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.
