Balloon focus: a seamless multi-focus+context method for treemaps

The treemap is one of the most popular methods for visualizing hierarchical data. When a treemap contains a large number of items, inspecting or comparing a few selected items in a greater level of detail becomes very challenging. In this paper, we present a seamless multi-focus and context technique, called Balloon Focus, that allows the user to smoothly enlarge multiple treemap items served as the foci, while maintaining a stable treemap layout as the context. Our method has several desirable features. First, this method is quite general and hence can be used with different treemap layout algorithms. Second, as the foci are enlarged, the relative positions among all items are preserved. Third, the foci are placed in a way that the remaining space is evenly distributed back to the non-focus treemap items. When Balloon Focus maximizes the possible zoom factor for the focus items, these features ensure that the treemap will maintain a consistent appearance and avoid any abrupt layout changes. In our algorithm, a DAG (Directed Acyclic Graph) is used to maintain the positional constraints, and an elastic model is employed to govern the placement of the treemap items. We demonstrate a treemap visualization system that integrates data query, manual focus selection, and our novel multi-focus+context technique, Balloon Focus, together. A user study was conducted. Results show that with Balloon Focus, users can better perform the tasks of comparing the values and the distribution of the foci.     

Perceptual guidelines for creating rectangular treemaps

Treemaps are space-filling visualizations that make efficient use of limited display space to depict large amounts of hierarchical data. Creating perceptually effective treemaps requires carefully managing a number of design parameters including the aspect ratio and luminance of rectangles. Moreover, treemaps encode values using area, which has been found to be less accurate than judgments of other visual encodings, such as length. We conduct a series of controlled experiments aimed at producing a set of design guidelines for creating effective rectangular treemaps. We find no evidence that luminance affects area judgments, but observe that aspect ratio does have an effect. Specifically, we find that the accuracy of area comparisons suffers when the compared rectangles have extreme aspect ratios or when both are squares. Contrary to common assumptions, the optimal distribution of rectangle aspect ratios within a treemap should include non-squares, but should avoid extremes. We then compare treemaps with hierarchical bar chart displays to identify the data densities at which length-encoded bar charts become less effective than area-encoded treemaps. We report the transition points at which treemaps exhibit judgment accuracy on par with bar charts for both leaf and non-leaf tree nodes. We also find that even at relatively low data densities treemaps result in faster comparisons than bar charts. Based on these results, we present a set of guidelines for the effective use of treemaps and suggest alternate approaches for treemap layout.     

一种层次结构中多维属性的可视化方法

在很多领域的统计分析中,通常需要分析既具有层次结构又具有多维属性的复杂数据,如食品安全数据、股票数据、网络安全数据等.针对现有多维数据和层次结构的可视化方法不能满足对同时具有层次和多维两种属性数据的可视分析要求,提出了一种树图中的多维坐标MCT(multi-coordinate in treemap)技术.该技术采用基于Squarified和Strip布局算法的树图表示层次结构,用树图中节点矩形的边作为属性轴,通过属性映射、属性点连接、曲线拟合实现层次结构中多维属性的可视化.将该技术应用于全国农药残留侦测数据,实现了对全国各地区、各超市、各农产品中农药残留检出和超标情况的可视化,为领域人员提供了有效的分析工具.MCT技术也可用于其他领域的层次多属性数据的可视化.     

Quantitative Comparison of Time-Dependent Treemaps

Rectangular treemaps are often the method of choice to visualize large hierarchical datasets. Nowadays such datasets are available over time, hence there is a need for (a) treemaps that can handle time-dependent data, and (b) corresponding quality criteria that cover both a treemap's visual quality and its stability over time. In recent years a wide variety of (stable) treemapping algorithms has been proposed, with various advantages and limitations. We aim to provide insights to researchers and practitioners to allow them to make an informed choice when selecting a treemapping algorithm for specific applications and data. To this end, we perform an extensive quantitative evaluation of rectangular treemaps for time-dependent data. As part of this evaluation we propose a novel classification scheme for time-dependent datasets. Specifically, we observe that the performance of treemapping algorithms depends on the characteristics of the datasets used. We identify four potential representative features that characterize time-dependent hierarchical datasets and classify all datasets used in our experiments accordingly. We experimentally test the validity of this classification on more than 2000 datasets, and analyze the relative performance of 14 state-of-the-art rectangular treemapping algorithms across varying features. Finally, we visually summarize our results with respect to both visual quality and stability to aid users in making an informed choice among treemapping algorithms. All datasets, metrics, and algorithms are openly available to facilitate reuse and further comparative studies.     

面向层次化数据的变分圆形树图

圆形树图(circular treemap)是面向层次化数据的一种信息可视化方法.提出一种圆形树图构造方法,将圆形树图的布局问题与组合优化中的圆排列(disk packing)问题相结合,以一种基于变分连续优化的算法求解多个半径不同圆的优化布局,由此提高圆形树图的空间利用率,并支持层次下行、层次上行与焦点+上下文等自然交互方式.实验结果表明了该方法的有效性.     

正方化树图布局算法研究与优化

层次数据是一种常见的数据类型,它着重表达个体之间的包含和从属关系等。树图是一种非常流行的利用包含关系来表达层次化数据的可视化方法。该方法具有高效的空间利用率及良好的交互性,并广泛应用于各个领域。正方化布局算法是树图可视化方法中常用的算法,但该算法存在无序和稳定性差等不足。提出了一种优化算法来改进该算法的不足,并通过实验数据证明了优化后算法的有效性。     

Spatially ordered treemaps

Existing treemap layout algorithms suffer to some extent from poor or inconsistent mappings between data order and visual ordering in their representation, reducing their cognitive plausibility. While attempts have been made to quantify this mismatch, and algorithms proposed to minimize inconsistency, solutions provided tend to concentrate on one-dimensional ordering. We propose extensions to the existing squarified layout algorithm that exploit the two-dimensional arrangement of treemap nodes more effectively. Our proposed spatial squarified layout algorithm provides a more consistent arrangement of nodes while maintaining low aspect ratios. It is suitable for the arrangement of data with a geographic component and can be used to create tessellated cartograms for geovisualization. Locational consistency is measured and visualized and a number of layout algorithms are compared. CIELab color space and displacement vector overlays are used to assess and emphasize the spatial layout of treemap nodes. A case study involving locations of tagged photographs in the Flickr database is described.     

Browsing zoomable treemaps: structure-aware multi-scale navigation techniques

Treemaps provide an interesting solution for representing hierarchical data. However, most studies have mainly focused on layout algorithms and paid limited attention to the interaction with treemaps. This makes it difficult to explore large data sets and to get access to details, especially to those related to the leaves of the trees. We propose the notion of zoomable treemaps (ZTMs), an hybridization between treemaps and zoomable user interfaces that facilitates the navigation in large hierarchical data sets. By providing a consistent set of interaction techniques, ZTMs make it possible for users to browse through very large data sets (e.g., 700,000 nodes dispatched amongst 13 levels). These techniques use the structure of the displayed data to guide the interaction and provide a way to improve interactive navigation in treemaps.     

Visualisation with treemaps and sunbursts in many-objective optimisation

Visualisation is an important aspect of evolutionary computation, enabling practitioners to explore the operation of their algorithms in an intuitive way and providing a better means for displaying their results to problem owners. The presentation of the complex data arising in many-objective evolutionary algorithms remains a challenge, and this work examines the use of treemaps and sunbursts for visualising such data. We present a novel algorithm for arranging a treemap so that it explicitly displays the dominance relations that characterise many-objective populations, as well as considering approaches for creating trees with which to represent multi- and many-objective solutions. We show that treemaps and sunbursts can be used to display important aspects of evolutionary computation, such as the diversity and convergence of a search population, and demonstrate the approaches on a range of test problems and a real-world problem from the literature.     

Visualization for Knowledge Graph Based on Education Data

Knowledge graph, also known as scienti c knowledge graph, can reveal the dynamic development rules in complex knowledge elds. How to clearly present the internal structure of knowledge graph is particularly important, however, the current visualization research based on knowledge graph is rare. In this paper, varieties of data related to education are mined from massive web data, and are fused together. Then knowledge graph which is centered on educational events is constructed utilizing extracted named entities and entity relations. We construct a visual analysis platform for education knowledge graph, EduVis, which can support users to do associated analysis of education, and enable users to obtain the public opinions. In EduVis, we design and implement a) a word cloud treemap to provide an overview of education knowledge graph, b) a layout of events relation network graph based on topological structure and timeline to explore in details, c) a click tracking path to record the history of users'' clicks and help users to backtrack. The case studies show that the aforementioned visual analysis methods for our knowledge graph can meet users'' demands for data analysis tasks.     

LOD map--A visual interface for navigating multiresolution volume visualization

In multiresolution volume visualization, a visual representation of level-of-detail (LOD) quality is important for us to examine, compare, and validate different LOD selection algorithms. While traditional methods rely on ultimate images for quality measurement, we introduce the LOD map--an alternative representation of LOD quality and a visual interface for navigating multiresolution data exploration. Our measure for LOD quality is based on the formulation of entropy from information theory. The measure takes into account the distortion and contribution of multiresolution data blocks. A LOD map is generated through the mapping of key LOD ingredients to a treemap representation. The ordered treemap layout is used for relative stable update of the LOD map when the view or LOD changes. This visual interface not only indicates the quality of LODs in an intuitive way, but also provides immediate suggestions for possible LOD improvement through visually-striking features. It also allows us to compare different views and perform rendering budget control. A set of interactive techniques is proposed to make the LOD adjustment a simple and easy task. We demonstrate the effectiveness and efficiency of our approach on large scientific and medical data sets.     

基于树图双向正方化算法的实验研究

在对树图生成算法理论研究的基础上,开发一个结合多种主要树图生成算法的树图原型.结合用户的反馈意见,对双向正方化算法和其他几种算法进行分析和比较,并对双向正方化算法的部分缺陷提出了一些解决方法.     

Improving Web usability through visualization

One reason for poor Web site usability is researchers' lack of understanding about how users surf for information. Predictive Web usage visualizations can help analysts uncover traffic patterns and usability problems. The author describes some of the techniques those in the User Interface Research Group at PARC have developed to visualize content changes, linkage structures, site usage, and so on. He explores how these techniques can be used to identify specific usability problems at large Web sites. As part of his work, he have created a predictive visualization model called Information Scent, in which simulated users help uncover patterns and deficiencies in information accessibility. He demonstrates these techniques using a prototype system called ScentViz to illustrate how Web usage analysis can be enhanced using visualization methods     

复杂网络聚类特征层次布局算法

网络聚类模式发现是网络分析中的一项重要任务,好的网络布局应能体现网络中的聚类特征,并允许用户从不同层次探索网络结构。为此,基于社团划分和多层次布局思想提出了聚类特征层次布局算法。首先利用种子节点和个性化PageRank对网络实现社团划分;其次根据划分结果对网络进行粗化,并设计了粗化网络初始布局;然后利用节点度信息改进力导向模型以完成细化;最后,为验证所提算法的有效性,设计了从整体到局部的实验。实验表明所提算法能够在有效时间内生成高质量的布局结果,与现有布局算法相比,所提算法更能真实展示网络聚类特征,同时兼顾网络微观结构,能够满足用户从不同层次探索网络结构的需要。     

HybridVis: An adaptive hybrid-scale visualization of multivariate graphs

Existing network visualizations support hierarchical exploration, which rely on user interactions to create and modify graph hierarchies based on the patterns in the data attributes. It will take a relatively long time for users to identify the impact of different attributes on the cluster structure. To address this problem, this paper proposes a visual analytical approach, called HybridVis, creating an interactive layout to reveal clusters of obvious characteristics on one or more attributes at different scales. HybridVis can help people gain social insight and better understand the roles of attributes within a cluster. First, an approximate optimal graph hierarchy based on an energy model is created, considering both data attributes and relationships among data items. Then a layout algorithm and a level-dependent perceptual view for multi-scale graphs are proposed to show the attribute-driven graph hierarchy. Several views, which interact with each other, are designed in HybridVis, including a graphical view of the relationships among clusters; a cluster tree revealing the cluster scales and the details of attributes on parallel coordinates augmented with histograms and interactions. From the meaningful and globally approximate optimal abstraction, users can navigate a large multivariate graph with an overview+detail to explore and rapidly find the potential correlations between the graph structure and the attributes of data items. Finally, experiments using two real world data sets are performed to demonstrate the effectiveness of our methods.     

Visual comparison of metabolic pathways

Biological databases contain a large amount of data about metabolic pathways, in particular about similar pathways in different species. Biologists are familiar with visual representations of metabolic pathways. Pathway diagrams help them to understand the complex relationships between the components of the pathways, to extract information from the data, and to compare pathways between different species. However, visual interfaces to metabolic pathway databases cannot cope well with the visual comparison of similar pathways in different species.This paper presents a new approach for the visual comparison of metabolic pathways which uses a graph drawing algorithm. Using layout constraints, identical parts of similar pathways in different species are placed side by side, thereby highlighting similarities and differences between these pathways. This visualization method can be used as a visual interface to databases. It supports different layout styles and has been tested with data obtained from the BioPath system and the KEGG database.     

结合视觉惯性模组的室内三维布局鲁棒重建方法

针对使用传统单目相机的全自动三维重建方法结果精确度差和整体结构理解缺失等问题,提出一种结合视觉惯性里程计和由运动到结构的全自动室内三维布局重建系统.首先利用视觉里程计获得关键帧图像序列和对应空间位置姿态,并利用运动恢复结构算法计算精确相机位姿;然后利用多图视立体几何算法生成高质量稠密点云;最后基于曼哈顿世界假设,针对典型的现代建筑室内场景,设计一种基于规则的自底向上的布局重建方法,得到最终房间外轮廓布局.使用浙江大学CAD&CG实验室场景现场扫描数据集和人工合成的稠密点云数据集作为实验数据,在Ubuntu 16.04和PCL 1.9环境下进行实验.结果表明,文中方法对三维点云噪声容忍度高,能够有效地重建出室内场景的三维外轮廓布局.     

Constructing data supply chain based on layered PROV

The inability to effectively construct data supply chain in distributed environments is becoming one of the top concerns in big data area. Aiming at this problem, a novel method of constructing data supply chain based on layered PROV is proposed. First, to abstractly describe the data transfer processes from creation to distribution, a data provenance specification presented by W3C is used to standardize the information records of data activities within and across data platforms. Then, a distributed PROV data generation algorithm for multi-platform is designed. Further, we propose a tiered storage management of provenance based on summarization technology, which reduces the provenance records by compressing mid versions so as to realize multi-level management of PROV. In specific, we propose a hierarchical visual technique based on a layered query mechanism, which allows users to visualize data supply chain from general to detail. The experimental results show that the proposed approach can effectively improve the construction performance for data supply chain.     

面向手机3D动画自动生成的空间分层布局规划

手机3D动画自动生成系统是将用户发送的短信,经过信息抽取、情节规划等一系列的处理,最终生成一段与短信内容相关的三维动画并发送给接收方这一过程.布局规划是系统的一个重要组成部分,其功能是将模型放置到场景的可用空间上.通过对布局问题的研究,本文提出了一种基于区域布局和模型布局的分层布局方法,其包括定性规划和定量计算两个部分,利用语义网技术建立分层布局知识库,基于规则的方法推导出分层布局定性规划方案,并对模型位置进行动态计算.最后,通过实验验证了分层布局规划的有效性和多样性,满足了自动生成系统对布局规划的要求.