Visual Analytics of Stratigraphic Correlation for Multi-Attribute Well-Logging Data Exploration

Visual analytics techniques for large multi-attribute time series data

Time series data commonly occur when variables are monitored over time. Many real-world applications involve the comparison of long time series across multiple variables (multi-attributes). Often business people want to compare this year’s monthly sales with last year’s sales to make decisions. Data warehouse administrators (DBAs) want to know their daily data loading job performance. DBAs need...

Big data exploration through visual analytics

SAS Visual Analytics Explorer is an advanced data visualization and exploratory data analysis application that is a component of the SAS Visual Analytics solution. It excels at handling big data problems like the VAST challenge. With a wide range of visual analytics features and the ability to scale to massive datasets, SAS Visual Analytics Explorer enables analysts to find patterns and relatio...

Visual Analytics for Improving Exploration and Projection of Multi-Dimensional Data

In the last years visual analytics got an important research topic to keep track of the vast amounts of electronically stored data and gain new information out of the data. This thesis arose from several real application areas and deals with visual analytics of two data types, multi-dimensional time related event based data and multi-dimensional data without time stamp, which are very heterogen...

Uncertainty-aware Visual Analytics for Spatio-temporal Data Exploration

Multi-attribute Tradespace Exploration

Survivability is the ability of a system to minimize the impact of a finite-duration disturbance on value delivery (i.e., stakeholder benefit at cost), achieved through (1) the reduction of the likelihood or magnitude of a disturbance, (2) the satisfaction of a minimally acceptable level of value delivery during and after a disturbance, and/or (3) a timely recovery. Traditionally specified as a...