No presente documento são reunidas as colaborações de inúmeros trabalhos das áreas de Bancos de Dados, Descoberta de Conhecimento em Bases de Dados, Mineração de Dados, e Visualização de Informações Auxiliada por Computador que, juntos, estruturam o tema de pesquisa e trabalho da dissertação de Mestrado: a Visualização de Informações. A teoria relevante é revista e relacionada para dar suporte às atividades conclusivas teóricas e práticas relatadas no trabalho. O referido trabalho, embasado pela substância teórica pesquisada, faz diversas contribuições à ciência em voga, a Visualização de Informações, apresentando-as através de propostas formalizadas no decorrer deste texto e através de resultados práticos na forma de softwares habilitados à exploração visual de informações. As idéias apresentadas se baseiam na exibição visual de análises numéricas estatísticas básicas, frequenciais (Frequency Plot), e de relevância (Relevance Plot). São relatadas também as contribuições à ferramenta FastMapDB do Grupo de Bases de Dados e Imagens do ICMC-USP em conjunto com os resultados de sua utilização. Ainda, é apresentado o Arcabouço, previsto no projeto original, para construção de ferramentas visuais de análise, sua arquitetura, características e utilização. Por fim, é descrito o Pipeline de visualização decorrente da junção entre o Arcabouço de visualização e a ferramenta FastMapDB. O trabalho se encerra com uma breve análise da ciência de Visualização de Informações com base na literatura estudada, sendo traçado um cenário do estado da arte desta disciplina com sugestões de futuros trabalhos. / In the present document are joined the collaborations of many works from the fields of Databases, Knowledge Discovery in Databases, Data Mining, and Computer-based Information Visualization, collaborations that, together, define the structure of the research theme and the work of the Masters Dissertation presented herein. This research topic is the Information Visualization discipline, and its relevant theory is reviewed and related to support the concluding activities, both theoretical and practical, reported in this work. The referred work, anchored by the theoretical substance that was studied, makes several contributions to the science in investigation, the Information Visualization, presenting them through formalized proposals described across this text, and through practical results in the form of software enabled to the visual exploration of information. The presented ideas are based on the visual exhibition of numeric analysis, named basic statistics, frequency analysis (Frequency Plot), and according to a relevance analysis (Relevance Plot). There are also reported the contributions to the FastMapDB tool, a visual exploration tool built by the Grupo de Bases de Dados e Imagens do ICMC-USP, the performed enhancements are listed as achieved results in the text. Also, it is presented the Framework, as previewed in this work's original proposal, projected to allow the construction of visual analysis tools; besides its description are listed its architecture, characteristics and utilization. At last, it is described the visualization Pipeline that emerges from the joining of the visualization Framework and the FastMapDB tool. The work ends with a brief analysis of the Information Visualization science based on the studied literature, it is delineated a scenario of the state of the art of this discipline along with suggestions for future work.

Submitted by PPG Ci?ncia da Computa??o (ppgcc@pucrs.br) on 2018-10-10T20:57:07Z No. of bitstreams: 1 EDUARDO GHIDINI_DIS.pdf: 8577965 bytes, checksum: 7ff48e36f96f7a9d7a545af88149f951 (MD5) / Approved for entry into archive by Sheila Dias (sheila.dias@pucrs.br) on 2018-10-17T11:12:35Z (GMT) No. of bitstreams: 1 EDUARDO GHIDINI_DIS.pdf: 8577965 bytes, checksum: 7ff48e36f96f7a9d7a545af88149f951 (MD5) / Made available in DSpace on 2018-10-17T11:21:19Z (GMT). No. of bitstreams: 1 EDUARDO GHIDINI_DIS.pdf: 8577965 bytes, checksum: 7ff48e36f96f7a9d7a545af88149f951 (MD5) Previous issue date: 2017-03-29 / The growth of data generated through the Internet increases the difficulty of gather relevant information for users. To minimize this, it is necessary to presented this information to the users in such a way that they can analyze it and extract useful information. In recent years, the use of narratives for the presentation of large volumes of data has been explored, considering its benefits. In this context, the present work aims to analyze and propose ways of presenting data, in narrative form, in the context of social networks, in order to support user interaction and data analysis. The work presents a model for the representation of narratives through visualizations, with data extracted from social networks, conceived from studies related to the areas of narratives and information visualization. The model was instantiated to enable its analysis through user studies. The studies indicated that the model has several applications, allowing the analysis of different types of data as well as its use by users with and without prior specific interests. We believe that the present work can support the construction of interactive narratives, through visualizations with data extracted from social networks, contemplating, not only the construction of the interface itself but, also, the mapping of the data to its visual representation. / O crescimento de dados gerados com o uso da Internet, faz com que, tamb?m, aumente a dificuldade de fazer com que informa??es relevantes cheguem aos usu?rios. Para que isso aconte?a, al?m do tratamento da informa??o, ? necess?rio que esta informa??o seja apresentada de tal forma que o usu?rio consiga analis?-la e extrair informa??es ?teis. Nos ?ltimos anos, vem se explorando o uso de narrativas para a apresenta??o de grandes volumes de dados, considerando-se os benef?cios desta forma de apresenta??o. Neste contexto, o presente trabalho objetiva analisar e propor formas de apresentar dados, em forma de narrativas, no contexto de redes sociais, a fim de apoiar a intera??o do usu?rio e sua an?lise dos dados. O trabalho apresenta um modelo para representa??o de narrativas por meio de visualiza??es, com dados extra?dos de redes sociais, concebido a partir de estudos relacionados ?s ?reas de narrativas e de visualiza??o de informa??es. O modelo foi instanciado para que viabilizasse a sua an?lise por meio de estudos com usu?rios. Os estudos indicam que o modelo tem variadas aplica??es, tanto no sentido de possibilitar a an?lise de diferentes tipos de dados, como, tamb?m, no que se refere ao uso por usu?rios com e sem interesse pr?vio em algum assunto espec?fico. Atrav?s do modelo proposto e do resultado de sua an?lise, acredita-se que o presente trabalho possa apoiar a constru??o de narrativas interativas neste contexto, contemplando, n?o somente a constru??o da interface em si, mas, tamb?m, o mapeamento dos dados para a sua representa??o visual.

As mídias sociais tiveram grande impacto no processo de inovação de jornais e revistas, porém adaptar-se em momentos de recessão ocasionou uma evolução apressada e procedimentos automatizados para mídias essencialmente diferentes. Apesar de haver estudos e soluções estado-da-arte em visualização para midias sociais dedicadas à análise do conteúdo e do comportamento de usuários, nenhum método é otimizado (e especializado) para encontrar padrões do ponto de vista de popularidade no contexto de canais de notícias. Nesta dissertação, discutimos duas diferentes propostas de utilização de combinações de técnicas de visualização que correlacionam as atividades de perfis e de sua comunidade de leitores com a popularidade resultante. Dados foram coletados reunindo postagens no Twitter, o número de seguidores dos perfis de interesse e os tópicos em tendência (trending topics) de canais da imprensa mundial para formar o conjunto de dados base para as propostas aqui apresentadas. Este conjunto de dados foi utilizado como semente para visualizações destinadas a possibilitar a comparação de múltiplas fontes, de forma que os usuários sejam habilitados a entender sua própria comunidade e também os sucessos e derrotas enfrentados pelos perfis competidores no mesmo meio. Essa análise foi validada através de entrevistas com um grupo de jornalistas de diferentes jornais estabelecidos. Através da interação com o sistema, é possível detectar padrões desconhecidos no grande volume de dados de mensagens e comentários de todo o mundo, possibilitando ao usuário uma visão única sobre os comportamentos e preferências de sua comunidade. / Social media has played a big part in the innovation process for newspapers and magazines, but adapting while going through a recession has led to a hasty evolution and automated processes for very different media. While existing social media studies and state-of-the-art visual solutions are available for analyzing social media content and users’ behaviors, no other method is optimized for finding patterns from a popularity standpoint in the specialized realm of news channels. In this dissertation, we discuss two different usages of a combination of different visualization techniques that co-relate profiles’ and their reading community activities with the resulting popularity. We gathered Twitter posts, the number of followers and trending topics from worldwide press profiles as the data set foundation for our proposal. We used this data set as the seed for our visualizations to allow for multiple source comparison, so that not only the user is able to understand their own community but also the success and pitfalls faced by the competition in the same medium. We validate our analysis by interviewing a group of journalists from different established newspapers. Through interacting with our system, it was possible to detect hidden patterns in the massive dataset of messages and comments worldwide, enabling the users to have unique insights into their community’s behaviors and preferences.

Este trabalho propõe um modelo hierárquico para coleta de dados de monitoramento em sistemas distribuídos. Seu objetivo é proporcionar a análise on-line do comportamento de sistemas e programas distribuídos. O meio escolhido para realizar essa análise foi a visualização. Inicialmente é apresentada uma contextualização sobre monitoramento de sistemas distribuídos. Também são abordados aspectos específicos ao monitoramento de Grid. Após, é analisado um conjunto de ferramentas de monitoramento. Então tem-se a apresentação do modelo proposto. Esse é composto por coletores locais, por uma hierarquia de agregadores e por clientes. É utilizado o modelo push de transmissão de dados e há um mecanismo de subscrição aos coletores. Foi implementado um protótipo do modelo de coleta proposto, que foi utilizado na implementação de um protótipo de ferramenta de monitoramento on-line. Nessa, os dados coletados são fornecidos ao DIMVisual, que é um modelo de integração de dados para visualização. Para visualização, o protótipo utiliza a ferramenta TRIVA, que recebe os dados integrados como entrada. Essa ferramenta foi modificada para gerar uma visualização que é atualizada de maneira on-line. Também foram realizados experimentos para avaliar o tempo necessário para enviar mensagens com diferentes hierarquias e configurações dos coletores. Além disso, foi avaliada a capacidade de o cliente implementado processar os dados recebidos, gerando sua visualização. / This work proposes a hierarchical model for collecting monitoring data from distributed systems. Its goal is to allow the on-line analysis of the behavior of distributed systems and applications. The means we chose to perform this analysis is to generate a visualization of the collected information. In the beginning of this dissertation we present an overview of the monitoring of distributed systems. Aspects that are specific to the monitoring of Grid systems are also reviewed. Next, we have an analysis of a set of monitoring tools. Then we present the proposed model, which is composed by local collectors, an hierarchical structure of aggregators and clients. A push data transmission model is used in the model and it also has a subscription mechanism. A prototype monitoring tool was implemented, integrating the data collection model with DIMVisual and TRIVA. The former is a data integration model whose output is formatted to be used as input for a visualization tool. The later is a visualization tool which, in the prototype, receives the integrated data from DIMVisual. TRIVA generates a visualization of the received information, which is updated in an on-line fashion. In order to evaluate the model, we performed a set of experiments using the prototype. One of the experiments measured the time spent to send data though different hierarchies. In these tests we have also varied the quantity and the configuration of the collectors. In another experiment we evaluated the capacity of the client to process the received data.

A análise de séries temporais gera muitos desafios para profisionais em um grande número de domínios. Várias soluções de visualização integrada com algoritmos de mineração já foram propostas para tarefas exploratórias em coleções de séries temporais. À medida que o conjunto de dados cresce, estas soluções falham em promover uma boa associação entre séries temporais similares. Neste trabalho, é apresentada uma ferramenta para a análise exploratória e mineração de conjuntos de séries temporais que adota uma representação visual baseada em medidas de dissimilaridade entre séries. Esta representação é criada usando técnicas rápidas de projeção, de forma que as séries temporais possam ser visualizadas em espaços bidimensionais. Vários tipos de atributos visuais e conexões no grafo resultante podem ser utilizados para suportar a exploração dessa representação. Também é possível aplicar algumas tarefas de mineração de dados, como a classificação, para apoiar a busca por padrões. As visualizações resultantes têm se mostrado muito úteis na identificação de grupos de séries com comportamentos similares, que são mapeadas para a mesma vizinhança no espaço bidimensional. Grupos visuais de elementos, assim como outliers, são facilmente identficáveis. A ferramenta é avaliada por meio de sua aplicação a vários conjuntos de séries. Um dos estudos de caso explora dados de vazões de usinas hidrelétricas no Brasil, uma aplicação estratégica para o planejamento energético. / Time series analysis poses many challenges to professionals in a wide range of domains. Several visualization solutions integrated with mining algorithms have been proposed for exploratory tasks on time series collections. As the data sets grow large, though, the visual alternatives do not allow for a good association between similar time series. In this work, we introduce a tool for exploratory visualization and mining of large time series data sets that adopts a visual representation based on distance measures between series. This representation is created employing fast projection techniques, so the time series can be viewed in two-dimensional spaces. Various types of visual attributes and connection on the resulting graph can be applied to support exploration. It also supports data mining tasks, such as classification, to search for patterns. The resulting visualizations have proved very useful for identifying groups of series with similar behavior, which are mapped to the close neighborhoods in twodimensional spaces. Visual clusters of elements, as well as outliers, are easily identifiable. Case studies on several domains are presented to validate the tool. One of them is on a data set of stream ows in hydroelectric power plants in Brazil, a strategic application for energy planning.

A necessidade de dispositivos analíticos para detecção precoce de câncer tem motivado pesquisas em nanomateriais de baixo custo, com busca de sinergia para obter alta sensibilidade e seletividade em biossensores. Neste trabalho, o ácido 11-mercaptoundecanóico, o polímero natural quitosana e a proteína concanavalina A (Con A) foram usados como plataforma para imobilizar anticorpos anti-CA 19-9 e construir biossensores para detecção de câncer de pâncreas. Esses biossensores foram produzidos com uma matriz de filmes automontados por adsorção química (self-assembled monolayers, SAM) e por adsorção física (layer-by-layer, LbL). A caracterização com técnicas espectroscópicas e gravimétricas permitiu selecionar as arquiteturas com quitosana/ Con A 2:1 (sensor A), quitosana/ Con A 1:1 (sensor B) e 11-MUA (sensor E), como sendo mais favoráveis à imobilização do anticorpo anti-CA 19-9. Usando os biossensores com espectroscopia de impedância foi possível detectar baixas concentrações do biomarcador CA 19-9, com limites de detecção entre 0,17-0,69 U/mL, 0,31-0,91 U/mL e 0,56-0,91 U/mL para os sensores A, B e E, respectivamente. Esses limites são suficientes para detectar câncer de pâncreas nos estágios iniciais. A seletividade dos dispositivos foi inferida em uma série de experimentos de controle com amostras de células SW 620 e HT-29, ácido úrico, ácido ascórbico, glicose, manose, sérum e antígeno p24, indicando ausência de interferência não específica ao biomarcador. O uso de técnicas de visualização de informação permitiu facilmente distinguir essas amostras, classificando-as de acordo com a concentração do biomarcador em um mapa. Permitiu também quantificar a seletividade dos biossensores através do coeficiente de silhueta, com valores 0,853, 0,861 e 0,897 para os sensores A, B e E, respectivamente. Essa especificidade dos biossensores foi confirmada por medidas de PM-IRRAS, através das bandas de amida I e II em 1566 cm-1 e 1650 cm-1, indicando a interação específica entre anticorpo e antígeno, que pode ser modelada com uma isoterma de Langmuir-Freundlich. Quando a matriz de quitosana/ Con A foi substituída por um filme monocamada ou quando se empregou um biomarcador de maior peso molecular, a adsorção do biomarcador foi explicada por uma combinação de dois processos de Langmuir-Freundlich. Conclui-se que os biossensores de baixo custo podem ser eficientes para diagnóstico e prognóstico, e serem implementados na rede nacional de saúde com disseminação da tecnologia. / The need of analytical devices to detect cancer at early stages has motivated research into nanomaterials where synergy is sought to achieve high sensitivity and selectivity in biosensors. In this work, 11-mercaptoundecanoic acid, the polymer chitosan and the protein concanavalin A (Con A) were used as a platform to immobilize the anti-CA 19-9 antibody using the self-assembled monolayer (SAM) and the layer-by-layer (LbL) techniques. The characterization with spectroscopic and gravimetric techniques allowed us to select the architectures with chitosan/Con A 2:1 (Sensor A), chitosan/Con A 1:1 (Sensor B) and 11 MUA (Sensor E) as optimized for immobilization of anti-CA 19-9 antibodies. Using impedance spectroscopy, the biosensors were capable of detecting low concentrations of CA 19-9 biomarker, with limit of detection in the range 0.17-0.69 U/mL, 0.31-0.91 U/mL and 0.56-0.91 U/mL for sensors A, B and E, respectively. These limits are sufficient to detect pancreatic cancer at early stages. The selectivity of the biosensors was inferred in a series of control experiments with cell samples SW-620 and HT-29, uric acid, ascorbic acid, glucose, mannose, serum and p24 antigen, indicating the absence of non-specific interference. With information visualization techniques, these samples could be easily distinguished in a visual map, and be classified according to their content of CA 19-9. Furthermore, the selectivity could be quantified through the silhouette coefficient, with values 0.853, 0.861 and 0.897 for sensors A, B and E, respectively. This biosensor specificity was confirmed with PM-IRRAS measurements by monitoring the amide I and II bands at 1566 cm-1 and 1650 cm-1. The specific interaction between antibody and antigen was modeled with a Langmuir-Freundlich isotherm. When the chitosan/Con A matrix was replaced by a SAM monolayer or if a larger biomarker was employed, adsorption was explained by a combination of two Langmuir-Freundlich processes. In conclusion, low cost biosensors may be effective for diagnostics and prognostics, and may be further implemented in the Brazilian national health system with technology transfer.

<p>This paper describes the design, implementation and evaluation of HyperSALmon, a Java™ open source prototype for visualizing service models in telecommunication networks. For efficient browsing and graphical monitoring of service models using SALmon, a service modeling language and a monitoring engine (Leijon et al., 2008), some kind of interactive GUI that implements a visualization of the service model is desired. This is what HyperSALmon is intended to do. The prototype has been designed in accordance with suggestions derived from a current research report of visualization techniques (Sehlstedt, 2008) appropriate for displaying service model data. In addition to these suggestions domain experts at Data Ductus Nord AB has expressed an urge for implementation of further features, some of their suggestions are deduced from research documents (Leijon et al., 2008; Wallin and Leijon, 2007, 2006), while others have been stated orally in direct relation to the prototype implementation work. The main visualization proposal is to use tree structures. Thus, both traditional tree structures and hyperbolic tree structures have been utilized, where the main navigation is set to occur in the hyperbolic tree view. In order to contribute further to this report I provide a discussion addressing problems related to the context of implementing a prototype for service model visualization using open source frameworks that meets the requirements set by the service model network architecture, the domain experts and the suggestions in the research report (Sehlstedt, 2008,page 51-52). Finally, I will present drawn conclusions of the attempted prototype implementation, illustrating potential strengths and weaknesses and consequently introduce suggestions for possible improvement and further development.</p>

<p>This thesis addresses some important characteristics of human visual perception and their implications for three-dimensional (3D) information visualization. The effort can be divided into two parts. First, findings from vision science are explored and validated. As a starting point, the compilation of perceptually motivated evidence about what constitutes an effective and efficient method for mapping of data is undertaken. Second, the knowledge obtained is used to create candidate visualizations and to demonstrate the predictive power of the findings.</p><p>Results indicate a general difficulty to convey metric, i.e. quantitative, information in 3D visualizations. Structure as defined by Euclidean geometry is not perceived with accuracy and information encoded by such distinctions are misunderstood or overlooked. On the other hand, qualitative properties as defined by affine geometry are salient are perceived with accuracy (paper I). These findings are also characteristic of two-dimensional (2D) visualizations when these need to be rapidly examined (paper II). </p><p>A novel method (3D surface glyphs) for abstract multivariate data sets was developed to investigate the possible merit of encoding information by qualitative distinctions, (paper III). Evaluations showed that the information conveyed was successfully utilized and that these types of glyph have great potential. The study also illustrated the predictive power of the earlier findings. These issues were further demonstrated when investigating how 3D perspective displays are unaffected by distortions in data when the patterns displayed were defined by affine properties (paper IV). In addition, a new metric for measuring the efficiency of visualizations is presented (paper III). </p><p>It is concluded that as long as visualizations are specified by qualitative properties, they could most probably be effectively and efficiently used. The need for user studies to determine if, when and how to choose a certain visualization technique for a given task is thereby significantly reduced.</p>

This thesis addresses some important characteristics of human visual perception and their implications for three-dimensional (3D) information visualization. The effort can be divided into two parts. First, findings from vision science are explored and validated. As a starting point, the compilation of perceptually motivated evidence about what constitutes an effective and efficient method for mapping of data is undertaken. Second, the knowledge obtained is used to create candidate visualizations and to demonstrate the predictive power of the findings. Results indicate a general difficulty to convey metric, i.e. quantitative, information in 3D visualizations. Structure as defined by Euclidean geometry is not perceived with accuracy and information encoded by such distinctions are misunderstood or overlooked. On the other hand, qualitative properties as defined by affine geometry are salient are perceived with accuracy (paper I). These findings are also characteristic of two-dimensional (2D) visualizations when these need to be rapidly examined (paper II). A novel method (3D surface glyphs) for abstract multivariate data sets was developed to investigate the possible merit of encoding information by qualitative distinctions, (paper III). Evaluations showed that the information conveyed was successfully utilized and that these types of glyph have great potential. The study also illustrated the predictive power of the earlier findings. These issues were further demonstrated when investigating how 3D perspective displays are unaffected by distortions in data when the patterns displayed were defined by affine properties (paper IV). In addition, a new metric for measuring the efficiency of visualizations is presented (paper III). It is concluded that as long as visualizations are specified by qualitative properties, they could most probably be effectively and efficiently used. The need for user studies to determine if, when and how to choose a certain visualization technique for a given task is thereby significantly reduced.

While linguistic skill is a hallmark of humanity, the increasing volume of linguistic data each of us faces is causing individual and societal problems — ‘information overload’ is a commonly discussed condition. Tasks such as finding the most appropriate information online, understanding the contents of a personal email repository, and translating documents from another language are now commonplace. These tasks need not cause stress and feelings of overload: the human intellectual capacity is not the problem. Rather, the computational interfaces to linguistic data are problematic — there exists a Linguistic Visualization Divide in the current state-of-the-art. Through five design studies, this dissertation combines sophisticated natural language processing algorithms with information visualization techniques grounded in evidence of human visuospatial capabilities. The first design study, Uncertainty Lattices, augments real-time computermediated communication, such as cross-language instant messaging chat and automatic speech recognition. By providing explicit indications of algorithmic confidence, the visualization enables informed decisions about the quality of computational outputs. Two design studies explore the space of content analysis. DocuBurst is an interactive visualization of document content, which spatially organizes words using an expert-created ontology. Broadening from single documents to document collections, Parallel Tag Clouds combine keyword extraction and coordinated visualizations to provide comparative overviews across subsets of a faceted text corpus. Finally, two studies address visualization for natural language processing research. The Bubble Sets visualization draws secondary set relations around arbitrary collections of items, such as a linguistic parse tree. From this design study we propose a theory of spatial rights to consider when assigning visual encodings to data. Expanding considerations of spatial rights, we present a formalism to organize the variety of approaches to coordinated and linked visualization, and introduce VisLink, a new method to relate and explore multiple 2d visualizations in 3d space. Intervisualization connections allow for cross-visualization queries and support high level comparison between visualizations. From the design studies we distill challenges common to visualizing language data, including maintaining legibility, supporting detailed reading, addressing data scale challenges, and managing problems arising from semantic ambiguity.