Journal of Visual Languages and Computing最新文献_第6页

Exploring density regions for analyzing dynamic graph data 探索用于分析动态图形数据的密度区域

Journal of Visual Languages and Computing Pub Date : 2018-02-01 DOI: 10.1016/j.jvlc.2017.09.007

Michael Burch

{"title":"Exploring density regions for analyzing dynamic graph data","authors":"Michael Burch","doi":"10.1016/j.jvlc.2017.09.007","DOIUrl":"https://doi.org/10.1016/j.jvlc.2017.09.007","url":null,"abstract":"<div><p>Static or dynamic graphs are typically visualized by either node-link diagrams, adjacency matrices<span>, adjacency lists<span>, or hybrids thereof. In particular, for the case of a changing graph structure a viewer wishes to be able to visually compare the graphs in a sequence. Doing such a comparison task rapidly and reliably demands for visually analyzing the dynamic graph for certain dynamic patterns. In this paper we describe a novel dynamic graph visualization that is based on the concept of smooth density fields generated by first splatting the link information of a given graph in a certain layout or visual metaphor. To further visually enhance the time-varying graph structures we add user-adaptable isolines to the resulting dynamic graph representation. The computed visual encoding of the dynamic graph is aesthetically appealing due to its smooth curves and can additionally be used to do comparisons in a long graph sequence, i.e., from an information visualization perspective it serves as an overview representation supporting to start more detailed analysis processes. To demonstrate the usefulness of the technique we explore real-world dynamic graph data by taking into account visual parameters like visual metaphors, node-link layouts, smoothing iterations, number of isolines, and different color codings. In this extended work we additionally incorporate matrix and list splatting while also supporting the selection of density regions with overlaid link information. Moreover, from the selected graph the user can automatically apply region comparisons with other graphs based on global and local density properties. Such a feature is in particular useful for finding commonalities, hence serving as a special filtering function.</span></span></p></div>","PeriodicalId":54754,"journal":{"name":"Journal of Visual Languages and Computing","volume":"44 ","pages":"Pages 133-144"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.jvlc.2017.09.007","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72106824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

A methodological evaluation of natural user interfaces for immersive 3D Graph explorations 用于沉浸式三维图形探索的自然用户界面的方法评估

Journal of Visual Languages and Computing Pub Date : 2018-02-01 DOI: 10.1016/j.jvlc.2017.11.002

Ugo Erra , Delfina Malandrino , Luca Pepe

引用次数: 20

Typeface size and weight and word location influence on relative size judgments in tag clouds 标签云中字体大小、权重和单词位置对相对大小判断的影响

Journal of Visual Languages and Computing Pub Date : 2018-02-01 DOI: 10.1016/j.jvlc.2017.11.009

Khaldoon Dhou , Mirsad Hadzikadic , Mark Faust

{"title":"Typeface size and weight and word location influence on relative size judgments in tag clouds","authors":"Khaldoon Dhou , Mirsad Hadzikadic , Mark Faust","doi":"10.1016/j.jvlc.2017.11.009","DOIUrl":"https://doi.org/10.1016/j.jvlc.2017.11.009","url":null,"abstract":"<div><p>This paper focuses on viewers’ perception of the relative size of words presented in tag clouds. Tag clouds are a type of visualization that displays the contents of a document as a cluster (cloud) of key words (tags) with frequency (importance) indicated by tag word features such as size or color, with variation of size within a tag cloud being the most common indicator of tag importance. Prior studies have shown that word size is the most influential factor of tag importance and tag memory. Systematic biases in relative size perception in tag clouds are therefore likely to have important implications for viewer understanding of tag cloud visualizations. Significant under- and over-perception of the relative size of tag words were observed, depending on the relative size ratio of the target tag words compared. The qualitative change in the direction of the estimation bias was predicted by a simple power-law model for size perception. This bias in relative size perception was modulated somewhat by a change to a bold typeface, but the typeface effect varied in a complex manner with the size and location of the tags. The results provide a first report of systematic biases in relative size judgment in tag clouds, suggest that, to a first approximation, simple power-law scaling models developed for simple displays containing 1–2 objects on a blank background, may be applicable to relative size judgments in complex tag clouds. The results may provide useful design guidance for tag cloud designers.</p></div>","PeriodicalId":54754,"journal":{"name":"Journal of Visual Languages and Computing","volume":"44 ","pages":"Pages 97-105"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.jvlc.2017.11.009","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72106828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12

Guest editorial: Special issue on information visualisation 客座编辑：信息可视化特刊

Journal of Visual Languages and Computing Pub Date : 2018-02-01 DOI: 10.1016/j.jvlc.2017.11.005

Ebad Banissi , Weidong Huang

引用次数: 0

Geovisualizing attribute uncertainty of interval and ratio variables: A framework and an implementation for vector data 区间和比率变量属性不确定性的地理可视化:矢量数据的框架与实现

Journal of Visual Languages and Computing Pub Date : 2018-02-01 DOI: 10.1016/j.jvlc.2017.11.007

Hyeongmo Koo , Yongwan Chun , Daniel A. Griffith

引用次数: 8

Overlap-free labeling of clustered networks based on Voronoi tessellation 基于Voronoi镶嵌的聚类网络无重叠标记

Journal of Visual Languages and Computing Pub Date : 2018-02-01 DOI: 10.1016/j.jvlc.2017.09.008

Hsiang-Yun Wu , Shigeo Takahashi , Rie Ishida

{"title":"Overlap-free labeling of clustered networks based on Voronoi tessellation","authors":"Hsiang-Yun Wu , Shigeo Takahashi , Rie Ishida","doi":"10.1016/j.jvlc.2017.09.008","DOIUrl":"https://doi.org/10.1016/j.jvlc.2017.09.008","url":null,"abstract":"<div><p>Properly drawing clustered networks significantly improves the visual readability of the meaningful structures hidden behind the associated abstract relationships. Nonetheless, we often degrade the visual quality of such clustered graphs when we try to annotate the network nodes with text labels due to their unwanted mutual overlap. In this paper, we present an approach for aesthetically sparing labeling space around nodes of clustered networks by introducing a space partitioning technique. The key idea of our approach is to adaptively blend an aesthetic network layout based on conventional criteria with that obtained through centroidal Voronoi tessellation. Our technical contribution lies in choosing a specific distance metric in order to respect the aspect ratios of rectangular labels, together with a new scheme for adaptively exploring the proper balance between the two network layouts around each node. Centrality-based clustering is also incorporated into our approach in order to elucidate the underlying hierarchical structure embedded in the given network data, which also allows for the manual design of its overall layout according to visual requirements and preferences. The accompanying experimental results demonstrate that our approach can effectively mitigate visual clutter caused by the label overlaps in several important types of networks.</p></div>","PeriodicalId":54754,"journal":{"name":"Journal of Visual Languages and Computing","volume":"44 ","pages":"Pages 106-119"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.jvlc.2017.09.008","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72106825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Rainbow boxes: A new technique for overlapping set visualization and two applications in the biomedical domain 彩虹盒：一种新的重叠集可视化技术及其在生物医学领域的两个应用

Journal of Visual Languages and Computing Pub Date : 2017-12-01 DOI: 10.1016/j.jvlc.2017.09.003

Jean-Baptiste Lamy , Hélène Berthelot , Coralie Capron , Madeleine Favre

{"title":"Rainbow boxes: A new technique for overlapping set visualization and two applications in the biomedical domain","authors":"Jean-Baptiste Lamy , Hélène Berthelot , Coralie Capron , Madeleine Favre","doi":"10.1016/j.jvlc.2017.09.003","DOIUrl":"https://doi.org/10.1016/j.jvlc.2017.09.003","url":null,"abstract":"<div><p>Overlapping set visualization is a well-known problem in information visualization. This problem considers elements and sets containing all or part of the elements, a given element possibly belonging to more than one set. A typical example is the properties of the 20 amino-acids. A more complex application is the visual comparison of the contraindications or the adverse effects of several similar drugs. The knowledge involved is voluminous, each drug has many contraindications and adverse effects, some of them are shared with other drugs. Another real-life application is the visualization of gene annotation, each gene product being annotated with several annotation terms indicating the associated biological processes, molecular functions and cellular components.</p><p>In this paper, we present rainbow boxes, a novel technique for visualizing overlapping sets, and its application to the presentation of the properties of amino-acids, the comparison of drug properties, and the visualization of gene annotation. This technique requires solving a combinatorial optimization problem; we propose a specific heuristic and we evaluate and compare it to general optimization algorithms. We also describe a user study comparing rainbow boxes to tables and showing that the former allowed physicians to find information significantly faster. Finally, we discuss the limits and the perspectives of rainbow boxes.</p></div>","PeriodicalId":54754,"journal":{"name":"Journal of Visual Languages and Computing","volume":"43 ","pages":"Pages 71-82"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.jvlc.2017.09.003","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72090193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 26

Visualizing trace of Java collection APIs by dynamic bytecode instrumentation 通过动态字节码检测可视化Java集合API的跟踪

Journal of Visual Languages and Computing Pub Date : 2017-12-01 DOI: 10.1016/j.jvlc.2017.04.006

Tufail Muhammad , Zahid Halim , Majid Ali Khan

{"title":"Visualizing trace of Java collection APIs by dynamic bytecode instrumentation","authors":"Tufail Muhammad , Zahid Halim , Majid Ali Khan","doi":"10.1016/j.jvlc.2017.04.006","DOIUrl":"https://doi.org/10.1016/j.jvlc.2017.04.006","url":null,"abstract":"<div><p><span><span>Object-oriented languages<span> are widely used in software development to help the developer in using dynamic data structures which evolve during program execution. However, the task of program comprehension and performance analysis necessitates the understanding of data structures used in a program. Particularly, in understanding which </span></span>application programming interface (API) objects are used during runtime of a program. The objective of this work is to give a compact view of the complete program code information at a single glance and to provide the user with an interactive environment to explore details of a given program. This work presents a novel interactive visualization tool for collection framework usage, in a Java program, based on hierarchical treemap. A given program is instrumented during execution time and data recorded into a log file. The log file is then converted to </span>extensible markup language (XML)-based tree format which proceeds to the visualization component. The visualization provides a global view to the usage of collection API objects at different locations during program execution. We conduct an empirical study to evaluate the impact of the proposed visualization in program comprehension. The experimental group (having the proposed tool support), on average, completes the tasks in 45% less time as compared to the control group (not provided with the proposed tool). Results show that the proposed tool enables to comprehend more information with less effort and time. We have also evaluated the performance of the proposed tool using 20 benchmark software tools. The proposed tool is anticipated to help the developer in understanding Java programs and assist in program comprehension and maintenance by identifying APIs usage and their patterns.</p></div>","PeriodicalId":54754,"journal":{"name":"Journal of Visual Languages and Computing","volume":"43 ","pages":"Pages 14-29"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.jvlc.2017.04.006","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72090194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Pattern discovery: A progressive visual analytic design to support categorical data analysis 模式发现：一种支持分类数据分析的渐进视觉分析设计

Journal of Visual Languages and Computing Pub Date : 2017-12-01 DOI: 10.1016/j.jvlc.2017.05.004

Hanqing Zhao , Huijun Zhang , Yan Liu , Yongzhen Zhang , Xiaolong (Luke) Zhang

{"title":"Pattern discovery: A progressive visual analytic design to support categorical data analysis","authors":"Hanqing Zhao , Huijun Zhang , Yan Liu , Yongzhen Zhang , Xiaolong (Luke) Zhang","doi":"10.1016/j.jvlc.2017.05.004","DOIUrl":"https://doi.org/10.1016/j.jvlc.2017.05.004","url":null,"abstract":"<div><p><span><span>When using data-mining tools to analyze big data, users often need tools to support the understanding of individual data attributes and control the analysis progress. This requires the integration of </span>data-mining algorithms with interactive tools to manipulate data and analytical process. This is where visual analytics can help. More than simple visualization of a dataset or some computation results, visual analytics provides users an environment to iteratively explore different inputs or parameters and see the corresponding results. In this research, we explore a design of progressive visual analytics to support the analysis of </span>categorical data with a data-mining algorithm, Apriori. Our study focuses on executing data mining techniques step-by-step and showing intermediate result at every stage to facilitate sense-making. Our design, called Pattern Discovery Tool, targets for a medical dataset. Starting with visualization of data properties and immediate feedback of users’ inputs or adjustments, Pattern Discovery Tool could help users detect interesting patterns and factors effectively and efficiently. Afterward, further analyses such as statistical methods could be conducted to test those possible theories.</p></div>","PeriodicalId":54754,"journal":{"name":"Journal of Visual Languages and Computing","volume":"43 ","pages":"Pages 42-49"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.jvlc.2017.05.004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72090191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

High-dimensional data visualization by interactive construction of low-dimensional parallel coordinate plots 交互式构造低维平行坐标图实现高维数据可视化

Journal of Visual Languages and Computing Pub Date : 2017-12-01 DOI: 10.1016/j.jvlc.2017.03.001

Takayuki Itoh , Ashnil Kumar , Karsten Klein , Jinman Kim

{"title":"High-dimensional data visualization by interactive construction of low-dimensional parallel coordinate plots","authors":"Takayuki Itoh , Ashnil Kumar , Karsten Klein , Jinman Kim","doi":"10.1016/j.jvlc.2017.03.001","DOIUrl":"https://doi.org/10.1016/j.jvlc.2017.03.001","url":null,"abstract":"<div><p><span>Parallel coordinate plots (PCPs) are among the most useful techniques for the visualization and exploration of high-dimensional data spaces. They are especially useful for the representation of correlations among the dimensions, which identify relationships and </span>interdependencies between variables. However, within these high-dimensional spaces, PCPs face difficulties in displaying the correlation between combinations of dimensions and generally require additional display space as the number of dimensions increases. In this paper, we present a new technique for high-dimensional data visualization in which a set of low-dimensional PCPs are interactively constructed by sampling user-selected subsets of the high-dimensional data space. In our technique, we first construct a graph visualization of sets of well-correlated dimensions. Users observe this graph and are able to interactively select the dimensions by sampling from its cliques, thereby dynamically specifying the most relevant lower dimensional data to be used for the construction of focused PCPs. Our interactive sampling overcomes the shortcomings of the PCPs by enabling the visualization of the most meaningful dimensions (i.e., the most relevant information) from high-dimensional spaces. We demonstrate the effectiveness of our technique through two case studies, where we show that the proposed interactive low-dimensional space constructions were pivotal for visualizing the high-dimensional data and discovering new patterns.</p></div>","PeriodicalId":54754,"journal":{"name":"Journal of Visual Languages and Computing","volume":"43 ","pages":"Pages 1-13"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.jvlc.2017.03.001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72090192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 32