Com o aumento da expectativa de vida em quase todos os países do mundo, inclusive no Brasil, o número de pessoas idosas vem crescendo de forma considerável. Consequentemente, as doenças degenerativas comuns às pessoas com idades avançadas também tendem a aumentar correspondentemente, tornando doenças, como o Alzheimer, cada vez mais comuns. O cuidado a esses idosos é de extrema importância. Infelizmente, um dos problemas enfrentados pela sociedade, é que o número de cuidadores nesse contexto não segue um aumento proporcional, resultando então em cuidadores altamente sobrecarregados. Acredita-se que o uso de tecnologia para algumas tarefas dos cuidadores (e.g. registro do dia a dia), possa amenizar essa sobrecarga, mas, o que se tem visto é a carência de ferramentas tecnológicas que possam auxiliar nas atividades de cuidado ao paciente idoso. Apesar da importância de estudos nessa direção, poucas iniciativas de pesquisas abordam questões relacionadas às ferramentas tecnológicas para apoiar cuidadores de idosos, sem que essa os traga uma sobrecarga ainda maior. Uma das tarefas que pode ser feita com o auxílio da tecnologia é o registro de informações diárias do idoso, como por exemplo, alimentação, medicação e higiene. A partir das informações coletadas, é possível gerar visualizações que podem potencializar as análises feitas pelos médicos, e consequentemente, prover colaboração entre os cuidadores e os diferentes profissionais de saúde (e.g. psicólogos, nutricionistas, terapeutas ocupacionais, enfermeiros). Com o objetivo de entender melhor as reais necessidades dos cuidadores na coleta das informações do dia a dia, foram conduzidos alguns estudos que consistiam, basicamente, na realização de entrevistas e aplicação de questionários avaliativos. Diante dos resultados obtidos nesses estudos, foi desenvolvida uma ferramenta nomeada Day2Day que utiliza técnicas de visualização de informação e conceitos colaborativos como solução. A fim de avaliar se o Day2Day atingia os objetivos propostos, foi possível implantar a ferramenta em dois ambientes reais distintos, um lar para idosos e duas residências particulares. No total, sete profissionais de saúde fizeram uso da ferramenta por aproximadamente 25 dias, gerando informações diárias de oito idosos. Os resultados dessa avaliação indicam que o Day2Day atende em conformidade com as expectativas propostas, como por exemplo, a redução do tempo gasto para registro das informação. / Nowadays, the number of elderly people has grown considerably is almost every country in the world, including Brazil. Thus, many degenerative diseases that affect elderly people, such as the Alzheimer, also tend to increase and becomme more common. Taking care of elderly is extremelly important, however one of the problems faced by society is the fact that the number of caregivers does not follow this proportional increase, overloading most of the professionals. A possible solution may be the adoption of technology to help elderly caregivers in their tasks, such as recording day to day activities, and addressing these needs in a context where there is a lack of technological tools. Despite the importance of studies in this area, few research initiatives deal issues related to technological tools in order to support elderly caregivers, and in general they bring an even greater overhead in their tasks. One activity that can be done using technological tools is the record daily information of the elderly, such as feeding, medication and hygiene times. From the information collected, it is possible to generate useful views that can enhance the analysis made by doctors, and consequently provide more collaboration among caregivers and different health professionals (phycologists, nursers and so on). In order to better understand the real needs of caregivers in their day to day tasks, interviews and the application of evaluation questionnaires were conducted. Based on these results a so called Day2Day tool has been developed. It uses information from visualization techniques and collaborative concepts. In purpose of assess Day2Day has reached its goals, the tool was deployed in two real different environments: a home for elderly people and two private homes. A total of seven health professionals used the tool for 25 days, producing daily information of eight elderly. The results of this study have shown that the Day2Day tool meets in accordance with expectation proposals, such as reducing the time spent for recording information.

Séries temporais permeiam os mais variados domínios de aplicação, sendo a análise e a compreensão da dinâmica de séries temporais um problema interessante e bastante complexo. Técnicas de visualização têm sido aplicadas com sucesso nesse contexto, pois tiram proveito das habilidades perceptuais humanas ao transformar dados abstratos em informação visual. Nesta dissertação, foi proposta uma metodologia de análise visual para séries temporais multidimensionais. A finalidade dessa metodologia é a exploração e o entendimento do comportamento de material particulado presente na atmosfera de São CarlosSP, para melhor compreender a sinergia entre a qualidade do ar, o clima e as doenças respiratórias. As características do material particulado variam consideravelmente no decorrer do tempo, assumindo diferentes padrões, a depender das condições climáticas. Isso atesta a importância de ferramentas analíticas que sejam capazes de explorar as mudanças temporais dos dados. Duas ferramentas de visualização interativas foram desenvolvidas, utilizando principalmente a linguagem de programação JavaScript com a biblioteca D3. As ferramentas são portáveis em basicamente todos os navegadores web modernos, não exigindo a instalação de softwares específicos para que os usuários acessem-nas e façam as suas pesquisas. Os resultados obtidos a partir das análises dos dados amostrados demonstram que houve uma redução nos níveis de poluentes atmosféricos ao longo dos anos. A efetividade e a utilidade das tecnologias propostas são demonstradas em estudos de caso envolvendo dados reais, validados por especialistas do domínio de interesse. / Time series data are present in a wide variety of applications, and the explorations, analysis, and understanding of time series dynamics are interesting although it is a quite complex problems. Information visualization techniques have been successfully applied in this context taking advantage of human perceptual abilities when transforming abstract data into visual information. In this master dissertation, we present a new visual analytic methodology for multidimensional time series analysis. The aim of the proposed approach is to allow the exploration of the behavior of particulate matter present in the urban atmosphere of São CarlosSP, in order to understand the synergy between air quality, climate, and respiratory diseases. Moreover, the features related to particulate matter vary considerably over time, assuming different patterns according to the weather conditions. This dynamic shows the importance of analytical tools that enable the exploration of temporal changes of the data. We developed two interactive visualization tools, mainly in JavaScript programming language and D3 library. The tools are portable and can be used in all the modern web browsers, not requiring any software installation. The data analysis results show a decrease in atmospheric pollutant level over the years. The effectiveness and usefulness of the proposed technologies are demonstrated in case studies which involve real data and it is validated by domain experts.

<p>This thesis presents Pixgis; a novel application for map-centric management of photographs. In short Pixgis is an interactive environment in which photographs may be discovered, viewed and managed through maps. With Pixgis finding photographs from a specific location or of a particular structure is as easy as finding the location or structure on a map. As Pixgis simultaneously displays maps, photographs and spatial metadata it also enables users to analyze photographs in new manners. This thesis work illustrates the benefits of applications for map-centric management of photographs, exposes the problems one faces when implementing such applications and presents novel solutions to many of these problems. The thesis also elaborates on spatial metadata and methods for acquisition of photographs with embedded spatial metadata.</p>

<p>Three-dimensional (3D) interfaces are made with the ambition to reinvent traditional two-dimensional (2D) displays into intuitive 3D environments that allow natural interactions and guarantee users’ satisfaction. However, reality is far from the expectations and 3D interfaces remain experimental. The results of empirical studies comparing 2D and 3D interfaces are incoherent and do not indisputably endorse the development of 3D applications. The reason behind this incoherency is that empirical comparisons often discard several factors that go beyond the specific style of the interface itself although they play a major role in human performance. Specifically: perceptual factors, factors related to semantics, contextual factors.</p><p>The identification of these factors was carried out through a set of empirical studies tackling two applications domains: information management (namely, the retrieval of data and on spatial memory tasks) and Air Traffic Control. Concerning the first domain, the results suggest that 3D interfaces can support spatial memory if the 3D interface is provided with a spatial structure that has also a semantic function. Also, the specific content of the objects disseminated in the 3D structure seem to affect performance. It is argued that when there is a strategic coupling of the semantics of the spatial structure with the meanings of the objects, 3D interfaces could enhance spatial memory. Concerning the second domain, the results indicate that 3D interfaces could support controllers’ tasks only for a limited set of activities. These do not include standard monitoring tasks where the presence of 3D would actually cause detriment to the performance due to perceptual biases. Finally, it is claimed that the idea of familiarity with an interface style can affect the way people interact with it and, despite the fuzziness of the concept, familiarity may represent a real challenge in users’ acceptance of 3D interfaces. </p>

Three-dimensional (3D) interfaces are made with the ambition to reinvent traditional two-dimensional (2D) displays into intuitive 3D environments that allow natural interactions and guarantee users’ satisfaction. However, reality is far from the expectations and 3D interfaces remain experimental. The results of empirical studies comparing 2D and 3D interfaces are incoherent and do not indisputably endorse the development of 3D applications. The reason behind this incoherency is that empirical comparisons often discard several factors that go beyond the specific style of the interface itself although they play a major role in human performance. Specifically: perceptual factors, factors related to semantics, contextual factors. The identification of these factors was carried out through a set of empirical studies tackling two applications domains: information management (namely, the retrieval of data and on spatial memory tasks) and Air Traffic Control. Concerning the first domain, the results suggest that 3D interfaces can support spatial memory if the 3D interface is provided with a spatial structure that has also a semantic function. Also, the specific content of the objects disseminated in the 3D structure seem to affect performance. It is argued that when there is a strategic coupling of the semantics of the spatial structure with the meanings of the objects, 3D interfaces could enhance spatial memory. Concerning the second domain, the results indicate that 3D interfaces could support controllers’ tasks only for a limited set of activities. These do not include standard monitoring tasks where the presence of 3D would actually cause detriment to the performance due to perceptual biases. Finally, it is claimed that the idea of familiarity with an interface style can affect the way people interact with it and, despite the fuzziness of the concept, familiarity may represent a real challenge in users’ acceptance of 3D interfaces.

In many command and control situations the understanding of dynamic events is crucial. With today’s development of hard- and software architecture, we have the possibility to visualize data in two-dimensional (2D) and three-dimensional (3D) images. The aim of this thesis is therefore to investigate different approaches to visualizing dynamic events. The visualization techniques investigated include 2D animation and time representations as markings on a 2D map. In 3D the visualization technique investigated is the “space time-cube” A further aim is to study whether the Cue Probability Learning (CPL) paradigm can be used to evaluate visualizations. By mapping time onto a spatial dimension, in the 2D visualization as lines with different densities and in 3D as height over the map, a simultaneous visualization of space and time is possible. The findings are that this mapping of time onto space is beneficial to users as compared with animations, but the two mapping techniques are not interchangeable. If a task requires judgments of metric spatial properties, a 2D visualization is more beneficial; however, if the task only requires judgments of more qualitative aspects, a 3D visualization is more beneficial. When we look at a 3D visualization, we utilize different sources of depth information. These sources are always present and each defines either a 3D scene or a projection surface. By using these different sources of depth information wisely, a visualization can be created that efficiently shows relevant information to a user while requiring a minimal amount of specialized hardware. Finally, the CPL paradigm seems to be a worthwhile option as an experimental paradigm in visualization experiments. One of the advantages of CPL is that novice users can be trained to be task experts in a controlled and time-efficient way.

Managing projects in an organization, especially a project-oriented organization, is a challenging task. Project data has a large volume and is complex to manage. It is different from managing a single project, because one needs to integrate and synthesize information from multiple projects and multiple perspectives for high-level strategic business decisions, such as aligning projects with business objectives, balancing investment and expected return, and allocating resources. Current methods and tools either do not well integrate multiple aspects or are not intuitive and easy to use for managers and executives. In this dissertation project, a multidimensional and visual exploration approach was designed and evaluated to provide a unique and intuitive option to support decision making in project portfolio management. The research followed a general design science research methodology involving phases of awareness of problem, suggestion, development, evaluation and conclusion. The approach was implemented into a software system using a prototyping method and was evaluated through user interviews. The evaluation result demonstrates the utility and ease-of-use of the approach, and confirms design objectives. The research brings a new perspective and provides a new decision support tool for project portfolio management. It also contributes to the design knowledge of visual exploration systems for business portfolio management by theorizing the system.

This thesis presents Pixgis; a novel application for map-centric management of photographs. In short Pixgis is an interactive environment in which photographs may be discovered, viewed and managed through maps. With Pixgis finding photographs from a specific location or of a particular structure is as easy as finding the location or structure on a map. As Pixgis simultaneously displays maps, photographs and spatial metadata it also enables users to analyze photographs in new manners. This thesis work illustrates the benefits of applications for map-centric management of photographs, exposes the problems one faces when implementing such applications and presents novel solutions to many of these problems. The thesis also elaborates on spatial metadata and methods for acquisition of photographs with embedded spatial metadata.

The sheer quantity of information available on the Internet poses a challenge to users who need an efficient way of finding the information most relevant to their needs. One of the most frequent information-seeking activities of Internet users is the search for health and medical information. In this research, I focus on the user process of seeking information on clinical trials which are the only evidence-based source of information in the medical domain. Through my work, I show that improvements for seeking clinical-trial information could be made to enhance the effectiveness of seeking and gathering results from clinical trials. Unfortunately, little work has been reported on alternative methods and on visualization systems in particular for these enhancements. I suggest that this omission may be due to a lack of understanding of the particular information needs of users of clinical-trial data. Understanding the users' needs is the first step towards providing more effective interfaces to support them in the information seeking process. In this dissertation, I investigate 1) how information is accessed in the medical domain; more specifically, how users seek clinical-trial information on the Internet and 2) how to improve current Web-seeking interfaces for clinical-trial users. I discuss my findings from three exploratory studies: moderated discussion with professional researchers of clinical trials, an online questionnaire with health professionals and patients who search the clinical trial domain, and a qualitative query log analysis of a popular medical search engine. The results of this research indicate that most of the time users are successful in finding the information they require. However, the process of seeking clinical-trial information is tedious, frustrating and time consuming, because current search interfaces do not sufficiently support users seeking this kind of information. Based on the findings from my studies, I propose a set of design principles to design better seeking interfaces. I validate my findings and the set of design principles with two visualization tools that support users in performing information-seeking tasks in the clinical-trial domain. Finally, I provide initial evidence that my proposed designs are indeed helpful with finding, summarizing and comparing information in this complex medical domain.

In this dissertation we have addressed the problem of modeling expertise in domains characterized by unquantifiable, often subjective, information, and using that model of expertise as the foundation for building computer-based decision support systems. The key feature of the expert model is to make explicit the essential characteristics of the knowledge experts use to process objective, quantitative information, for making decisions in environments rich in qualitative data. This model is then used as the basis for an "intelligent" interactive assistant that presents information appropriate for the context to operators who may not have developed the necessary expertise. The core of the assistant is a heuristic algorithm that reflects what an expert decision maker would actually do. The algorithm incorporates a set of production rules, i.e., if-then-else rules, to define relevance conditions of quantitative data. These rules employ a dominance principle, i.e., a heuristic association of the relevance of quantitative data with the attributes of qualitative data, characterized as a set of ordered values. The heuristic algorithm is embedded in the assistant and is used to assist non-expert operators in locating information useful for making decisions. The modeling methodology and the heuristic algorithm are applicable for modeling expertise in a class of decision problems characterized by large amounts of qualitative and quantitative data. The process of structuring the expert's knowledge requires empirical evidence from actual decision problems; this evidence feeds the algorithm with heuristic associations between qualitative and quantitative data. The algorithm uses the dominance principle to decide what information to present for a particular set of conditions.