Doctor of Philosophy

dissertationVisualization has emerged as an effective means to quickly obtain insight from raw data. While simple computer programs can generate simple visualizations, and while there has been constant progress in sophisticated algorithms and techniques for generating insightful pictorial descriptions of complex data, the process of building visualizations remains a major bottleneck in data exploration. In this thesis, we present the main design and implementation aspects of VisTrails, a system designed around the idea of transparently capturing the exploration process that leads to a particular visualization. In particular, VisTrails explores the idea of provenance management in visualization systems: keeping extensive metadata about how the visualizations were created and how they relate to one another. This thesis presents the provenance data model in VisTrails, which can be easily adopted by existing visualization systems and libraries. This lightweight model entirely captures the exploration process of the user, and it can be seen as an electronic analogue of the scientific notebook. The provenance metadata collected during the creation of pipelines can be reused to suggest similar content in related visualizations and guide semi-automated changes. This thesis presents the idea of building visualizations by analogy in a system that allows users to change many visualizations at once, without requiring them to interact with the visualization specifications. It then proposes techniques to help users construct pipelines by consensus, automatically suggesting completions based on a database of previously created pipelines. By presenting these predictions in a carefully designed interface, users can create visualizations and other data products more efficiently because they can augment their normal work patterns with the suggested completions. VisTrails leverages the workflow specifications to identify and avoid redundant operations. This optimization is especially useful while exploring multiple visualizations. When variations of the same pipeline need to be executed, substantial speedups can be obtained by caching the results of overlapping subsequences of the pipelines. We present the design decisions behind the execution engine, and how it easily supports the execution of arbitrary third-party modules. These specifications also facilitate the reproduction of previous results. We will present a description of an infrastructure that makes the workflows a complete description of the computational processes, including information necessary to identify and install necessary system libraries. In an environment where effective visualization and data analysis tasks combine many different software packages, this infrastructure can mean the difference between being able to replicate published results and getting lost in a sea of software dependencies and missing libraries. The thesis concludes with a discussion of the system architecture, design decisions and learned lessons in VisTrails. This discussion is meant to clarify the issues present in creating a system based around a provenance tracking engine, and should help implementors decide how to best incorporate these notions into their own systems

An ontological approach to information visualization.

Visualization is one of the indispensable means for addressing the rapid explosion of data and information. Although a large collection of visualization techniques have been developed over the past three decades, the majority of ordinary users have little knowledge about these techniques. Despite there being many interactive visualization tools available in the public domain or commercially, producing visualizations remains a skilled and time-consuming task. One approach for cost-effective dissemination of visualization techniques is to use captured expert knowledge for helping ordinary users generate visualizations automatically. In this work, we propose to use captured knowledge in ontologies to reduce the parameter space, providing a more effective automated solution to the dissemination of visualization techniques to ordinary users. As an example, we consider the visualization of music chart data and football statistics on the web, and aim to generate visualizations automatically from the data. The work has three main contributions: Visualisation as Mapping. We consider the visualization process as a mapping task and assess this approach from both a tree-based and graph-based perspective. We discuss techniques for automatic mapping and present a general approach for Information Perceptualisation through mapping which we call Information Realisation. VizThis: Tree-centric Mapping. We have built a tree-based mapping toolkit which provides a pragmatic solution for visualising any XML-based source data using either SVG or X3D (or potentially any other XML-based target format). The toolkit has data cleansing and data analysis features. It also allows automatic mapping through a type-constrained system (AutoMap). If the user wishes to alter mappings, the system gives the users warnings about specific problem areas so that they can be immediately corrected. SeniViz: Graph-centric Mapping. We present an ontology-based pipeline to automatically map tabular data to geometrical data, and to select appropriate visualization tools, styles and parameters. The pipeline is based on three ontologies: a Domain Ontology (DO) captures the knowledge about the subject domain being visualized; a Visual Representation Ontology (VRO) captures the specific representational capabilities of different visualization techniques (e.g.. Tree Map); and a Semantic Bridge Ontology (SBO) captures specific expert-knowledge about valuable mappings between domain and representation concepts. In this way, we have an ontology mapping algorithm which can dynamically score and rank potential visualizations. We also present the results of a user study to assess the validity and effectiveness of the SemViz approach

GSFC Heliophysics Science Division FY2010 Annual Report

This report is intended to record and communicate to our colleagues, stakeholders, and the public at large about heliophysics scientific and flight program achievements and milestones for 2010, for which NASA Goddard Space Flight Center's Heliophysics Science Division (HSD) made important contributions. HSD comprises approximately 323 scientists, technologists, and administrative personnel dedicated to the goal of advancing our knowledge and understanding of the Sun and the wide variety of domains that its variability influences. Our activities include: Leading science investigations involving flight hardware, theory, and data analysis and modeling that will answer the strategic questions posed in the Heliophysics Roadmap; Leading the development of new solar and space physics mission concepts and support their implementation as Project Scientists; Providing access to measurements from the Heliophysics Great Observatory through our Science Information Systems; and Communicating science results to the public and inspiring the next generation of scientists and explorers

Iowa State University, Courses and Programs Catalog 2014–2015

The Iowa State University Catalog is a one-year publication which lists all academic policies, and procedures. The catalog also includes the following: information for fees; curriculum requirements; first-year courses of study for over 100 undergraduate majors; course descriptions for nearly 5000 undergraduate and graduate courses; and a listing of faculty members at Iowa State University.https://lib.dr.iastate.edu/catalog/1025/thumbnail.jp