Evaluation of a Bundling Technique for Parallel Coordinates

We describe a technique for bundled curve representations in parallel-coordinates plots and present a controlled user study evaluating their effectiveness. Replacing the traditional C^0 polygonal lines by C^1 continuous piecewise Bezier curves makes it easier to visually trace data points through each coordinate axis. The resulting Bezier curves can then be bundled to visualize data with given cluster structures. Curve bundles are efficient to compute, provide visual separation between data clusters, reduce visual clutter, and present a clearer overview of the dataset. A controlled user study with 14 participants confirmed the effectiveness of curve bundling for parallel-coordinates visualization: 1) compared to polygonal lines, it is equally capable of revealing correlations between neighboring data attributes; 2) its geometric cues can be effective in displaying cluster information. For some datasets curve bundling allows the color perceptual channel to be applied to other data attributes, while for complex cluster patterns, bundling and color can represent clustering far more clearly than either alone

Development of a geovisual analytics environment using parallel coordinates with applications to tropical cyclone trend analysis

A global transformation is being fueled by unprecedented growth in the quality, quantity, and number of different parameters in environmental data through the convergence of several technological advances in data collection and modeling. Although these data hold great potential for helping us understand many complex and, in some cases, life-threatening environmental processes, our ability to generate such data is far outpacing our ability to analyze it. In particular, conventional environmental data analysis tools are inadequate for coping with the size and complexity of these data. As a result, users are forced to reduce the problem in order to adapt to the capabilities of the tools. To overcome these limitations, we must complement the power of computational methods with human knowledge, flexible thinking, imagination, and our capacity for insight by developing visual analysis tools that distill information into the actionable criteria needed for enhanced decision support. In light of said challenges, we have integrated automated statistical analysis capabilities with a highly interactive, multivariate visualization interface to produce a promising approach for visual environmental data analysis. By combining advanced interaction techniques such as dynamic axis scaling, conjunctive parallel coordinates, statistical indicators, and aerial perspective shading, we provide an enhanced variant of the classical parallel coordinates plot. Furthermore, the system facilitates statistical processes such as stepwise linear regression and correlation analysis to assist in the identification and quantification of the most significant predictors for a particular dependent variable. These capabilities are combined into a unique geovisual analytics system that is demonstrated via a pedagogical case study and three North Atlantic tropical cyclone climate studies using a systematic workflow. In addition to revealing several significant associations between environmental observations and tropical cyclone activity, this research corroborates the notion that enhanced parallel coordinates coupled with statistical analysis can be used for more effective knowledge discovery and confirmation in complex, real-world data sets

Development of a geovisual analytics environment using parallel coordinates with applications to tropical cyclone trend analysis

A global transformation is being fueled by unprecedented growth in the quality, quantity, and number of different parameters in environmental data through the convergence of several technological advances in data collection and modeling. Although these data hold great potential for helping us understand many complex and, in some cases, life-threatening environmental processes, our ability to generate such data is far outpacing our ability to analyze it. In particular, conventional environmental data analysis tools are inadequate for coping with the size and complexity of these data. As a result, users are forced to reduce the problem in order to adapt to the capabilities of the tools. To overcome these limitations, we must complement the power of computational methods with human knowledge, flexible thinking, imagination, and our capacity for insight by developing visual analysis tools that distill information into the actionable criteria needed for enhanced decision support. In light of said challenges, we have integrated automated statistical analysis capabilities with a highly interactive, multivariate visualization interface to produce a promising approach for visual environmental data analysis. By combining advanced interaction techniques such as dynamic axis scaling, conjunctive parallel coordinates, statistical indicators, and aerial perspective shading, we provide an enhanced variant of the classical parallel coordinates plot. Furthermore, the system facilitates statistical processes such as stepwise linear regression and correlation analysis to assist in the identification and quantification of the most significant predictors for a particular dependent variable. These capabilities are combined into a unique geovisual analytics system that is demonstrated via a pedagogical case study and three North Atlantic tropical cyclone climate studies using a systematic workflow. In addition to revealing several significant associations between environmental observations and tropical cyclone activity, this research corroborates the notion that enhanced parallel coordinates coupled with statistical analysis can be used for more effective knowledge discovery and confirmation in complex, real-world data sets

Exploration and Analysis of Information Visualization Techniques Applied to the TeachEngineering Digital Library

The rapid development of computing technologies in recent decades has allowed for data to be generated at unprecedented rates. As a result, users are challenged with the task of finding the precise information that they are looking for. Visualization techniques provide the ability to view and analyze data in different ways, helping users to find what they are looking for and gain additional insights. TeachEngineering is a digital library system where K-12 educators can search for high-quality lesson plans that meet national and state-specific educational standards. Users have several different types of criteria to search by, including: grade level, cost, time required, group size, keywords, source state, and educational standards. Being able to see how individual documents compare to specific variables can help identify additional results that are worthy of user consideration. Surveying visualization techniques, specific methods (scatterplots, parallel coordinates, star glyphs and hyperbolic trees) are qualitatively analyzed with regards to how they could be applied to TeachEngineering search query results. Each visualization type has advantages and limitations, and no single technique can be considered the definitive solution. Recommendations on conducting future experiments and research are included

Tools and theory to improve data analysis

This thesis proposes a scientific model to explain the data analysis process. I argue that data analysis is primarily a procedure to build un- derstanding and as such, it dovetails with the cognitive processes of the human mind. Data analysis tasks closely resemble the cognitive process known as sensemaking. I demonstrate how data analysis is a sensemaking task adapted to use quantitative data. This identification highlights a uni- versal structure within data analysis activities and provides a foundation for a theory of data analysis. The model identifies two competing chal- lenges within data analysis: the need to make sense of information that we cannot know and the need to make sense of information that we can- not attend to. Classical statistics provides solutions to the first challenge, but has little to say about the second. However, managing attention is the primary obstacle when analyzing big data. I introduce three tools for managing attention during data analysis. Each tool is built upon a different method for managing attention. ggsubplot creates embedded plots, which transform data into a format that can be easily processed by the human mind. lubridate helps users automate sensemaking out- side of the mind by improving the way computers handle date-time data. Visual Inference Tools develop expertise in young statisticians that can later be used to efficiently direct attention. The insights of this thesis are especially helpful for consultants, applied statisticians, and teachers of data analysis

Cognitive Foundations for Visual Analytics

In this report, we provide an overview of scientific/technical literature on information visualization and VA. Topics discussed include an update and overview of the extensive literature search conducted for this study, the nature and purpose of the field, major research thrusts, and scientific foundations. We review methodologies for evaluating and measuring the impact of VA technologies as well as taxonomies that have been proposed for various purposes to support the VA community. A cognitive science perspective underlies each of these discussions

A sketching-oriented design method for information visualization software.

The aim of this research is to describe a useful approach for supporting creativity and problem-solving in the design of Information Visualization software. This type of software is useful for helping people to understand large or complex collections of data by making the data easier to see and use. Because it can be so helpful, many people are motivated to create visualization software to address their own unique problems of understanding data. However, the techniques which visualizations use to enhance cognition of data are not widely known. Also, there are currently few resources which comprehensively describe a method for designing novel visualizations. Consequently, people who seek to build new Information Visualization tools are left to consult design examples, guidelines, and reference models, which do not adequately describe the visualization design process. The key question of the research concerns how Information Visualization methodologies should account for representation of the user, existing visualization design knowledge, and sketching. Given that the current methods of Information Visualization design are incomplete and show evidence of significant shortcomings, how can novice visualization design teams bridge these gaps by using methods from other design disciplines to successfully create effective visualizations To investigate this question, several studies were conducted. Also, a design methodology called So Viz was developed. It incorporates a participatory design approach, using sketching and visualization design patterns to support creativity and problem-solving. A prototype was designed using the SoViz approach. The key contributions of this thesis are results which show that Information Visualization designers can benefit from using this method. The thesis presents the results of using SoViz to create an Information Visualization prototype and describes the theoretical consequences for Information Visualization methodology

Decision Support Systems

Decision support systems (DSS) have evolved over the past four decades from theoretical concepts into real world computerized applications. DSS architecture contains three key components: knowledge base, computerized model, and user interface. DSS simulate cognitive decision-making functions of humans based on artificial intelligence methodologies (including expert systems, data mining, machine learning, connectionism, logistical reasoning, etc.) in order to perform decision support functions. The applications of DSS cover many domains, ranging from aviation monitoring, transportation safety, clinical diagnosis, weather forecast, business management to internet search strategy. By combining knowledge bases with inference rules, DSS are able to provide suggestions to end users to improve decisions and outcomes. This book is written as a textbook so that it can be used in formal courses examining decision support systems. It may be used by both undergraduate and graduate students from diverse computer-related fields. It will also be of value to established professionals as a text for self-study or for reference

Erweiterte virtuelle Umgebungen zur interaktiven, immersiven Verwendung von Funktionsmodellen

Dem Erkennen und Verstehen von komplexen Produktabhängigkeiten u. a. durch Visualisierung, auch über die klassischen Domänengrenzen hinweg, kommt eine zentrale Bedeutung, insbesondere während den frühen Konstruktionsphasen, zu. Im Rahmen dieser Arbeit wurde ein Prototyp entwickelt, mit dessen Hilfe Funktionsmodelle in virtuelle Umgebungen übertragen und interaktiv genutzt werden können. Dies fördert das interdisziplinäre Gesamtverständnis und unterstützt eine frühzeitige Qualitätskontrolle

Erweiterte virtuelle Umgebungen zur interaktiven, immersiven Verwendung von Funktionsmodellen

Dem Erkennen und Verstehen von komplexen Produktabhängigkeiten u. a. durch Visualisierung, auch über die klassischen Domänengrenzen hinweg, kommt eine zentrale Bedeutung, insbesondere während den frühen Konstruktionsphasen, zu. Im Rahmen dieser Arbeit wurde ein Prototyp entwickelt, mit dessen Hilfe Funktionsmodelle in virtuelle Umgebungen übertragen und interaktiv genutzt werden können. Dies fördert das interdisziplinäre Gesamtverständnis und unterstützt eine frühzeitige Qualitätskontrolle