Rapid growing volumes of data demands new solutions in terms of analysing and visualizing. The growing amount of data contains valuable information which organizations in a more digitized society need to manage. It is a major challenge to visualize data, both in a static and interactive way. Through visualization of big data follows several opportunities containing risk assessment and decision basis. Previous research indicates a lack of standards and guidelines considering the development of interactive dashboards. By studying factors of success from a user-centered perspective we proceeded with a qualitative approach using semi-structured interviews. In addition to this we performed a thorough examination of existing literature in this particular field of research. A total of eight interviews were held, all eight respondents had experience from using or developing dashboards. The results indicates that user experience is an important yet not a sufficiently used principle. They also indicates challenges concerning the management of big data and particularly visualizing it. The results developed into a model which illustrates guidelines and vital components to orchestrate when developing a dashboard. A user-centered approach should pervade the entire developing process. Interactive functionalities are rather a necessity than a recommendation. With interactiveness comes drill-down functionalities which leads to a more intuitively practice. User experience is an essential component of the model, bringing light to individual customisations as well as it makes allowances to a large target group. The last component highlights the importance of early prototyping and an iterative approach to software development. The conclusion of the study is our complete model which brings opportunities to transform big data to great knowledge.

The current proliferation of connected displays and mobile devices from smart phones and tablets to wall-sized displays presents a number of exciting opportunities for information visualization and visual analytics. When a user employs heterogeneous displays collaboratively to achieve a goal, they form what is known as a display ecology. The display ecology enables multiple displays to function in concert within a broader technological environment to accomplish tasks and goals. However, since information and tasks are scattered and disconnected among separate displays, one of the inherent challenges associated with visual analysis in display ecologies is enabling users to seamlessly coordinate and subsequently connect and integrate information across displays. This research primarily addresses these challenges through the creation of interaction and visualization techniques and systems for display ecologies in order to support sensemaking with visual analysis. This dissertation explores essential visual analysis activities and design considerations for visual analysis in order to inform the new design of display ecologies for visual analysis. Based on identified design considerations, we then designed and developed two visual analysis systems. First, VisPorter supports intuitive gesture interactions for sharing and integrating information in a display ecology. Second, the Spatially Aware Visual Links (SAViL) presents a cross-display visual link technique capable of guiding the user's attention to relevant information across displays. It also enables the user to visually connect related information over displays in order to facilitate synthesizing information scattered over separate displays and devices. The various aspects associated with the techniques described herein help users to transform and empower the multiple displays in a display ecology for enhanced visual analysis and sensemaking. / Ph. D.

Since the completion of the Human Genome Project in 2003, biologists have become exceptionally good at producing data. Indeed, biological data has experienced a sustained exponential growth rate, putting effective and thorough analysis beyond the reach of many biologists. This thesis presents BioBridge, an interactive visualization tool developed to bring intuitive data exploration to biologists. BioBridge is designed to work on omics style tabular data in general and thus has broad applicability. This work describes the design and evaluation of BioBridge's Entity View primary visualization as well the accompanying user interface. The Entity View visualization arranges glyphs representing biological entities (e.g. genes, proteins, metabolites) along with related text mining results to provide biological context. Throughout development the goal has been to maximize accessibility and usability for biologists who are not computationally inclined. Evaluations were done with three informal case studies, one of a metabolome dataset and two of microarray datasets. BioBridge is a proof of concept that there is an underexploited niche in the data analysis ecosystem for tools that prioritize accessibility and usability. The use case studies, while anecdotal, are very encouraging. These studies indicate that BioBridge is well suited for the task of data exploration. With further development, BioBridge could become more flexible and usable as additional use case datasets are explored and more feedback is gathered.

Due to the impressive capabilities of human visual processing, interactive visualization methods have become essential tools for scientists to explore and analyze large, complex datasets. However, traditional approaches do not account for the increased size or latency of data retrieval when interacting with these often remote datasets. In this dissertation, I discuss two novel design paradigms, based on accepted models of the information visualization process and graphics hardware pipeline, that are appropriate for interactive visualization of large remote datasets. In particular, I discuss novel solutions aimed at improving the performance of interactive visualization systems when working with large numeric datasets and large terrain (elevation and imagery) datasets by using data reduction and asynchronous retrieval of view-prioritized data, respectively. First I present a modified version of the standard information visualization model that accounts for the challenges presented by interacting with large, remote datasets. I also provide the details of a software framework implemented using this model and discuss several different visualization applications developed within this framework. Next I present a novel technique for leveraging the hardware graphics pipeline to provide asynchronous, view-prioritized data retrieval to support interactive visualization of remote terrain data. I provide the results of statistical analysis of performance metrics to demonstrate the effectiveness of this approach. Finally I present the details of two novel visualization techniques, and the results of evaluating these systems using controlled user studies and expert evaluation. The results of these qualitative and quantitative evaluation mechanisms demonstrate improved visual analysis task performance for large numeric datasets.

A software Bug report contains information about the bug in the form of problem description and comments using natural language texts. Managing reported bugs is a significant challenge for a project manager when the number of bugs for a software project is large. Prior to the assignment of a newly reported bug to an appropriate developer, the triager (e.g., manager) attempts to categorize it into existing categories and looks for duplicate bugs. The goal is to reuse existing knowledge to fix or resolve the new bug, and she often spends a lot of time in reading a number of bug reports. When fixing or resolving a bug, a developer also consults with a series of relevant bug reports from the repository in order to maximize the knowledge required for the fixation. It is also preferable that developers new to a project first familiarize themselves with the project along with the reported bugs before actually working on the project. Because of the sheer numbers and size of the bug reports, manually analyzing a collection of bug reports is time-consuming and ineffective. One of the ways to mitigate the problem is to analyze summaries of the bug reports instead of analyzing full bug reports, and there have been a number of summarization techniques proposed in the literature. Most of these techniques generate extractive summaries of bug reports. However, it is not clear how useful those generated extractive summaries are, in particular when the developers do not have prior knowledge of the bug reports. In order to better understand the usefulness of the bug report summaries, in this thesis, we first reimplement a state of the art unsupervised summarization technique and evaluate it with a user study with nine participants. Although in our study, 70% of the time participants marked our developed summaries as a reliable means of comprehending the software bugs, the study also reports a practical problem with extractive summaries. An extractive summary is often created by choosing a certain number of statements from the bug report. The statements are extracted out of their contexts, and thus often lose their consistency, which makes it hard for a manager or a developer to comprehend the reported bug from the extractive summary. Based on the findings from the user study and in order to further assist the managers as well as the developers, we thus propose an interactive visualization for the bug reports that visualizes not only the extractive summaries but also the topic evolution of the bug reports. Topic evolution refers to the evolution of technical topics discussed in the bug reports of a software system over a certain time period. Our visualization technique interactively visualizes such information which can help in different project management activities. Our proposed visualization also highlights the summary statements within their contexts in the original report for easier comprehension of the reported bug. In order to validate the applicability of our proposed visualization technique, we implement the technique as a standalone tool, and conduct both a case study with 3914 bug reports and a user study with six participants. The experiments in the case study show that our topic analysis can reveal useful keywords or other insightful information about the bug reports for aiding the managers or triagers in different management activities. The findings from the user study also show that our proposed visualization technique is highly promising for easier comprehension of the bug reports.

Os rankings musicais destinam-se principalmente a fins de marketing, mas também ajudam os usuários a descobrir novas músicas, bem como a comparar artistas, álbuns, etc. Este trabalho apresenta uma ferramenta interativa para visualizar, encontrar e comparar rankings musicais usando diferentes técnicas além de exibir atributos das músicas. A técnica foi concebida após uma pesquisa remota que coletou dados sobre como as pessoas escolhem música. As técnicas de visualização tornam mais fácil obter informações sobre artistas e faixas, e também comparar os dados obtidos a partir dos dois principais rankings de música, Billboard e Spotify. A ferrament também permite a interação com dados pessoais. Resultados de experimentos conduzidos com usuários potenciais mostraram que a ferramenta foi considerada interessante, com um layout atrativo. Comparando com as formas tradicionais de visualizar rankings de músicas, usuários preferiram a ferramenta aqui desenvolvida, mas a diferença para Billboard e Spotify não foi grande. Entretanto, quando avaliada a usabilidade da ferramenta, os resultados foram melhores, principalmente no que se refere à filtragem e às técnicas de comparação. MusicVis foi também considerado fácil de aprender. / Music rankings are mainly aimed at marketing purposes but also help users in discovering new music as well as comparing songs, artists, albums, etc. This work presents an interactive way to visualize, find and compare music rankings using different techniques, including the display of music attributes. The technique was conceived after a remote survey we conducted to collect data about how people choose music. Our visualization makes easier to obtain information about artists and tracks, and also to compare the data gathered from the two major music rankings, namely Billboard and Spotify. The tool also provides interaction with personal data. The results obtained from experiments with potential users showed that the tool was considered interesting, with an attractive layout. Compared to traditional music ranking tools users preferred ours, but with not such a large difference from using Billboard or Spotify. However, when evaluating the usability of our tool, results are positive, mainly concerning to data filtering and comparison features. MusicVis was also considered easy to learn.

Técnicas de visualização volumétrica direta são utilizadas para visualizar e explorar volumes de dados complexos. Dados volumétricos provêm de diversas fontes, tais como dispositivos de diagnóstico médico, radares de sensoriamento remoto ou ainda simulações científicas assistidas por computador. Um problema fundamental na visualização volumétrica é a especificação de Funções de Transferência (FTs) que atribuem cor e opacidade aos valores escalares que compõem o volume de dados. Essas funções são importantes para a exibição de características e objetos de interesse do volume, porém sua definição não é trivial ou intuitiva. Abordagens tradicionais permitem a edição manual de pontos de controle que representam a FT a ser utilizada no volume. No entanto, essas técnicas acabam conduzindo o usuário a um processo de “tentativa e erro” para serem obtidos os resultados desejados. Considera-se também que técnicas automáticas que excluem o usuário do processo não são consideradas as mais adequadas, visto que o mesmo deve possuir algum controle sobre o processo de visualização. Este trabalho apresenta uma ferramenta semi-automática e interativa destinada a auxiliar o usuário na geração de FTs de cor e opacidade. A ferramenta proposta possui dois níveis de interação com o usuário. No primeiro nível são apresentados várias FTs candidatas renderizadas como thumbnails 3D, seguindo o método conhecido como Design Galleries (MARKS et al., 1997). São aplicadas técnicas para reduzir o escopo das funções candidatas para um conjunto mais razoável, sendo possível ainda um refinamento das mesmas. No segundo nível é possível definir cores para a FT de opacidade escolhida, e ainda refinar essa função de modo a melhorála de acordo com as necessidades do usuário. Dessa forma, um dos objetivos desse trabalho é permitir ao usuário lidar com diferentes aspectos da especificação de FTs, que normalmente são dependentes da aplicação em questão e do volume de dados sendo visualizado. Para o rendering do volume, são exploradas as capacidades de mapeamento de textura e os recursos do hardware gráfico programável provenientes das plácas gráficas atuais visando a interação em tempo real. Os resultados obtidos utilizam volumes de dados médicos e sintéticos, além de volumes conhecidos, para a análise da ferramenta proposta. No entanto, é dada ênfase na especificação de FTs de propósito geral, sem a necessidade do usuário prover um mapeamento direto representando a função desejada. / Direct volume rendering techniques are used to visualize and explore large scalar volumes. Volume data can be acquired from many sources including medical diagnoses scanners, remote sensing radars or even computer-aided scientific simulations. A key issue in volume rendering is the specification of Transfer Functions (TFs) which assign color and opacity to the scalar values which comprise the volume. These functions are important to the exhibition of features and objects of interest from the volume, but their specification is not trivial or intuitive. Traditional approaches allow the manual editing of a graphic plot with control points representing the TF being applied to the volume. However, these techniques lead the user to an unintuitive trial and error task, which is time-consuming. It is also considered that automatic methods that exclude the user from the process should be avoided, since the user must have some control of the visualization process. This work presents a semi-automatic and interactive tool to assist the user in the specification of color and opacity TFs. The proposed tool has two levels of user interaction. The first level presents to the user several candidate TFs rendered as 3D thumbnails, following the method known as Design Galleries (MARKS et al., 1997). Techniques are applied to reduce the scope of the candidate functions to a more reasonable one. It is also possible to further refine these functions at this level. In the second level is permitted to define and edit colors in the chosen TF, and refine this function if desired. One of the objectives of this work is to allow users to deal with different aspects of TF specification, which is generally dependent of the application or the dataset being visualized. To render the volume, the programmability of the current generation of graphics hardware is explored, as well as the features of texture mapping in order to achieve real time interaction. The tool is applied to medical and synthetic datasets, but the main objective is to propose a general-purpose tool to specify TFs without the need for an explicit mapping from the user.

generated large databases containing information on the concentrations of chemical elements in rocks, surface sediments and biogeochemical materials. Regional geochemical data being imprecise, multivariate, spatially auto-correlated and non-normally distributed pose specific problems to the choice of data analysis methods. Commonly several methods are combined, and the choice of techniques depends on the characteristics of data as well as the purpose of study. One critical issue is dealing with extreme data values (or outliers) in the initial stages of analysis. Another common problem is that integrated analysis of several geochemical datasets is not possible without interpolating the point data into surfaces. Finally, separation of anthropogenic influences from natural geochemical background in the surface materials is an issue of great importance for environmental studies. This study describes an approach to address the above-mentioned problems by a flexible combination and use of GIS and multivariate statistical techniques with high-dimensional visualization. Dynamically linked parallel coordinate and scatterplot matrix display techniques allow simultaneous presentation of spatial, multi-element and qualitative information components of geochemical data. The plots not only display data in multi-dimensional space, but also allow detailed inspection of the data with interactive multi-dimensional brushing tools. The results of the study indicate that these simple high-dimensional visualization techniques can successfully complement the traditional statistical and GIS analysis in all steps of data processing, from data description and outlier identification through data integration, analysis, validation, and presentation of results. The outcomes of the study include: a visual procedure towards intelligent data cleaning where potentially significant information in very high element concentrations is preserved, methods for integration and visual analysis of geochemical datasets collected in different grids, estimation of geochemical baseline concentrations of trace metals in till geochemistry of southeastern Sweden, use of multi-element spatial fingerprints to trace natural geochemical patterns in biogeochemistry, and a new graphical approach to present multi-element geochemical data summaries and results from numerical analysis. / QC 20100609

Šio darbo tikslas yra suprojektuoti ir realizuoti vizualizacijos sistemą, naudojančią trimačius elementus ir atlikti tyrimą, ar tokia vizualizacijos sistemos koncepcija padeda spręsti tam tikras operatorių problemas. Darbo metu siekiama išsiaiškinti, ar trimačiai elementai gali būti naudingesni nei dvimačiai jų analogai. Vizualizacijos sistemai realizuoti panaudotas Microsoft DirectX trimatės grafikos kūrimo priemonių rinkinys. Sukurtas realiai veikiančios dvimatės vizualizacijos sistemos trimatis analogas, apimantis tam tikrą realios sistemos dalį. Atliktas tyrimas, kurio tikslas – išsiaiškinti, ar sukurta sistema turi pranašumą prieš savo pirmtką identifikuojant ir lokalizuojant sistemoje įvykusiems įvykiams. / The goal of this work is to develop vizualization system which uses 3D elements. Also to perform research with goal to analyze if such visualization system helps to solve particular problems for operators. During this work will be trying to answer the question if 3D elements can be more helpful than 2D elements. Microsoft DirectX SDK is used to create visualization system. Only a specific part of running 2D visualization system is created. Research is performed to identify if created system can be more helpful in identifying and localizing system events.

A análise de redes sociais através de ferramentas visuais permite ao usuário extrair informações importantes sobre os indivíduos e seus relacionamentos. Através dela é possível entender de que forma os grupos se organizam. Para o caso de redes de coautoria, algumas conclusões como qual o pesquisador com maior prestígio na rede ou qual pesquisador tem o perfil mais parecido com o seu podem ser obtidas. Uma grande quantidade de ferramentas têm sido desenvolvidas para visualização de redes sociais. Algumas delas permitem que análises sejam feitas sobre os dados que compõem as redes, porém a maioria não mostra os resultados dessas análises sobre o próprio grafo, em geral apresentando-as como informações textuais. Neste trabalho, inicialmente, foi feito um estudo comparativo de diversas ferramentas visuais que além de mostrar redes sociais de forma gráfica, fazem algum tipo de análise sobre a rede. O estudo subsidiou o desenvolvimento de Pandora, uma ferramenta que permite visualização incremental de redes acadêmicas além de interação com o grafo e cálculo de algumas métricas, como centralidades, assortatividade e coeficiente de colaboração. / The analysis of social networks through visual tools allows to extract important information about each individual and their relationships. Through it we can understand how groups are organized. For the case of co-authorship networks, some conclusions about which researcher has greater prestige in the network or where the researcher has profile more like his can be obtained. A lot of tools have been developed for visualizing social networks. Some of them allow analyzes are made about the data that make up the networks, but most do not show the results of these analyzes on the graph itself, usually presenting them as textual information. This work was initially done a comparative study of various visual tools that show beyond social networks graphically. This tools generally do some kind of analysis on the network. In this work Pandora was developed, a visualization tool that allows incremental academic networks and interaction with the graph and calculate some metrics, such as centralities, assortativity and collaboration coefficient.