"Visual analytics is an emerging field which uses visual techniques to interact with users in the analytical reasoning process. Users can choose the most appropriate representation that conveys the important content of their data by acting upon different visual displays. The data itself has many features of interest, including clusters, trends (commonalities) and anomalies. Most visualization techniques currently focus on the discovery of trends and other relations, where uncommon phenomena are treated as outliers and are either removed from the datasets or de-emphasized on the visual displays. Much less work has been done on the visual analysis of outliers, or anomalies. In this thesis, I will introduce a method to identify the different levels of “outlierness” by using interactive selection and other approaches to process outliers after detection. In one approach, the values of these outliers will be estimated from the values of their k-Nearest Neighbors and replaced to increase the consistency of the whole dataset. Other approaches will leave users with the choice of removing the outliers from the graphs or highlighting the unusual patterns on the graphs if points of interest lie in these anomalous regions. I will develop and test these anomaly handling methods within the XMDV Tool."

Large-scale genomics projects such as the Cancer Genome Atlas (TCGA), and the Encyclopedia of DNA Elements (ENCODE) involve generation of data at an unprecedented scale, requiring new computational techniques for analysis and interpretation. In the three studies I present in this thesis, I utilize these data sources to derive biological insights or created visualization tools that enable others to obtain insights more easily. First, I examine the distribution of the lengths for copy number variations (CNVs) in the cancer genome. This analysis shows that a small number of genes are altered at a greater frequency than expected from a power law distribution, suggesting that a large number of genomes must be sequenced for a given tumor type to a comprehensive discovery of somatic mutations. Second, I investigate germline CNVs in thousands of TCGA samples using single nucleotide polymorphism (SNP) array data to find variants that may confer increased susceptibility to cancer. This CNV-based genome-wide association study resulted in many germline CNVs that potentially increase risk in brain, breast, colorectal, renal, or ovarian cancers. Finally, I apply several visualization techniques to create tools for the TCGA and ENCODE projects in order to help investigators better process and synthesize meaning from large volume of data. Seqeyes combines linear and circular genomic views to explore predicted structural variations to help guide experimental validation. The modEncode browser visualizes chromatin organization by integrating data from a multitude of histone marks and chromosomal proteins. These results present visualization as a useful strategy for rapid identification of salient genomic features from large, heterogeneous genomic datasets.

Visualização é o processo genérico que utiliza representações visuais e interativas para facilitar a análise e o entendimento de informações de conjunto de dados. A maioria das ferramentas de visualização existentes atualmente utiliza exclusivamente recursos visuais para representar informações e isto tem limitado a capacidade exploratória e a apresentação de dados. Vários estudos têm demonstrado que o uso do som como recurso alternativo para representação de dados (sonificação) pode ser útil na interpretação de informações e também pode apoiar o aumento da dimensionalidade da apresentação visual. A sonificação é o objeto de estudo deste trabalho. Este trabalho implementa o novo módulo de sonificação de um sistema de exploração visual de dados, o Super Spider (Watanabe, 2007), que foi estendido com a implementação de recursos que auxiliam a exploração de dados por meio de sons. Um novo sistema, chamado Sonar 2D, também foi desenvolvimento de forma integrada ao Super Spider e apresenta uma nova técnica para sonificação de dados. Além disso, são apresentados resultados de testes com usuários aplicados para avaliar e validar os mapeamentos visuais e sonoros utilizados nos sistemas / Visualization is a generic process that uses visual and interactive representations to easy the analysis and the understanding of complex datasets. To this date, most of the visualization toolkits make use almost exclusively of visual aid to represent information, which has limited the capacity for data presentation and exploration. Many studies have shown that sound as an alternative data display tool (sonification) can be useful to support information interpretation and may also add dimensions to a visual display. Sonification is the object of study of this work. This work implements the new sonification module for a recently developed visual exploration system, the Super Spider (Watanabe, 2007). It has been extended with the implementation of functionalities in order to support data exploration through sounds. A new system, called Sonar 2D, was also developed and integrated to Super Spider, including a new technique of data sonification. In addition, this work presents results user evaluation for validation of some of the visual and sound mappings employed in both systems

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.

The focus of this study was to evaluate the psychological and psychosocial factors of a novel and composite meditation–visualization practice known as the best self visualization method (BSM). The researcher adapted and modified the BSM to work within a brief 2-week, two-session intervention period. The aim of the study was to evaluate the effects on psychopathology (GAD, PHQ), resilience (PHQ, GAD, Gratitude, Compassion, DSES, Trust, Personal Growth, Mindfulness, and Social Connection), and bio-physiological changes related to EEG spectral power, coherence, and heart rate variability (BPM-Coherence). A total of 66 participants were randomized into active meditation control (n = 35) and BSM (n = 31) intervention groups. Data analysis revealed significant effects for GAD in favor of BSM psychopathology attenuation (U = 316.5, z = -1.62, p ≤ .05) as well as for the PHQ (U = 321.5, z = -1.54, p = .06). Individual t tests revealed a much more robust effect. There were no significant differences for the other scales measured except for interpersonal trust, which had a stronger effect for the BSM group, t(23) = -1.90, p = .04. For EEG and HRV data, results showed the BSM elicited significant changes in parietal gamma spectral power (F[2, 15] = 6.34, p = .010), parietal alpha blocking (F[1, 15] = 5.14, p = .039), and heart rate coherence achievement (t[28] = 1.97, p = .03), as well as demonstrated a heart rate increase trend. Paradoxically, the BSM’s bio-physiological profile was more “activating” when compared to the control, indicating psychopathology attenuation was not related necessarily to a relaxation response.

We explore visualization and abstraction approaches to represent neuronal data. Neuroscientists acquire electron microscopy volumes to reconstruct a complete wiring diagram of the neurons in the brain, called the connectome. This will be crucial to understanding brains and their development. However, the resulting data is complex and large, posing a big challenge to existing visualization techniques in terms of clarity and scalability. We describe solutions to tackle the problems of scalability and cluttered presentation. We first show how a query-guided interactive approach to visual exploration can reduce the clutter and help neuroscientists explore their data dynamically. We use a knowledge-based query algebra that facilitates the interactive creation of queries. This allows neuroscientists to pose domain-specific questions related to their research. Simple queries can be combined to form complex queries to answer more sophisticated questions. We then show how visual abstractions from 3D to 2D can significantly reduce the visual clutter and add clarity to the visualization so that scientists can focus more on the analysis. We abstract the topology of 3D neurons into a multi-scale, relative distance-preserving subway map visualization that allows scientists to interactively explore the morphological and connectivity features of neuronal cells. We then focus on the process of acquisition, where neuroscientists segment electron microscopy images to reconstruct neurons. The segmentation process of such data is tedious, time-intensive, and usually performed using a diverse set of tools. We present a novel web-based visualization system for tracking the state, progress, and evolution of segmentation data in neuroscience. Our multi-user system seamlessly integrates a diverse set of tools. Our system provides support for the management, provenance, accountability, and auditing of large-scale segmentations. Finally, we present a novel architecture to render very large volumes interactively. We focus on two aspects: (1) Segmented objects are often toggled on and off by an interactive query, which makes it unfeasible to pre-compute a well-adapted space subdivision. (2) To scale to large data, culling and empty-space skipping must scale with the output size instead of the input volume. Our approach combines the advantages of object- and image-order stages of the empty-space skipping process.

Made available in DSpace on 2016-04-29T14:22:52Z (GMT). No. of bitstreams: 1 Guilherme Blaia DAvila.pdf: 1840808 bytes, checksum: 1c9061f1bf634734e2fb50f29b7ce8b6 (MD5) Previous issue date: 2011-05-12 / The goal of this research is the construction of an interface prototype for the visualization of changes in the territorial configuration, having as its starting point information from the Macro tool, whose author is Prof. Dr. Nelson Brissac Peixoto. A tool that enables the user to visualize and understand the relations among regional and global processes and their changes along time was created, turning large scale processes that were inaccessible to the individual experience into comprehensive information. To do so, it was made necessary the effort to synthesize the information contained on Macro, extracting its basic attributes and enabling its clustering and categorization. It was also necessary to create a versatile visual representation system that is capable of referencing each and every element of information. The prototype that was developed during this research can be used with different goals. It can be viable either for academic use or could be used by the government and companies. Its utilization as a tool could help the comprehension of the dynamics of territorial configuration, its cause and effect relations and connections between regional and global processes / Esta pesquisa tem como meta a construção de um protótipo de interface para a visualização de alterações na configuração territorial, tendo como ponto de partida informações contidas na ferramenta Macro, de autoria do Prof. Dr. Nelson Brissac Peixoto. Foi criada uma ferramenta que possibilita ao usuário visualizar e compreender relações entre processos regionais e globais e suas modificações ao longo do tempo, tornando apreensíveis processos em grande escala que são inacessíveis à experiência individual. Para tanto, tornou-se necessário sintetizar a informação inerente à ferramenta Macro, extraindo seus atributos básicos e possibilitando seu agrupamento e categorização, e também criar um sistema de representação visual abrangente e versátil que fosse capaz de referenciar todo e qualquer elemento de informação. O protótipo desenvolvido mostrou-se factível de introdução para diversos fins. Pode ser viável tanto para uso acadêmico como para o uso por instâncias governamentais e empresariais. Sua utilização como ferramenta pode auxiliar na compreensão das dinâmicas de configuração territorial, suas relações de causa e efeito, ligações entre processos regionais e locais

Words need a context to be understood. Visual patterns also need a context to convey their meaning. When patterns represent quantities in business graphics, decision makers (DMs) depend on contrasting visual contexts to discern patterns and discover relationships. Depending on the context in which DMs see trends, differences between two trends may point to a problem, to continuity, or to an opportunity. Can enhancing the context in computer graphics help DMs visualize problems? To answer this research question, three experiments were done in the field on computer graphics. One hundred five DMs tried 17 different contexts for time-series trends displayed on a microcomputer monitor. The research objective was to find out whether changing the context in graphics affected the decision efficiency (accuracy/response time) of DMs in determining relationships among trends. Essential for measuring the effect were interactive computer programs that displayed random trends in graphics of differing contexts, collected the DMs' answers to questions about the trends, and graded 1133 graphics based on the answers, response times, and trend data. The experimental results supported the hypothesis that computers can enhance the visual context surrounding time-series trends so that DMs can better visualize problems. Results were based on comparisons of DMs' decision efficiencies between trial graphics with differing contextual enhancements and based on answers to questions about the trial graphics. The results were tested with nonparametric statistics at the 0.05 significance level. Specific findings were: (1) Computer-supplied forecasts, as an enhancement, significantly helped DMs discover differences among trends. (2) Although not statistically significant, stratified presentation of trends and fading chartjunk tended to increase DMs' efficiencies. (3) Adding two colors, as an enhancement, made no difference in efficiency over black and white. (4) Paired trends in windows did not affect efficiency significantly. (5) Sequentially traced trends and composites of enhancements did not affect efficiency significantly. (6) DMs preferred stratified trends most and had the most confidence in graphics with fading context. They least liked and had the least confidence in black-and-white graphics.

Thesis (M.C.S.)--Miami University, Dept. of Computer Science and Systems Analysis, 2007. / Title from first page of PDF document. Includes bibliographical references (p. 86-88).

Project Management is the primary key to successful software development. In 1995 Caper Jones stated that the failure or cancellation rate of large software systems was over 20% in his article on patterns of large software systems. More than two thirds of the projects fail due to improper management of skills, activities, and personnel. One main reason is that software is not a tangible entity and is hard to visualize and hence to monitor. A manager has to be skilled in different CASE tools and technologies to track and manage a software development process successfully. The volume of results produced by these CASE tools is so huge that a high level manager cannot look into all the details. He has to get a high level picture of the project, to know where the project is heading, and if needed, then look into the finer level details by drilling down to locate and correct problems. The objective of this thesis is to build an Advanced Charting System (ACS), which would act as a companion to PAMPA 2 (Project Attribute Monitoring and Prediction Associate) and help a manager visualize the state of a software project over a standard World Wide Web browser. The PAMPA 2 ACS will be responsible for visualizing and tracking of resources, tasks, schedules and milestones of a software project described in the plan. PAMPA 2 ACS will have the ability to depict the status of the project through a variety of graphs and charts. PAMPA 2 ACS implements a novel charting technique called as DOT Chart to track the processes and activities of a software project. PAMPA 2 ACS provides a multilevel view of the project status. PAMPA 2 ACS will be able to track any arbitrary plan starting from a collapsed / concise view of a whole project. This can be further drilled down to the lowest level of detail. The status can be viewed at the project version level, plan and workbreakdown levels, process, sub process, and activity level. Among all the process models, the DOT charts can be applied effectively to spiral process model where each spiral represents a project version.