Thesis (M.S.)--University of Central Florida, 2009. / Adviser: Joseph J. LaViola Jr. Includes bibliographical references (p. 79-84).

Thesis (M.S.)--University of Missouri-Columbia, 2008. / The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on August 12, 2009) Includes bibliographical references.

Thesis (Ph. D.)--University of Hong Kong, 2006. / Title proper from title frame. Also available in printed format.

No description available.

A visualização computacional de informação é um campo em expansão por oferecer meios de se interpretar e analisar vários tipos de dados em grande quantidade e/ou de grande complexidade, compreendendo diversas técnicas e ferramentas para fornecer a um usuário formas de interagir e explorar conjuntos de dados a fim de se obter informações úteis ou importantes. A música, por sua vez, é um domínio complexo e de difícil estudo sob o ponto de vista computacional devido à análise de seu conteúdo possuir caráter muitas vezes subjetivo e dependente da interpretação humana. Embora vários trabalhos tenham sido publicados a respeito do assunto nos últimos anos, a maior parte das aplicações de visualização de informação relativas a música tende a analisar conjuntos de composições musicais a fim de agrupar ou classificar dados de acordo com algum tipo de critério. Assim, a visualização das informações contidas em uma única peça musical por si só é uma área que ainda pode ser melhor explorada, sobretudo visando compreender a informação musical envolvida o conteúdo extraído por um músico a partir de partituras e tablaturas. Esta dissertação relata o desenvolvimento de uma abordagem para visualização de dados musicais referentes a melodias em guitarra, com a capacidade de exibir elementos como variações de harmonia, melodia e tempo, tendo como objetivo auxiliar um músico (ou aprendiz de músico) na tarefa de interpretar tais dados. / Information visualization is an expanding research field due to its offering of novel approaches to analyze data of great size or complexity, referring to many techniques and tools in order to offer ways to interact and explore data sets to find important or useful information. Music is a domain of high complexity and hard to study and analyze by computer due to its sometimes subjective features, dependant of human interpretation. Although many research initiatives have been published regarding this subject recently, most of the music-related information visualization applications tend to analyze datasets composed by many different musical pieces, aiming to classify or group the data according to certain criteria. Thus, visualization of the information contained in a single musical piece is an area that still could be better explored, especially regarding to the comprehension of the musical information involved information extracted by a musician by reading musical scores. This document reports the development of a novel approach to musical data visualization based on electric guitar melodies, capable of showing elements such as harmony, melody and timing variations, aiming to aid a musician in the task of understanding such data.

Design form choices and information visualization outcomes remain inexhaustible, and they result from ongoing judgments about their appropriateness or effectiveness. Visualization design decision models have been widely proposed and applied. However, experts fail to explicitly study using design judgment to produce informed, professional decisions. In this dissertation, I bridge design form informational judgment gap when analyzing five studies with lab and in-situ designs individually as well as cross-case synthetically and comparably to examine the design judgments of all students working with visualization projects. The outcome stands to explain comprehensively how these student designers make judgments throughout their design process. Through analyzing several design cases, I identify the judgments enabling design moves forward and outcomes. The findings provide a robust description of designers’ design judgment activities and how the design judgment methods relate to design outcomes. These findings may also help identify gaps in information visualization education.<br>

No description available.

No description available.

Across domains, researchers, engineers, and designers are faced with large volumes of data that are heterogeneous in nature - including spatial, abstract, and temporal information. There are numerous design and technical challenges when considering the unification, management, and presentation of these information types. Most research and applications have focused on display techniques for each of the information types individually, but much less in known about how to represent the relationships between information types. This research explores the perceptual and usability impacts of data representations and layout algorithms for the next-generation of integrated information spaces. We propose Information-Rich Virtual Environments (IRVEs) as a solution to challenges of integrated information spaces. In this presentation, we will demonstrate the application requirements and foundational technology of IRVEs and articulate crucial tradeoffs in IRVE information design. We will present a design space and evaluation methodology to explore the usability effects of these tradeoffs. Experimental results will be presented for a series of empirical usability evaluations that increase our understanding of how these tradeoffs can be resolved to improve user performance. Finally, we interpret the results though the models of Information Theory and Human Information Processing to derive new conclusions regarding the role of perceptual cues in determining user performance in IRVEs. These lessons are posed as a set of design guidelines to aid developers of new IRVE interfaces and specifications. / Ph. D.

Information visualizations utilizing multiple coordinated views allow users to rapidly explore complex data spaces and discover complex relationships. Most multiple-view visualizations are static with regard to the views that they provide and the coordinations that they support. Despite significant progress in the field of Information Visualization and development of novel interaction techniques, user interfaces for exploring data have lacked flexibility. As a result, the vast quantities of information rapidly being collected in databases are underutilized and opportunities for advancement of knowledge are lost. This research proposes the central concept of visualization schemas based on the Snap-Together Visualization (Snap) model, analogous to the successful database concept of data schemas, which will enable dynamic specification of information visualizations for any given database without programming. Relational databases provide significant flexibility to organize, store, and manipulate an infinite variety of complex data collections. This flexibility is enabled by the concept of relational data schemas, which allow data owners to easily design custom databases according to their unique needs. We bring the same level of flexibility to visualization development through visualization schemas. Visualization Schemas is a conceptual model, user interface, and software architecture while Fusion is the implemented system that enable users to rapidly and dynamically construct personalized multi-view visualization workspaces by coordinating visualizations in ways unforeseen by the original developers. / Master of Science