Visual Analytics Applications Research Articles

Using Visual Analytics to Develop Situation Awareness in Astrophysics

We present a novel collaborative visual analytics application for cognitively overloaded users in the astrophysics domain. The system was developed for scientists who need to analyze heterogeneous, complex data under time pressure, and make predictions and time-critical decisions rapidly and correctly under a constant influx of changing data. The Sunfall Data Taking system utilizes several novel visualization and analysis techniques to enable a team of geographically distributed domain specialists to effectively and remotely maneuver a custom-built instrument under challenging operational conditions. Sunfall Data Taking has been in production use for 2 years by a major international astrophysics collaboration (the largest data volume supernova search currently in operation), and has substantially improved the operational efficiency of its users. We describe the system design process by an interdisciplinary team, the system architecture and the results of an informal usability evaluation of the production system by domain experts in the context of Endsley's three levels of situation awareness.

Supporting the Process of Exploring and Interpreting Space–Time Multivariate Patterns: The Visual Inquiry Toolkit

While many data sets carry geographic and temporal references, our ability to analyze these datasets lags behind our ability to collect them because of the challenges posed by both data complexity and tool scalability issues. This study develops a visual analytics approach that leverages human expertise with visual, computational, and cartographic methods to support the application of visual analytics to relatively large spatio-temporal, multivariate data sets. We develop and apply a variety of methods for data clustering, pattern searching, information visualization, and synthesis. By combining both human and machine strengths, this approach has a better chance to discover novel, relevant, and potentially useful information that is difficult to detect by any of the methods used in isolation. We demonstrate the effectiveness of the approach by applying the Visual Inquiry Toolkit we developed to analyze a data set containing geographically referenced, time-varying and multivariate data for U.S. technology industries.

Fast Point-Feature Label Placement for Dynamic Visualizations

This paper describes a fast approach to automatic point label de-confliction on interactive maps. The general Map Labeling problem is NP-hard and has been the subject of much study for decades. Computerized maps have introduced interactive zooming and panning, which has intensified the problem. Providing dynamic labels for such maps typically requires a time-consuming pre-processing phase. In the realm of visual analytics, however, the labeling of interactive maps is further complicated by the use of massive datasets laid out in arbitrary configurations, thus rendering reliance on a pre-processing phase untenable. This paper offers a method for labeling point-features on dynamic maps in real time without pre-processing. The algorithm presented is efficient, scalable, and exceptionally fast; it can label interactive charts and diagrams at speeds of multiple frames per second on maps with tens of thousands of nodes. To accomplish this, the algorithm employs a novel geometric de-confliction approach, the ‘trellis strategy,’ along with a unique label candidate cost analysis to determine the “least expensive” label configuration. The speed and scalability of this approach make it well-suited for visual analytic applications.

Visual Elements Inventory InUrban Landscapes: Collecting Data For A VisualEnvironmental G.I.S.

The environment that we perceive, record and analyze as is the most complex of all landscapes, due to the multiple interactions between its built components and the dynamic social, economical and cultural standards of the society. Each urban landscape has its own history. Visual resource analysis can contribute to the management of urban environments by assisting in decision making or actions, such as determining which geographic areas are suitable for urbanization or deciding what to keep or what to develop at the district or neighborhood level because of its inherent or associated visual quality. There are many elements that can be recorded for an integrated analysis of the urban environment. In this paper, emphasis is given to those elements, methods and techniques that describe, analyze and evaluate the visual elements of a city. An application of visual element inventory and analysis in the Zografos area is presented and these data are entered into a spatial database, within a visual environmental Geographical Information System. Furthermore, the common problems of the Greek urban landscape are briefly discussed in this paper.

Visual discovery and analysis

We have developed a flexible software environment called ADVIZOR for visual information discovery. ADVIZOR complements existing assumptive-based analyses by providing a discovery-based approach. ADVIZOR consists of five parts: a rich set of flexible visual components, strategies for arranging the components for particular analyses, an in-memory data pool, data manipulation components, and container applications. Working together, ADVIZOR's architecture provides a powerful production platform for creating innovative visual query and analysis applications.