplines, providing a new perspective on the model analysis and data interaction. This system further demonstrates that learning and visualization technologies developed in Shenzhen can benefit from integrating virtual reality.     

面向多领域的可视化应用开发平台MOVADP

ＭＯＶＡＤＰ是一个面向多领域的可视化应用开发平台，文中主要介绍了该平台的软件结构和实现技术，ＭＯＶＡＤＰ以数据流机制为核心，采用可视编程技术，为用户开发可视化应用提供了一个文凭交互的模块级图形编程环境，与同类平台相比，ＭＯＶＡＤＰ的特点在于，引入了ＩＦＴＨＥＮ－ＥＬＳＥ，ＷＨＩＬＥ－ＬＯＯＰ等控制结构，支持用户构建复杂的可化应用流图；支持“ｌａｚｙｅｖａｌｕａｔｉｏｎ”命令驱动方式下的流图局部运行     

一种面向VR多投影环幕设备的可视化结果显示方法

传统显示设备难以满足大规模复杂数据可视化结果显示的需求,而VR多投影环幕显示设备提供的沉浸式显示环境可以良好地应对复杂数据可视化显示的使用情景。提出一种面向VR多投影环幕设备的可视化结果显示方法,通过设计多投影环境中兼容2D与3D显示的渲染流程,解决了传统方法中出现的画面渲染模糊问题。同时,该方法通过3D运动模拟计算以及交互射线计算解决了在新渲染流程下的立体显示和交互坐标转换问题。实验结果表明,该方法有效地提高了多投影环境中可视化结果画面的清晰度,并支持立体显示与交互。     

地学e-Science发展的回顾与展望

自 e-Science 提出之后的近 20 年间,地学 e-Science 在计算、网络和存储等信息技术的推动下,业已形成了基于数据、模型、计算、可视化分析和协同工作的地学研究框架,已经成为推动地学研究方法变革的驱动器。本文梳理和归纳了地学 e-Science 的发展过程和一些典型应用,总结了地学e-Science 的发展趋势,提出了简化的基于 3M 平台（Monitoring（监测平台）、Modeling（模型平台）、Manipulating（操作平台））的地学 e-Science 架构。从地学 e-Science 发展趋势上看,建立基于数据产生、采集、传输、管理的联合观测系统,形成完善的监测平台是地学 e-Science 的基础。建立数据分析、制备、同化和模型构建、集成与模拟的模型平台是地学 e-Science 的核心。建立基于高性能计算、可视化分析和协同工作环境的操作平台是地学 e-Science 研究的基本环境。     

水质自动监测站无人机实景三维建模与应用

实景三维技术的发展为生态环境监测提供更加快捷、有效的技术手段。对水质自动监测站地理空间环境进行三维影像采集，在影像数据批量提取及三角测量解析、几何校正及平差处理后，获取水站及周边厘米级的垂直和倾斜三维影像。以莲花山水质自动监测站倾斜实景三维建模为例，逐步建立水站实景三维模型，构建三维影像数据库并实现业务化应用，其中数据采集过程航线的旁向重叠率一般需要达到 65%，航向重叠率一般需要达到 75%。处理后的矢量照片进行自动密集匹配处理，生成包含矢量信息的白模，最后构建 TIN 模型映射 3D 纹理。功能除了强大的可视化功能，如放大、缩小、旋转、多角度展示外，还具有空间测量、数据融合和分析研判功能，提高水站的可视化应用水平。     

网络环境下高性能计算的可视化

本文介绍了在“先进计算基础设施”环境中实现科学计算可视化的方法 .该环境对可视化提出了较高的要求 :一方面 ,客户是通过 Internet观察这些结果的 ,没有事先安装任何软件 ;另一方面 ,高性能计算结果的可视化数据规模又非常大 ,必须用动态三维图像展现 .因此 ,传统的可视化手段难以同时满足这两个目标 .本文基于 Java的 Java 3D建立了三维可视化环境 ,实现了从 Internet自动安装用户端运行环境 ,并能通过传输控制三维模型的代码 ,在用户端快速生成可视化图像 ;同时 ,结合 Applet与 Servlet交互技术 ,在用户观察当前可视化结果的同时 ,分解传输有效数据来控制三维模型后续的运动 ,使跨网可视化的动态效果接近于本地运行的水平 .     

Distributed volume visualization: A step towards integrated data analysis and image synthesis

Integrated on-the-fly data analysis and image synthesis is one of the most dominant challenges on modern volume visualization tools. Since volume visualization algorithms are them self computationally complex and memory intensive there is hardly a chance to efficiently integrate data analysis tools on standard single processor architectures. The development and spreading of multiprocessor systems with large scale memory allow for the direct analysis and modification of the data during the rendering process. But to efficiently integrate both tasks similar parallelization strategies and a unique data layout must be chosen. Furthermore, since more and more systems with hardware assisted processing and visualization options can be accessed across high performance networks, distributed visualization tools should benefit from these options whenever possible. In the following paper a prototyped parallel visualization environment will be exemplified in which data analysis and image synthesis are simultaneously performed on demand. The objective is to outline basic parallelization and distribution aspects which enable flexible integration of different tasks rather than to present a concrete implementation. In this context the development and design of a unique algorithmic framework for integrated and/or distributed data analysis and image synthesis dominates the work hereafter.     

分子结构网络三维可视化系统的设计与实现

生物学数据的复杂性导致针对生物信息的可视化研究的不断深入,而网络是新兴的可视化工作的媒介,因此针对异地生物学数据设计网络三维可视化系统十分必要.该文研究网络环境下如何异地调用原始数据以及可视化工具,制定分子结构网络三维可视化系统的设计方案,实现网络环境下的分子结构可视化模型.该可视化系统在客户端仅仅需要一个标准浏览器而非胖客户端,使用户能方便地使用个人电脑远程浏览蛋白质分子结构图.通过不同原子个数的蛋白质分子在不同显示模式下的性能测试,表明了该系统的可行性.该系统有助于可视化地分析和利用生物学数据.     

AMP及其可视化的研究和实现

首先介绍了网络测量的基本概念和AMP项目的背景,然后阐述了基于Java的可视化环境,实现原始测量数据的整理和可视化.可视化结果可以明显地帮助研究人员准确及时地了解并分析当前网络的状况.     

雷达无源干扰态势监测方案设计与实现

为了满足复杂电磁环境下反舰导弹无源干扰试验态势分析与评估需求,论证并设计了基于相参雷达信号处理技术的无源态势环境监测方案。通过改造雷达导引头信号处理软件,并利用高速数据采集设备,实现了无源干扰试验态势的时域、频域、能量域可视化、可量化试验数据的录取,为态势分析评估提供了数据支撑。经实际工程应用,满足了抗干扰试验干扰态势复盘分析需要。     

3DIVE: An Immersive Environment for Interactive Volume Data Exploration

This paper describes an immersive system,called 3DIVE,for interactive volume data visualization and exploration inside the CAVE virtual environment.Combining interactive volume rendering and virtual reality provides a netural immersive environment for volumetric data visualization.More advanced data exploration operations,such as object level data manipulation,simulation and analysis ,are supported in 3DIVE by several new techniques,In particular,volume primitives and texture regions ae used for the rendering,manipulation,and collision detection of volumetric objects;and the region-based rendering pipeline is integrated with 3D image filters to provide an image-based mechanism for interactive transfer function design.The system has been recently released as public domain software for CAVE/ImmersaDesk users,and is currently being actively used by various scientific and biomedical visualization projects.     

高性能计算环境下陆面建模系统的关键技术

为了从多角度精确评估陆面特征,改善陆面过程模型的模拟性能,并为研究者提供一套完整的从数据处理到模拟分析的陆面建模系统.采用多种脚本语言和模型数据融合方法来构建陆面建模系统.此建模系统集成观测数据、陆面过程模型、高性能计算、数据处理和分析方法,以及可视化等技术手段.在此系统内针对两种不同的陆面过程模型进行了应用示范,证明了不同脚本语言的建模系统在目前高性能计算环境中的应用潜力,以及不同可视化方案在陆面建模系统的作用.