2011 IEEE Conference on Visual Analytics Science and Technology (VAST)最新文献_第4页

Visual social network analytics for relationship discovery in the enterprise 企业关系发现的可视化社会网络分析

2011 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2011-12-15 DOI: 10.1109/VAST.2011.6102443

Adam Perer, Ido Guy, E. Uziel, Inbal Ronen, Michal Jacovi

引用次数: 35

Interactive decision making using dissimilarity to visually represented prototypes 交互式决策使用不同的视觉表示原型

2011 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2011-12-15 DOI: 10.1109/VAST.2011.6102451

M. Migut, J. V. Gemert, M. Worring

{"title":"Interactive decision making using dissimilarity to visually represented prototypes","authors":"M. Migut, J. V. Gemert, M. Worring","doi":"10.1109/VAST.2011.6102451","DOIUrl":"https://doi.org/10.1109/VAST.2011.6102451","url":null,"abstract":"To make informed decisions, an expert has to reason with multi-dimensional, heterogeneous data and analysis results of these. Items in such datasets are typically represented by features. However, as argued in cognitive science, features do not yield an optimal space for human reasoning. In fact, humans tend to organize complex information in terms of prototypes or known cases rather than in absolute terms. When confronted with unknown data items, humans assess them in terms of similarity to these prototypical elements. Interestingly, an analogues similarity-to-prototype approach, where prototypes are taken from the data, has been successfully applied in machine learning. Combining such a machine learning approach with human prototypical reasoning in a Visual Analytics context requires to integrate similarity-based classification with interactive visualizations. To that end, the data prototypes should be visually represented to trigger direct associations to cases familiar to the domain experts. In this paper, we propose a set of highly interactive visualizations to explore data and classification results in terms of dissimilarities to visually represented prototypes. We argue that this approach not only supports human reasoning processes, but is also suitable to enhance understanding of heterogeneous data. The proposed framework is applied to a risk assessment case study in Forensic Psychiatry.","PeriodicalId":103998,"journal":{"name":"2011 IEEE Conference on Visual Analytics Science and Technology (VAST)","volume":"453 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116077529","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: 21

SensePlace2: GeoTwitter analytics support for situational awareness SensePlace2:为态势感知提供GeoTwitter分析支持

2011 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2011-12-15 DOI: 10.1109/VAST.2011.6102456

A. MacEachren, Anuj R. Jaiswal, A. Robinson, Scott Pezanowski, A. Savelyev, P. Mitra, Xiao Zhang, J. Blanford

{"title":"SensePlace2: GeoTwitter analytics support for situational awareness","authors":"A. MacEachren, Anuj R. Jaiswal, A. Robinson, Scott Pezanowski, A. Savelyev, P. Mitra, Xiao Zhang, J. Blanford","doi":"10.1109/VAST.2011.6102456","DOIUrl":"https://doi.org/10.1109/VAST.2011.6102456","url":null,"abstract":"Geographically-grounded situational awareness (SA) is critical to crisis management and is essential in many other decision making domains that range from infectious disease monitoring, through regional planning, to political campaigning. Social media are becoming an important information input to support situational assessment (to produce awareness) in all domains. Here, we present a geovisual analytics approach to supporting SA for crisis events using one source of social media, Twitter. Specifically, we focus on leveraging explicit and implicit geographic information for tweets, on developing place-time-theme indexing schemes that support overview+detail methods and that scale analytical capabilities to relatively large tweet volumes, and on providing visual interface methods to enable understanding of place, time, and theme components of evolving situations. Our approach is user-centered, using scenario-based design methods that include formal scenarios to guide design and validate implementation as well as a systematic claims analysis to justify design choices and provide a framework for future testing. The work is informed by a structured survey of practitioners and the end product of Phase-I development is demonstrated / validated through implementation in SensePlace2, a map-based, web application initially focused on tweets but extensible to other media.","PeriodicalId":103998,"journal":{"name":"2011 IEEE Conference on Visual Analytics Science and Technology (VAST)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125992651","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: 386

From movement tracks through events to places: Extracting and characterizing significant places from mobility data 从移动轨迹到事件再到地点:从移动数据中提取和描述重要地点

2011 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2011-12-15 DOI: 10.1109/VAST.2011.6102454

G. Andrienko, N. Andrienko, C. Hurter, S. Rinzivillo, S. Wrobel

引用次数: 130

A visual navigation system for querying neural stem cell imaging data 用于查询神经干细胞成像数据的视觉导航系统

2011 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2011-12-15 DOI: 10.1109/VAST.2011.6102459

Ishwar Kulkarni, Shanaz Y. Mistry, Brian J Cummings, M. Gopi

{"title":"A visual navigation system for querying neural stem cell imaging data","authors":"Ishwar Kulkarni, Shanaz Y. Mistry, Brian J Cummings, M. Gopi","doi":"10.1109/VAST.2011.6102459","DOIUrl":"https://doi.org/10.1109/VAST.2011.6102459","url":null,"abstract":"Cellular biology deals with studying the behavior of cells. Current time-lapse imaging microscopes help us capture the progress of experiments at intervals that allow for understanding of the dynamic and kinematic behavior of the cells. On the other hand, these devices generate such massive amounts of data (250GB of data per experiment) that manual sieving of data to identify interesting patterns becomes virtually impossible. In this paper we propose an end-to-end system to analyze time-lapse images of the cultures of human neural stem cells (hNSC), that includes an image processing system to analyze the images to extract all the relevant geometric and statistical features within and between images, a database management system to manage and handle queries on the data, a visual analytic system to navigate through the data, and a visual query system to explore different relationships and correlations between the parameters. In each stage of the pipeline we make novel algorithmic and conceptual contributions, and the entire system design is motivated by many different yet unanswered exploratory questions pursued by our neurobiologist collaborators. With a few examples we show how such abstract biological queries can be analyzed and answered by our system.","PeriodicalId":103998,"journal":{"name":"2011 IEEE Conference on Visual Analytics Science and Technology (VAST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129964791","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

Perception-based visual quality measures 基于感知的视觉质量测量

2011 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2011-12-15 DOI: 10.1109/VAST.2011.6102437

Georgia Albuquerque, M. Eisemann, M. Magnor

引用次数: 51

Visual analytical approaches to evaluating uncertainty and bias in crowd sourced crisis information 评估群众源危机信息的不确定性和偏差的可视化分析方法

2011 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2011-12-15 DOI: 10.1109/VAST.2011.6102470

I. Dillingham, J. Dykes, J. Wood

引用次数: 5

A visual analytics process for maritime resource allocation and risk assessment 海洋资源分配和风险评估的可视化分析过程

2011 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2011-12-15 DOI: 10.1109/VAST.2011.6102460

A. Malik, Ross Maciejewski, Ben Maule, D. Ebert

{"title":"A visual analytics process for maritime resource allocation and risk assessment","authors":"A. Malik, Ross Maciejewski, Ben Maule, D. Ebert","doi":"10.1109/VAST.2011.6102460","DOIUrl":"https://doi.org/10.1109/VAST.2011.6102460","url":null,"abstract":"In this paper, we present our collaborative work with the U.S. Coast Guard's Ninth District and Atlantic Area Commands where we developed a visual analytics system to analyze historic response operations and assess the potential risks in the maritime environment associated with the hypothetical allocation of Coast Guard resources. The system includes linked views and interactive displays that enable the analysis of trends, patterns and anomalies among the U.S. Coast Guard search and rescue (SAR) operations and their associated sorties. Our system allows users to determine the potential change in risks associated with closing certain stations in terms of response time, potential lives and property lost and provides optimal direction as to the nearest available station. We provide maritime risk assessment tools that allow analysts to explore Coast Guard coverage for SAR operations and identify regions of high risk. The system also enables a thorough assessment of all SAR operations conducted by each Coast Guard station in the Great Lakes region. Our system demonstrates the effectiveness of visual analytics in analyzing risk within the maritime domain and is currently being used by analysts at the Coast Guard Atlantic Area.","PeriodicalId":103998,"journal":{"name":"2011 IEEE Conference on Visual Analytics Science and Technology (VAST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130921406","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: 46

Visual sentiment analysis on twitter data streams 推特数据流的视觉情感分析

2011 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2011-12-15 DOI: 10.1109/VAST.2011.6102472

M. Hao, Christian Rohrdantz, H. Janetzko, U. Dayal, D. Keim, L. Haug, M. Hsu

引用次数: 86

A two-stage framework for designing visual analytics system in organizational environments 组织环境中可视化分析系统设计的两阶段框架

2011 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2011-12-15 DOI: 10.1109/VAST.2011.6102463

Xiaoyu Wang, Wenwen Dou, T. Butkiewicz, E. Bier, W. Ribarsky

{"title":"A two-stage framework for designing visual analytics system in organizational environments","authors":"Xiaoyu Wang, Wenwen Dou, T. Butkiewicz, E. Bier, W. Ribarsky","doi":"10.1109/VAST.2011.6102463","DOIUrl":"https://doi.org/10.1109/VAST.2011.6102463","url":null,"abstract":"A perennially interesting research topic in the field of visual analytics is how to effectively develop systems that support organizational users' decision-making and reasoning processes. The problem is, however, most domain analytical practices generally vary from organization to organization. This leads to diverse designs of visual analytics systems in incorporating domain analytical processes, making it difficult to generalize the success from one domain to another. Exacerbating this problem is the dearth of general models of analytical workflows available to enable such timely and effective designs. To alleviate these problems, we present a two-stage framework for informing the design of a visual analytics system. This design framework builds upon and extends current practices pertaining to analytical workflow and focuses, in particular, on incorporating both general domain analysis processes as well as individual's analytical activities. We illustrate both stages and their design components through examples, and hope this framework will be useful for designing future visual analytics systems. We validate the soundness of our framework with two visual analytics systems, namely Entity Workspace [8] and PatViz [37].","PeriodicalId":103998,"journal":{"name":"2011 IEEE Conference on Visual Analytics Science and Technology (VAST)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132574568","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: 27