CPA-G&V: Interactive Stream Views: Visual Analysis of Streaming Data

标题：CPA-G&&V：交互式流视图：流数据的可视化分析PIS：马修·沃德博士和Elke Rundensteiner，WPI CS部门可视化是广泛应用领域中数据分析和决策的关键组件，因为它能够提供丰富的概述，并允许用户快速发现模式和离群值。虽然信息可视化方面的重要研究侧重于支持扫描静态数据集以寻找模式的过程，但将可视化应用于连续流数据的分析在很大程度上仍然是一个尚未开发的机会。然而，具有重大社会影响的领域，如科学发现、国土安全和医疗保健，经常需要实时处理规模和复杂性不断增加的数字数据流，这使得信息可视化的发展变得至关重要。为了解决这一问题，研究人员正在开发一种称为交互式流视图(Interactive Stream View，ISV)的计算基础设施，用于可视化、管理、分析和交互地探索实时数据流。这项研究在大容量流数据的可视化和交互方面开辟了新的天地，将屏幕、计算和感知资源限制考虑到负载控制和多分辨率抽象。在ISV中，分析师通过在数据视图中选择特征或通过显式调用特征提取过程来将他们的兴趣表达为查询。由强大的交互支持的定制显示展示了这些查询的结果，突出显示了它们的属性和抽象，同时还将它们链接到相应的数据。ISV使来自不同领域的专家，如生命体征监测和战术移动跟踪，能够直观地监控和探索他们的数据，提高他们在关键需求和高影响领域做出实时决策的效率。

TITLE: CPA-G&V: Interactive Stream Views: Visual Analysis of Streaming Data PIS: Drs. Matthew Ward and Elke Rundensteiner, WPI CS Department Visualization is a critical component for data analysis and decision-making in a wide range of application areas, both for its ability to provide rich overviews and to permit users to rapidly uncover patterns and outliers. While significant research in information visualization has focused on supporting the process of scanning static data sets in search of patterns, applying visualization to the analysis of continuously streaming data remains a largely untapped opportunity. However, domains of significant societal impact, such as scientific discovery, homeland security, and health care, routinely have to process digital data streams of ever increasing scale and complexity in real-time, making the advancement of information visualization to effectively support such visual stream analysis of paramount importance.To address this problem, the investigators are developing a computational infrastructure, called Interactive Stream Views (ISV), to visualize, manage, analyze, and interactively explore real-time data streams. This research breaks new ground in the visualization of and interactions on high-volume streaming data taking screen, computation, and perceptual resource constraints into account for load control and multiresolution abstraction. In ISV, analysts express their interests as queries, either by selecting features in data views or by the explicit invocation of feature-extraction processes. Customized displays supported by powerful interactions present the results of these queries, highlighting their attributes and abstractions, while also linking them to their corresponding data. ISV enables specialists from diverse domains, such as vital sign monitoring and tactical movement tracking, to visually monitor and explore their data, increasing their effectiveness in making real-time decisions in areas of critical need and high impact.