一种模型驱动的交互式信息可视化开发方法

设计与实现面向领域应用的交互式信息可视化软件十分困难.缺乏统一的开发方法与支撑工具箱,为非专家用户提供对层次、网络、多维等数据类型的统一支持,对各种可视化技术与交互技术的统一支持,以及对信息可视化任务的统一支持针对此问题,提出了一种模型驱动的交互式信息可视化开发方法Daisy.首先,提出了交互式信息可视化界面模型IIVM(interactive information visualization interface model);然后,提出了基于IIVM的交互式信息可视化开发方法Daisy,讨论了该方法的两个核心技术:IIVM建模与描述文件生成方法、系统自动生成方法.同时。给出了Daisy工具箱,包括Daisy建模工具、Daisy系统自动生成工具以及运行时框架与组件库.最后,给出了该开发方法与工具箱的应用实例.实例表明,该方法能够为交互式信息可视化开发的统一支撑方法问题提供一种有效的解决方案.     

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...     

基于管道隐喻的工作流可视化方法

为直观高效的呈现工作流数据,提出面向大量工作流实例的基于三维管道隐喻的可视化方法.研究了运行阶段工作流数据特点,对流程和相关数据进行分析和建模,面向流程型数据特点提出一个有针对性的可视形态,将数据映射到三维空间中,以信息密度高的三维形态呈现多工作流实例视图,并在此基础上讨论用户交互目标和交互任务集,提供自然的交互方法,揭示工作流数据中隐含的规律,为分析利用大量工作流数据提供支持.通过系统实例验证了该方法的有效性.     

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.     

大数据可视分析综述

可视分析是大数据分析的重要方法.大数据可视分析旨在利用计算机自动化分析能力的同时,充分挖掘人对于可视化信息的认知能力优势,将人、机的各自强项进行有机融合,借助人机交互式分析方法和交互技术,辅助人们更为直观和高效地洞悉大数据背后的信息、知识与智慧.主要从可视分析领域所强调的认知、可视化、人机交互的综合视角出发,分析了支持大数据可视分析的基础理论,包括支持分析过程的认知理论、信息可视化理论、人机交互与用户界面理论.在此基础上,讨论了面向大数据主流应用的信息可视化技术——面向文本、网络(图)、时空、多维的可视化技术.同时探讨了支持可视分析的人机交互技术,包括支持可视分析过程的界面隐喻与交互组件、多尺度/多焦点/多侧面交互技术、面向Post-WIMP的自然交互技术.最后,指出了大数据可视分析领域面临的瓶颈问题与技术挑战.     

面向网状信息的Radial+Focus可视化*

针对当前网状信息可视化技术忽略了网状信息节点的可视信息的问题,提出一种面向网状信息的Radial+Focus可视化技术。首先介绍网状信息节点的信息详细度与先验重要度,并研究通过节点的交互历史计算节点的先验重要度的方法;然后研究了基于节点先验重要度的Radial+Focus布局算法;最后,给出了Radial+Focus可视化技术的应用实例和实验评估。实验评估表明,该技术能自然、高效地可视化网状信息,为用户对网状信息关系及网状信息节点的可视信息的分析提供有力的支持。     

面向地下钱庄洗钱行为的可视化交互分析平台

针对经济犯罪侦查中线索信息数据量极大、信息质量不高(数据缺失、内容不一致、结构复杂等),并且目前大部分系统都着重于从宏观的角度对数据进行分析统计以及决策,无法针对某个具体领域的案件梳理出线索,找出破案关键的问题,研究了地下钱庄洗钱的交易方式以及交易数据的特点、犯罪网络中的结构特征,提出设计并实现了一个面向地下钱庄洗钱行为的可视化交互分析平台。该平台支持对异构数据的同一化,建立了数据模型以及可视结构,资金链的可视化分析,允许用户交互操作,并结合地下钱庄洗钱的交易特征改进了DBSCAN算法;讨论了该平台的系统框架及其关键技术,并结合实际数据给出了应用实例。该平台能够给予办案人员更直观清晰的思路,提高办案效率。     

空气质量细粒度数据内联关系可视分析系统

随着数据观测和数字计算技术的快速发展,空气质量数据粒度越来越细致,为研究空气质量的细粒度数据内联关系可视化、辅助理解空气污染物的转化规律提供了数据基础.针对蕴含丰富内联特征的大气质量细粒度数据开发了一个内联关系可视分析系统.首先,基于大气质量数据多维属性设计时空数据维度模型增强数据的时空表达,并提出一种基于深度学习的特征提取方法,将空气质量数据从高维空间映射到支持交互可视分析的低维特征空间;然后,设计了一套多视图联动的可视化系统,帮助用户发现空气污染传输中的细粒度内联关系,理解污染传输途径的数据分布特征.用户实例和用户评价结果表明,该系统是有效的.     

多线程可视化Java类装载器MVJL的分析与设计

多线程可视化类装载器(MVJL)作可视化软件开发环境(VSDE)的预研,提供在启动装载阶段或者解析阶段中,多个类装载器实例装载一组装载相关类型的装载过程以及涉及信息的可视变换和交互式的动态视图.MVJL解决了单个类装载器实例带来的安全性和网络移动性问题.     

研讨信息交互式可视化平台设计与实现

针对传统研讨信息静态可视化视图杂乱、难以辨认等问题,提出研讨信息可视化框架和基于交互式可视化技术的解决方案。利用Java、XML技术,借助JFreeChar、Prefuse软件包实现交互式可视化平台。该平台基于节点链接结构,允许用户交互式操作,支持可视化检索和分析。运行结果表明,该平台改善了研讨信息的可访问性,具有较强的可扩展性。     

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.     

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.     

地理信息可视化关键性技术研究综述

可视化技术为分析和处理海量信息提供了新的手段。该文讨论了目前地理信息可视化中2．5维、三维以及多维可视化3个研究领域的国内外研究现状，并在此基础上提出了今后的研究方向。     

Faster Edge-Path Bundling through Graph Spanners

Edge-Path bundling is a recent edge bundling approach that does not incur ambiguities caused by bundling disconnected edges together. Although the approach produces less ambiguous bundlings, it suffers from high computational cost. In this paper, we present a new Edge-Path bundling approach that increases the computational speed of the algorithm without reducing the quality of the bundling. First, we demonstrate that biconnected components can be processed separately in an Edge-Path bundling of a graph without changing the result. Then, we present a new edge bundling algorithm that is based on observing and exploiting a strong relationship between Edge-Path bundling and graph spanners. Although the worst case complexity of the approach is the same as of the original Edge-Path bundling algorithm, we conduct experiments to demonstrate that the new approach is 5 – 256 times faster than Edge-Path bundling depending on the dataset, which brings its practical running time more in line with traditional edge bundling algorithms.     

Are We There Yet? A Roadmap of Network Visualization from Surveys to Task Taxonomies

Networks are abstract and ubiquitous data structures, defined as a set of data points and relationships between them. Network visualization provides meaningful representations of these data, supporting researchers in understanding the connections, gathering insights, and detecting and identifying unexpected patterns. Research in this field is focusing on increasingly challenging problems, such as visualizing dynamic, complex, multivariate, and geospatial networked data. This ever-growing, and widely varied, body of research led to several surveys being published, each covering one or more disciplines of network visualization. Despite this effort, the variety and complexity of this research represents an obstacle when surveying the domain and building a comprehensive overview of the literature. Furthermore, there exists a lack of clarification and uniformity between the terminology used in each of the surveys, which requires further effort when mapping and categorizing the plethora of different visualization techniques and approaches. In this paper, we aim at providing researchers and practitioners alike with a “roadmap” detailing the current research trends in the field of network visualization. We design our contribution as a meta-survey where we discuss, summarize, and categorize recent surveys and task taxonomies published in the context of network visualization. We identify more and less saturated disciplines of research and consolidate the terminology used in the surveyed literature. We also survey the available task taxonomies, providing a comprehensive analysis of their varying support to each network visualization discipline and by establishing and discussing a classification for the individual tasks. With this combined analysis of surveys and task taxonomies, we provide an overarching structure of the field, from which we extrapolate the current state of research and promising directions for future work.     

ComVis-Sail: Comparative Sailing Performance Visualization for Coaching

During training sessions, sailors rely on feedback provided by the coaches to reinforce their skills and improve their performance. Nowadays, the incorporation of sensors on the boats enables coaches to potentially provide more informed feedback to the sailors. A common exercise during practice sessions, consists of two boats of the same class, sailing side by side in a straight line with different boat handling techniques. Coaches try to understand which techniques are that make one boat go faster than the other. The analysis of the obtained data from the boats is challenging given its multi-dimensional, time-varying and spatial nature. At present, coaches only rely on aggregated statistics reducing the complexity of the data, hereby losing local and temporal information. We describe a new domain characterization and present a visualization design that allows coaches to analyse the data, structuring their analysis and explore the data from different perspectives. A central element of the tool is the glyph design to intuitively represent and aggregate multiple aspects of the sensor data. We have conducted multiple user studies with naive users, sailors and coaches to evaluate the design and potential of the overall tool.

     

VisualDM：一个灵活的可视化数据挖掘系统

如果要建造一个健壮的数据挖掘系统，仅仅依靠挖掘算法是不够的。目前的挖掘算法还没有完全“智能”化，所以挖掘有用的信息常常不是很有效。不过可视化技术给了我们很大的帮助，我们将挖掘算法和可视化技术结合起来，从而实现了数据挖掘系统VisualDM。     

Hinted Star Coordinates for Mixed Data

Mixed data sets containing numerical and categorical attributes are nowadays ubiquitous. Converting them to one attribute type may lead to a loss of information. We present an approach for handling numerical and categorical attributes in a holistic view. For data sets with many attributes, dimensionality reduction (DR) methods can help to generate visual representations involving all attributes. While automatic DR for mixed data sets is possible using weighted combinations, the impact of each attribute on the resulting projection is difficult to measure. Interactive support allows the user to understand the impact of data dimensions in the formation of patterns. Star Coordinates is a well-known interactive linear DR technique for multi-dimensional numerical data sets. We propose to extend Star Coordinates and its initial configuration schemes to mixed data sets. In conjunction with analysing numerical attributes, our extension allows for exploring the impact of categorical dimensions and individual categories on the structure of the entire data set. The main challenge when interacting with Star Coordinates is typically to find a good configuration of the attribute axes. We propose a guided mixed data analysis based on maximizing projection quality measures by the use of recommended transformations, named hints, in order to find a proper configuration of the attribute axes.     

Graphical Information Portals—The Application of Smart Maps in G≻eoN≻et 4D

This paper presents a new brand of portals that elevates the concepts of information portals to a new level of interaction and navigation means. The graphical information portal is built upon the concept of smart maps for information visualization and exploration. Smart maps serve as navigational hub by indicating the existence of information carrying relevance for a specific location, by relating distributed multimedia information to a location on a map of interest, and by categorizing information for easier orientation in subjects. Main advantage of a map-based information portal lies in the intuitive information presentation, navigation, search and retrieval. Representative usage scenarios include facility management, information kiosks, and environmental information systems. Groupware functions for collaborative visualization and interactive editing on maps are added on top in order to migrate the concept of graphical information portals to further domains, such as concurrent engineering, risk management, and the like. An implementation of a geographical information portal has been designed and implemented in project GeoNet 4D, focussing on facility management for portuary zones.     

空间信息多维可视化技术综述

可视化技术的出现为分析和处理海量信息提供了新的手段 .将空间信息多维可视化的实现方法分为基于 2变量的多信息可视化、基于多变量的多维信息可视化和基于动画的多维信息可视化三类 ,并详细讨论了这三类方法的各种实现算法