SunMap:一种基于热图和放射环的关联层次数据可视化方法
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摘要
针对食品安全等领域对数据空间分布和关联关系分析的需求,提出一种基于热图和放射环的关联层次数据可视化方法——Sun Map(Sunburst+Map).利用基于地理信息的热力型数据地图展示数据的地域分布,用基于节点排序的放射环可视化具有层次结构的数据,将热图置于放射环内,并用直线表示热图节点与放射环节点之间的关联;为减少视觉混乱,提出一种基于Bézier曲线的路径优化算法,通过设置过渡点,用三次Bézier曲线取代直线优化边;加入矩阵热图展示数据细节;采用数据选择、Sun Map和矩阵热图多视图联动等交互手段实现对关联层次数据的可视分析.将Sun Map应用于可视化全国农药残留侦测数据,通过用户研究对该方法进行评价.实验结果表明,该方法能有效地帮助用户快速找到目标信息,探寻隐含在数据之间的关联;它还可用于经济、金融、社会网络等领域的关联层次数据可视分析.
In order to satisfy the requirements of analyzing geographical distribution and relationships of data sets in food safety field, we proposed an associated hierarchical data visualization method named Sun Map, which is based on Sunburst and Heatmap. Firstly, a Heatmap based on geographical information is created to present geographical distribution of the dataset, and a sunburst is created to present the hierarchical structure of the dataset. Secondly, put the Heatmap into the center of sunburst, and use the lines connecting nodes between Heatmap and sunburst to present the relationships between them. Thirdly, execute the route optimization algorithm which introduces transiton points and uses Cubic Bézier curve instead of straight lines to represent the relationships to reduce visual clutter. Finally, a Matrix-Heatmap view, which is composed of an adjacent matrix and two bar charts, is used to represent the detail of the dataset. Multi-view linkage of data selection, Sun Map, Matrix-Heatmap and some other interactions help users analyze the associated hierarchical data. We applied this methods to the pesticide residues detection data and the result of user studies demonstrates that this visual design is effective in helping users to find object information and relationships among complex hierarchical data. The method can also be used in other fields of associated hierarchical data like economic, financial and social networks.
In order to satisfy the requirements of analyzing geographical distribution and relationships of data sets in food safety field, we proposed an associated hierarchical data visualization method named Sun Map, which is based on Sunburst and Heatmap. Firstly, a Heatmap based on geographical information is created to present geographical distribution of the dataset, and a sunburst is created to present the hierarchical structure of the dataset. Secondly, put the Heatmap into the center of sunburst, and use the lines connecting nodes between Heatmap and sunburst to present the relationships between them. Thirdly, execute the route optimization algorithm which introduces transiton points and uses Cubic Bézier curve instead of straight lines to represent the relationships to reduce visual clutter. Finally, a Matrix-Heatmap view, which is composed of an adjacent matrix and two bar charts, is used to represent the detail of the dataset. Multi-view linkage of data selection, Sun Map, Matrix-Heatmap and some other interactions help users analyze the associated hierarchical data. We applied this methods to the pesticide residues detection data and the result of user studies demonstrates that this visual design is effective in helping users to find object information and relationships among complex hierarchical data. The method can also be used in other fields of associated hierarchical data like economic, financial and social networks.
引文
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[23]Gou L,Zhang X L.Treenetviz:revealing patterns of networks over tree structures[J].IEEE Transactions on Visualization and Computer Graphics,2011,17(12):2449-2458
[24]Chen Yi,Zhang Xinyue,Chen Hongqian,et al.Hybrid layout algorithm for double interrelated tree[J].Journal of System Simulation,2014,26(9):2160-2165(in Chinese)(陈谊,张鑫跃,陈红倩,等.一种双关联树的混合布局算法[J].系统仿真学报,2014,26(9):2160-2165)
[25]Sugiyama K,Misue K.Visualization of structural information:automatic drawing of compound digraphs[J].IEEE Transactions on Systems,Man and Cybernetics,1991,21(4):876-892
[26]Ziegler J,Kunz C,Botsch V.Matrix browser:visualizing and exploring large networked information spaces[C]//Proceedings of the CHI’02 Extended Abstracts on Human Factors in Computing Systems.New York:ACM Press,2002:602-603
[2]Keim D A,Panse C,Sips M,et al.Visual data mining in large geospatial point sets[J].IEEE Transactions on Computer Graphics and Applications,2004,24(5):36-44
[3]Buchin K,Speckmann B,Verbeek K.Flow map layout via spiral trees[J].IEEE Transactions on Visualization and Computer Graphics,2011,17(12):2536-2544
[4]Gastner M T,Newman M E J.Diffusion-based method for producing density-equalizing maps[J].Proceedings of the National Academy of Sciences of the United States of America,2004,101(20):7499-7504
[5]Dorling D,Barford A,Newman M.Worldmapper:the world as you've never seen it before[J].IEEE Transactions on Visualization and Computer Graphics,2006,12(5):757-764
[6]Keim D A,Panse C,North S C.Medial-axis-based cartograms[J].IEEE Transactions on Computer Graphics and Applications,2005,25(3):60-68
[7]Speckmann B,Verbeek K.Necklace maps[J].IEEE Transactions on Visualization and Computer Graphics,2010,16(6):881-889
[8]Li J,Zhang K,Meng Z P.Vismate:interactive visual analysis of station-based observation data on climate changes[C]//Proceedings of IEEE Conference on Visual Analytics Science and Technology.Los Alamitos:IEEE Computer Society Press,2014:133-142
[9]Collins C,Penn G,Carpendale S.Bubble sets:revealing set relations with isocontours over existing visualizations[J].IEEE Transactions on Visualization and Computer Graphics,2009,15(6):1009-1016
[10]Alper B,Riche N H,Ramos G,et al.Design study of linesets,a novel set visualization technique[J].IEEE Transactions on Visualization and Computer Graphics,2011,17(12):2259-2267
[11]Ko S,Afzal S,Walton S,et al.Analyzing high-dimensional multivariate network links with integrated anomaly detection,highlighting and exploration[C]//Proceedings of IEEE Conference on Visual Analytics Science and Technology.Los Alamitos:IEEE Computer Society Press,2014:83-92
[12]Jiang X R,Zheng C Y,Tian Y,et al.Large-scale taxi O/D visual analytics for understanding metropolitan human movement patterns[J].Journal of Visualization,2015,18(2):185-200
[13]Liao Z F,Li Y,Peng Y N,et al.A semantic-enhanced trajectory visual analytics for digital forensic[J].Journal of Visualization,2015,18(2):173-184
[14]Chen S M,Yuan X R,Wang Z H,et al.Interactive visual discovering of movement patterns from sparsely sampled geotagged social media data[J].IEEE Transactions on Visualization and Computer Graphics,2016,22(1):270-279
[15]Wang F,Chen W,Wu F R,et al.A visual reasoning approach for data-driven transport assessment on urban roads[C]//Proceedings of IEEE Conference on Visual Analytics Science and Technology.Los Alamitos:IEEE Computer Society Press,2014:103-112
[16]Stasko J,Zhang E.Focus+context display and navigation techniques for enhancing radial,space-filling hierarchy visualizations[C]//Proceedings of IEEE Symposium on Information Visualization.Los Alamitos:IEEE Computer Society Press,2000:57-65
[17]Chen Y,Zhang X Y,Feng Y C,et al.Sunburst with ordered nodes based on hierarchical clustering:a visual analyzing method for associated hierarchical pesticide residue data[J].Journal of Visualization,2015,18(2):237-254
[18]Zhang Xin,Yuan Xiaoru.Treemap visualization[J].Journal of Computer-Aided Design&Computer Graphics,2012,24(9):1113-1124(in Chinese)(张昕,袁晓如.树图可视化[J].计算机辅助设计与图形学学报,2012,24(9):1113-1124)
[19]Chen Yi,Hu Haiyun,Li Zhilong.Performance compare and optimization of rectangular treemap layout algorithms[J].Journal of Computer-Aided Design&Computer Graphics,2013,25(11):1623-1634(in Chinese)(陈谊,胡海云,李志龙.树图布局算法的比较与优化研究[J].计算机辅助设计与图形学学报,2013,25(11):1623-1634)
[20]Storey M A D,Müller H A.Graph layout adjustment strategies[M]//Lecture Notes in Computer Science.Heidelberg:Springer,1996,1027:487-499
[21]Fekete J,Wang D,Dang N,et al.Interactive poster:overlaying graph links on treemaps[C]//Proceedings of IEEE Symposium on Information Visualization.Los Alamitos:IEEE Computer Society Press,2003:82-83
[22]Neumann P,Schlechtweg S,Carpendale S.Arc Trees:visualizing relations in hierarchical data[C]//Proceedings of the 7th Joint Eurographics/IEEE VGTC Conference on Visualization.Los Alamitos:IEEE Computer Society Press,2005:53-60
[23]Gou L,Zhang X L.Treenetviz:revealing patterns of networks over tree structures[J].IEEE Transactions on Visualization and Computer Graphics,2011,17(12):2449-2458
[24]Chen Yi,Zhang Xinyue,Chen Hongqian,et al.Hybrid layout algorithm for double interrelated tree[J].Journal of System Simulation,2014,26(9):2160-2165(in Chinese)(陈谊,张鑫跃,陈红倩,等.一种双关联树的混合布局算法[J].系统仿真学报,2014,26(9):2160-2165)
[25]Sugiyama K,Misue K.Visualization of structural information:automatic drawing of compound digraphs[J].IEEE Transactions on Systems,Man and Cybernetics,1991,21(4):876-892
[26]Ziegler J,Kunz C,Botsch V.Matrix browser:visualizing and exploring large networked information spaces[C]//Proceedings of the CHI’02 Extended Abstracts on Human Factors in Computing Systems.New York:ACM Press,2002:602-603