2022 IEEE 15th Pacific Visualization Symposium (PacificVis)最新文献

Visual Analytics of Multiple Network Ranking Based on Structural Similarity 基于结构相似度的多网络排序可视化分析

2022 IEEE 15th Pacific Visualization Symposium (PacificVis) Pub Date : 2022-04-01 DOI: 10.1109/PacificVis53943.2022.00032

Aosheng Cheng, Yulong Yin, Zhenyu Yan, Yuhua Liu, Zhiguang Zhou

{"title":"Visual Analytics of Multiple Network Ranking Based on Structural Similarity","authors":"Aosheng Cheng, Yulong Yin, Zhenyu Yan, Yuhua Liu, Zhiguang Zhou","doi":"10.1109/PacificVis53943.2022.00032","DOIUrl":"https://doi.org/10.1109/PacificVis53943.2022.00032","url":null,"abstract":"Ranking the node importance in complex networks has been widely applied for different purposes, such as web search, resource allocation, and network security. However, existing node ranking methods are almost single network ranking using only one relationship, or aggregate the node ranking scores on multiple networks with equal weight, which are insufficient to construct reasonable multiple network rankings, since the association information among multiple networks is largely ignored. Thus, we propose a multiple network visualization framework by fusing multiple networks to obtain credible node ranking scores. After measuring the scores of nodes in each single network by the classic PageRank, a network weight self-adjustment model based on structural similarities between pair-wise networks is designed to strengthen the common features of multiple networks or their distinct characteristics. Then, a combined score for each node is computed by a weighted sum of its individual ranking scores on multiple networks. Besides, we provide a set of visualization and interaction interfaces, enabling users to intuitively explore, optimize and compare the multiple network rankings. Case studies on real datasets show that our system is flexible to adapt to different application scenarios, and users can successfully solve multiple network ranking tasks efficiently.","PeriodicalId":117284,"journal":{"name":"2022 IEEE 15th Pacific Visualization Symposium (PacificVis)","volume":"206 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114237456","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

Hierarchical Multifocus Navigation in Text Annotation Data 文本标注数据中的分层多焦点导航

2022 IEEE 15th Pacific Visualization Symposium (PacificVis) Pub Date : 2022-04-01 DOI: 10.1109/PacificVis53943.2022.00026

M. Baumann, Jena Satkunarajan, Steffen Koch, T. Ertl

引用次数: 0

Browser-based Hyperbolic Visualization of Graphs 基于浏览器的图形双曲可视化

2022 IEEE 15th Pacific Visualization Symposium (PacificVis) Pub Date : 2022-04-01 DOI: 10.48550/arXiv.2205.08028

Jacob Miller, S. Kobourov, Vahan Huroyan

引用次数: 2

Hybrid Traffic Route Visual Recommendation Based on Multilayer Complex Networks 基于多层复杂网络的混合交通路径视觉推荐

2022 IEEE 15th Pacific Visualization Symposium (PacificVis) Pub Date : 2022-04-01 DOI: 10.1109/PacificVis53943.2022.00030

Tangyuan Zou, Song Wang, Hanglin Li, Yadong Wu

引用次数: 3

Tuning Automatic Summarization for Incident Report Visualization 调整事件报告可视化的自动摘要

2022 IEEE 15th Pacific Visualization Symposium (PacificVis) Pub Date : 2022-04-01 DOI: 10.1109/PacificVis53943.2022.00031

Nathan Danneman, R. Gove

引用次数: 0

Persuasive Data Storytelling with a Data Video during Covid-19 Infodemic: Affective Pathway to Influence the Users' Perception about Contact Tracing Apps in less than 6 Minutes 在Covid-19信息大流行期间，用数据视频讲有说服力的数据故事:在不到6分钟的时间内影响用户对接触者追踪应用程序的看法的情感途径

2022 IEEE 15th Pacific Visualization Symposium (PacificVis) Pub Date : 2022-04-01 DOI: 10.1109/PacificVis53943.2022.00028

Y. Sakamoto, Samar Sallam, Aaro Salo, Jason Leboe-McGowan, Pourang Irani

{"title":"Persuasive Data Storytelling with a Data Video during Covid-19 Infodemic: Affective Pathway to Influence the Users' Perception about Contact Tracing Apps in less than 6 Minutes","authors":"Y. Sakamoto, Samar Sallam, Aaro Salo, Jason Leboe-McGowan, Pourang Irani","doi":"10.1109/PacificVis53943.2022.00028","DOIUrl":"https://doi.org/10.1109/PacificVis53943.2022.00028","url":null,"abstract":"The current pandemic showed us the importance of swiftly disseminating data-based information to the masses of people. This study explores an affect-centered narrative to convey data-driven messages regarding contact tracing apps (CTAs) using video as a medium (i.e., data video). A between-subjects online study compared the effect of three storytelling approaches on viewers' perception. A video developed by Google was selected as the baseline video (Control Condition; 2min 23s) due to its high quality and relevance to CTAs. The central messages of this baseline video were; a) how CTAs work, and b) how safe and effective CTAs are. Infographics supporting these messages were then added to the baseline video (the second condition; 3min 19s); this was a simple data video (DV), and it did not intend to induce specific emotional experiences in participants (i.e., cognition-centered video). Finally, an affect-focused DV (AFDV) was also created by emphasizing the emotion-based narrative aspect of the message (the third condition; 4min 6s). In this video, three cute human-like cartoon characters were introduced. Viewers in this condition needed to process both cognitive and affective information. Note all three videos (i.e., control video, DV, and AFDV) conveyed identical messages. Participants watched one of these three videos only once, and we explored the video effect on their perception. Our results repeatedly indicated the potential benefits of including affect in data storytelling.","PeriodicalId":117284,"journal":{"name":"2022 IEEE 15th Pacific Visualization Symposium (PacificVis)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115264171","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: 0

Evaluating the Effect of Enhanced Text-Visualization Integration on Combating Misinformation in Data Story 评估增强文本可视化集成在数据故事中打击错误信息的效果

2022 IEEE 15th Pacific Visualization Symposium (PacificVis) Pub Date : 2022-04-01 DOI: 10.48550/arXiv.2205.11911

Chengbo Zheng, Xiaojuan Ma

{"title":"Evaluating the Effect of Enhanced Text-Visualization Integration on Combating Misinformation in Data Story","authors":"Chengbo Zheng, Xiaojuan Ma","doi":"10.48550/arXiv.2205.11911","DOIUrl":"https://doi.org/10.48550/arXiv.2205.11911","url":null,"abstract":"Misinformation has disruptive effects on our lives. Many researchers have looked into means to identify and combat misinformation in text or data visualization. However, there is still a lack of under-standing of how misinformation can be introduced when text and visualization are combined to tell data stories, not to mention how to improve the lay public's awareness of possible misperceptions about facts in narrative visualization. In this paper, we first analyze where misinformation could possibly be injected into the production-consumption process of data stories through a literature survey. Then, as a first step towards combating misinformation in data stories, we explore possible defensive design methods to enhance the reader's awareness of information misalignment when data facts are scripted and visualized. More specifically, we conduct a between-subjects crowdsourcing study to investigate the impact of two design methods enhancing text-visualization integration, i.e., explanatory annotation and interactive linking, on users' awareness of misinformation in data stories. The study results show that although most participants still can not find misinformation, the two design methods can significantly lower the perceived credibility of the text or visualizations. Our work informs the possibility of fighting an infodemic through defensive design methods.","PeriodicalId":117284,"journal":{"name":"2022 IEEE 15th Pacific Visualization Symposium (PacificVis)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121724800","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: 0

Spatio-temporal Analysis of Multi-agent Scheduling Behaviors on Fixed-track Networks 固定轨道网络中多智能体调度行为的时空分析

2022 IEEE 15th Pacific Visualization Symposium (PacificVis) Pub Date : 2022-04-01 DOI: 10.1109/PacificVis53943.2022.00011

S. Agarwal, Günter Wallner, Jeremy Watson, Fabian Beck

{"title":"Spatio-temporal Analysis of Multi-agent Scheduling Behaviors on Fixed-track Networks","authors":"S. Agarwal, Günter Wallner, Jeremy Watson, Fabian Beck","doi":"10.1109/PacificVis53943.2022.00011","DOIUrl":"https://doi.org/10.1109/PacificVis53943.2022.00011","url":null,"abstract":"Multi-agent systems require coordination among the agents to solve a given task. For movement on fixed-track networks, traditional scheduling algorithms have dominated so far, but the interest in autonomous and intelligent agents is growing as they promise to react to unexpected and exceptional situations more robustly. In this paper, we study data from the Flatland 2020 NeurIPS Competition, where trains move through a virtual rail network. We developed a timeline-based visualization that provides an overview of all train movements in a simulated episode, clearly hinting at different phases, non-optimal routes, and issues such as deadlocks. This view is complemented with a map view and a graph view, interactively linked through highlighting and synchronous animation. Defining regions of interest in the map builds an analysis graph for detailed inspection. A comparison mode allows contrasting two different episodes regarding the same rail network across all views. We have conducted this application study in close collaboration with the Flatland community. Identified analysis goals stem from interviews with key persons of the community, while the approach itself was developed in two iterations based on feedback from experts with diverse backgrounds. This feedback, together with an analysis of the winning submissions from the competition, confirms that the initial analysis goals can be answered.","PeriodicalId":117284,"journal":{"name":"2022 IEEE 15th Pacific Visualization Symposium (PacificVis)","volume":"146 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122411999","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

dGG, dRNG, DSC: New Degree-based Shape-based Faithfulness Metrics for Large and Complex Graph Visualization dGG, dRNG, DSC:基于度的基于形状的大型复杂图形可视化信誉度度量

2022 IEEE 15th Pacific Visualization Symposium (PacificVis) Pub Date : 2022-04-01 DOI: 10.1109/PacificVis53943.2022.00014

Seok-Hee Hong, A. Meidiana, James Wood, J. P. Ataides, P. Eades, Kunsoo Park

{"title":"dGG, dRNG, DSC: New Degree-based Shape-based Faithfulness Metrics for Large and Complex Graph Visualization","authors":"Seok-Hee Hong, A. Meidiana, James Wood, J. P. Ataides, P. Eades, Kunsoo Park","doi":"10.1109/PacificVis53943.2022.00014","DOIUrl":"https://doi.org/10.1109/PacificVis53943.2022.00014","url":null,"abstract":"Shape-based metrics measure how faithfully a drawing D of a large graph G shows the structure of graph, by comparing the similarity between G and a proximity graph S computed from D. Although these metrics can successfully evaluate drawings of large graphs, they are limited to relatively sparse graphs, since existing metrics use planar proximity graphs GG (Gabriel Graph) and RNG (Relative Neighbourhood Graph). This paper presents new shape-based faithfulness metrics for evaluating drawings of large and complex graphs, using high-order prox-imity graphs k-GG and k-RNG. Extensive experiments demonstrate that our new shape-based metrics using degree-based proximity graphs dGG and dRNG can more accurately measure the faithful-ness of drawings of large and complex graphs, with a significant improvement of over 100% better, on average, than the existing shape-based metrics using GG and RNG. Moreover, we present a new shape change faithfulness metric DSC for evaluating drawings of dynamic graphs, by measuring how proportional the geometric shape change in the drawings of dynamic graphs is to the ground truth change in dynamic graphs. Validation using deformation experiments support that DSC can accurately measure shape change faithfulness in dynamic graph drawing. Furthermore, we present extensive comparison experiments of ten popular graph layouts using our new shape-based metrics dGG, dRNG and DSC, to recommend which layouts can give a better shape-faithful graph drawing for large and complex graphs.","PeriodicalId":117284,"journal":{"name":"2022 IEEE 15th Pacific Visualization Symposium (PacificVis)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131455120","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: 0

Virtual Inspection of Additively Manufactured Parts 增材制造零件的虚拟检测

2022 IEEE 15th Pacific Visualization Symposium (PacificVis) Pub Date : 2022-04-01 DOI: 10.1109/PacificVis53943.2022.00017

Pavol Klacansky, H. Miao, A. Gyulassy, A. Townsend, Kyle Champley, J. Tringe, Valerio Pascucci, P. Bremer

{"title":"Virtual Inspection of Additively Manufactured Parts","authors":"Pavol Klacansky, H. Miao, A. Gyulassy, A. Townsend, Kyle Champley, J. Tringe, Valerio Pascucci, P. Bremer","doi":"10.1109/PacificVis53943.2022.00017","DOIUrl":"https://doi.org/10.1109/PacificVis53943.2022.00017","url":null,"abstract":"Advanced manufacturing techniques, such as additive manufacturing, enable the design of increasingly complex components for a wide range of industrial applications. However, this complexity makes qualification of the parts, determining whether a part is within some margin of error from the initial design, difficult. To inspect and qualify complex internal geometries that are not accessible with an external probe, parts are typically scanned with computed tomography (CT), and manually compared to the computer-aided design (CAD) model using visual inspections. Matching the CAD model to the 3D reconstructed object is challenging in a traditional desktop environment due to the lack of depth perception and 3D interaction. An additional challenge comes from the geometric complexity of CAD meshes and large-scale CT scans. We present a virtual reality (VR) system for manual qualification, providing a novel defect visualization method. First, we describe a semiautomatic CAD-to-Scan Registration approach in VR using a finite element mesh. Second, we introduce the Defect Box, which enables full-resolution inspection for massive scans and CAD-CT comparison of local defect regions. Finally, our system includes intuitive 3D Metrology methods that enable natural interactions for the measurement of features and defects in VR. We demonstrate our approach on both real and synthetic data and discuss feedback from four expert users in nondestructive qualification.","PeriodicalId":117284,"journal":{"name":"2022 IEEE 15th Pacific Visualization Symposium (PacificVis)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114713215","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