一种面向临床决策推理的可视诊疗技术

海量医学信息的快速增长已远远超出人类认知能力,医疗服务环境和用户人群的复杂多样性使得海量数据难以在现有能力和工具的支持下满足广大用户对于信息服务的需求.临床诊疗服务的可视化、智能化程度不高导致现有的医学知识服务水平难以保证海量资源信息的充分利用.在分析了临床诊疗环境下人机协同认知特性的基础上给出了一种基于语义层次的信息组织方式;分析了符合该数据组织模式的可视形态及自然的可视交互技术;在上述工作的基础上构建了一个面向临床决策推理的可视诊疗分析框架,并给出了原型系统实例加以验证.结果表明,通过结合交互式可视化和自动分析技术,可以有效地帮助人们从海量数据中获取到有用的信息模式,减轻人们对数据进行分析的负担,为医疗诊断过程提供决策支持服务.     

DaisyVA:支持信息多面体可视分析的智能交互式可视化平台

针对目前缺乏有效地支持信息多面体可视分析的交互式信息可视化平台的问题,提出并实现了一个面向最终用户的交互式可视化平台DaisyVA.首先建立了一个支持信息多面体可视分析界面模型IMFA,并定义了IMFA的多面体数据模型、可视表征模型和交互控制模型;然后围绕IMFA设计了DaisyVA的体系架构,讨论了基于模型的系统开发机制、核心模块与运行时框架机理,以及DaisyVA组件库;最后将DaisyVA应用于大型集团制造企业物流网络瓶颈的可视分析实例中.实例分析结果表明,DaisyVA能为多面体数据提供统一建模的支持和可扩展可视化算法库的支持、提供多种所需的交互技术并可灵活定制可视分析的交互任务、支持信息多面体间的内在语义关联分析,以及能够为最终用户提供一种简单快速原型方法,因此能够为信息多面体可视分析提供一种有效的支持.     

基于交互式可视组件的分析决策环境研究

针对人类分析决策活动的分步骤、交互化特点,基于认知心理学相关理论研究了分析决策过程中的人机协同工作模型,提出了基于交互式可视组件的分析决策交互任务框架,建立了交互式可视组件的统一描述,研究了交互式可视组件的实现技术,包括运行过程中信息可视化技术、交互技术和配置过程中的交互历史复用技术等,构建了一个交互式可视组件的分析决...     

教育大数据可视化研究综述

教育大数据可视化分析对于复杂教育规律的理解与挖掘具有重要作用,已成为当前教育信息科学研究领域的重要课题。首先归纳了教育大数据的典型特征,从促进学生元认知发展、辅助教师监督学习过程及提升管理者科学决策水平三个角度介绍了教育大数据应用的最新研究成果,并简述了利用教育大数据实施可视化分析的基本流程。然后重点对文本数据可视化、多维数据可视化、网络数据可视化、时间序列数据可视化以及地理空间数据可视化等五种主流的教育大数据可视化呈现方法进行特征描述,并给出具体的应用场景。随后介绍了动态查询与过滤技术、可缩放/变形界面技术和多视图联动技术三个实施教育大数据可视化的关键交互技术方法。最后依据最新研究动态,从多模态教育数据融合、人机交互、人机协同范式以及教育数据可视化设计的标准规范和评价体系四方面对教育大数据可视化未来研究方向进行了展望。     

大数据可视化的挑战与最新进展

大数据的来临增强了可视化的重要性。可视化分析挖掘人类对于信息的认知能力与优势,将人、机有机融合,借助人机交互高效洞悉大数据背后的信息与规律,是大数据分析的重要方法。针对大数据数据量大、维度高、多来源、多形态等特点论述了大规模数据、流数据、非结构和异构数据的可视化方法。首先讨论了大规模数据的可视化技术：1）采用分而治之的原则将大问题分解成较小的任务并采用并行处理的方式解决以提高处理的速度;2）通过聚合、采样、多分辨表示的方法进行数据约简;3）针对高维数据选择若干个视图,在多个角度下生成不同的可视化结果。然后针对监控型、叠加型两类流数据探讨了流数据的可视化过程。最后阐述了非结构化数据以及异构性数据的可视化技术。总之,可视化能够克服计算机自动化分析方法的劣势与不足,整合计算机的分析能力和人们对信息的感知能力,有效地洞悉大数据背后的信息与智慧,但其理论研究成果也非常有限,同时面临着数据规模大、动态变化、维度高、多源异构等方面的挑战,这些也逐渐成为今后的大数据可视化研究的热点与方向。     

面向虚实融合的人机交互

面向虚实融合的人机交互涉及计算机科学、认知心理学、人机工程学、多媒体技术和虚拟现实等领域，旨在提高人机交互的效率，同时响应人类认知与情感的需求，在办公教育、机器人和虚拟/增强现实设备中都有广泛应用。本文从人机交互涉及感知计算、人与机器人交互及协同、个性化人机对话和数据可视化等4个维度系统阐述面向虚实融合人机交互的发展现状。对国内外研究现状进行对比，展望未来的发展趋势。本文认为兼具可迁移与个性化的感知计算、具备用户行为深度理解的人机协同、用户自适应的对话系统等是本领域的重要研究方向。     

科学计算可视化

科学计算可视化(V_isc)是正在兴起的崭新技术领域。V_isc把数据信息转换成可视信息,是分析与解释大体积数据的有力工具。本文阐述了V_isc技术的若干重要方面,指出研制可视化应用开发环境VadE的主要目标,即与学科无关性和可视驾驭计算功能。     

生物大分子可视化技术综述

生物大分子,如蛋白质、核酸,影响着生命体的微观行为,直接决定了物种的生命功能.生物大分子可视化技术,对分子生物学和生物化学领域具有重要的研究意义,是计算机辅助药物设计的重要研究方向.文中对近年来生物大分子可视化进行深入的分析.首先从分子结构的空间形态定义出发,概述分子骨架、表面、空腔3种基本空间形态的概念和可视化方法;然后论述近年来大规模生物分子场景可视化技术,包括分子组装、多细节层次和GPU加速;再阐述动态分子可视分析技术,包括分子轨迹和空腔可视分析,进而介绍面向虚拟现实的生物分子可视化交互技术;最后,总结生物大分子可视化研究面临的挑战,并对其未来发展趋势进行展望.     

基于主题的文本可视分析研究

文本可视分析是一个跨学科的领域,涉及文本数据挖掘、计算机图形图像以及人机交互等各方面的知识和技术,可以帮助用户以可视分析的手段交互地分析海量的文本数据内容,提供及时的反馈,发现异常和规则,提取知识以及获取洞察.已被应用在国土安全、商业智能分析以及金融分析等很多不同的领域,受到国内外学术界、工业界以及政府部门越来越多的重视.文中首先简要地介绍了文本可视分析的一般流程;然后系统地介绍了典型的文本分析和可视化技术,并着重讨论这2类研究的最新技术以及发展;最后对全文进行了总结并展望了文本可视分析面临的四大研究挑战:海量数据规模、复杂数据的不确定性、数据融合以及人机交互.     

2020年CCF科学技术奖-技术发明奖获奖项目简介

2020年CCF科学技术奖技术发明一等奖(2个)项目名称:面向数字经济的可视化设计与开发关键技术及应用完成单位:浙江大学阿里巴巴集团控股有限公司主要完成人:陈为闻啸梅鸿辉关会华马瑞娴忻程烨获奖理由:该项目发明了面向复杂数据的特征增强的可视表达技术、基于视觉感知原理的高效能可视化技术、面向广域数据应用的低代码可视化设计技术、面向多源异构数据的敏捷可视查询与分析技术,研发可视化交互设计与开发软件平台,被应用于超过1万个用户、超十万个数据可视化应用及场景的构建,社会和经济效益显著。     

Visualization of Multi-Variate Scientific Data

In this state-of-the-art report we discuss relevant research works related to the visualization of complex, multi-variate data. We discuss how different techniques take effect at specific stages of the visualization pipeline and how they apply to multi-variate data sets being composed of scalars, vectors and tensors. We also provide a categorization of these techniques with the aim for a better overview of related approaches. Based on this classification we highlight combinable and hybrid approaches and focus on techniques that potentially lead towards new directions in visualization research. In the second part of this paper we take a look at recent techniques that are useful for the visualization of complex data sets either because they are general purpose or because they can be adapted to specific problems.     

A Characterization of Interactive Visual Data Stories With a Spatio-Temporal Context

Large-scale issues with a spatial and temporal context such as the COVID-19 pandemic, the war against Ukraine, and climate change have given visual storytelling with data a lot of attention in online journalism, confirming its high effectiveness and relevance for conveying stories. Thus, new ways have emerged that expand the space of visual storytelling techniques. However, interactive visual data stories with a spatio-temporal context have not been extensively studied yet. Particularly quantitative information about the used layout and media, the visual storytelling techniques, and the visual encoding of space-time is relevant to get a deeper understanding of how such stories are commonly built to convey complex information in a comprehensible way. Covering these three aspects, we propose a design space derived by merging and adjusting existing approaches, which we used to categorize 130 collected web-based visual data stories with a spatio-temporal context from between 2018 and 2022. An analyzis of the collected data reveals the power of large-scale issues to shape the landscape of storytelling techniques and a trend towards a simplified consumability of stories. Taken together, our findings can serve story authors as inspiration regarding which storytelling techniques to include in their own spatio-temporal data stories.     

Progress in scientific visualization

This paper surveys recent work in the visualization of molecules, scalar fields, and vector fields.     

A Modified Double Gyre with Ground Truth Hyperbolic Trajectories for Flow Visualization

The model of a Double Gyre flow by Shadden et al. is a standard benchmark data set for the computation of hyperbolic Lagrangian Coherent Structures (LCS) in flow data. While structurally extremely simple, it generates hyperbolic LCS of arbitrary complexity. Unfortunately, the Double Gyre does not come with a well‐defined ground truth: the location of hyperbolic LCS boundaries can only be approximated by numerical methods that usually involve the gradient of the flow map. We present a new benchmark data set that is a small but carefully designed modification of the Double Gyre , which comes with ground truth closed‐form hyperbolic trajectories. This allows for computing hyperbolic LCS boundaries by a simple particle integration without the consideration of the flow map gradient. We use these hyperbolic LCS as a ground truth solution for testing an existing numerical approach for extracting hyperbolic trajectories. In addition, we are able to construct hyperbolic LCS curves that are significantly longer than in existing numerical methods.     

A Survey on Visualizations for Musical Data

Digital methods are increasingly applied to store, structure and analyse vast amounts of musical data. In this context, visualization plays a crucial role, as it assists musicologists and non-expert users in data analysis and in gaining new knowledge. This survey focuses on this unique link between musicology and visualization. We classify 129 related works according to the visualized data types, and we analyse which visualization techniques were applied for certain research inquiries and to fulfill specific tasks. Next to scientific references, we take commercial music software and public websites into account, that contribute novel concepts of visualizing musicological data. We encounter different aspects of uncertainty as major problems when dealing with musicological data and show how occurring inconsistencies are processed and visually communicated. Drawing from our overview in the field, we identify open challenges for research on the interface of musicology and visualization to be tackled in the future.     

多维可视化技术综述

当前,面对科学、工程和商业领域中海量的多维信息,用户迫切需要使用有效的可视化工具在知识发现、信息认知及信息决策过程中对其进行理解。首先对多维和多变元的概念进行了界定,给出了二者的适用领域,然后基于多维可视化技术的分类体系,详细阐述了各类技术代表方法的基本原理、适用性及功能作用,最后分析比较了各类技术方法的优缺点,展望了多维可视化技术未来的研究方向及其面临的挑战。     

Stochastic Volume Rendering of Multi‐Phase SPH Data

In this paper, we present a novel method for the direct volume rendering of large smoothed‐particle hydrodynamics (SPH) simulation data without transforming the unstructured data to an intermediate representation. By directly visualizing the unstructured particle data, we avoid long preprocessing times and large storage requirements. This enables the visualization of large, time‐dependent, and multivariate data both as a post‐process and in situ. To address the computational complexity, we introduce stochastic volume rendering that considers only a subset of particles at each step during ray marching. The sample probabilities for selecting this subset at each step are thereby determined both in a view‐dependent manner and based on the spatial complexity of the data. Our stochastic volume rendering enables us to scale continuously from a fast, interactive preview to a more accurate volume rendering at higher cost. Lastly, we discuss the visualization of free‐surface and multi‐phase flows by including a multi‐material model with volumetric and surface shading into the stochastic volume rendering.     

美学改进的空间优化树绘制

如何在有限的屏幕空间呈递层次规模尽可能大的树并保持其清晰的层次结构以避免认知困难问题一直是树可视化研究的主要问题之一。提出的改进的空间优化的树方法采用更合理的子树空间划分,进一步提高空间利用率,通过改变边缘结点定位方式进一步降低了原方法中因其分布不规则性而造成的认知负担问题。     

The State of the Art in Flow Visualization: Dense and Texture-Based Techniques

Flow visualization has been a very attractive component of scientific visualization research for a long time. Usually very large multivariate datasets require processing. These datasets often consist of a large number of sample locations and several time steps. The steadily increasing performance of computers has recently become a driving factor for a reemergence in flow visualization research, especially in texture‐based techniques. In this paper, dense, texture‐based flow visualization techniques are discussed. This class of techniques attempts to provide a complete, dense representation of the flow field with high spatio‐temporal coherency. An attempt of categorizing closely related solutions is incorporated and presented. Fundamentals are shortly addressed as well as advantages and disadvantages of the methods.     

基于VTK技术的可视化研究

可视化工具（Visualization ToolKit）是一个面向对象的可视化类库，它为从事可视化工具开发的广大科研工作者提供直接的技术支持。本文介绍了使用VTK环境的建立，工作机制以及构成VTK对象模型的组成部分。最后给出了一个可视化的实现。