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Submitted by Maike Costa (maiksebas@gmail.com) on 2017-02-22T12:01:33Z No. of bitstreams: 1 arquvo total.pdf: 18917608 bytes, checksum: fcfcd686ecacb39c53f8f45267048264 (MD5) / Made available in DSpace on 2017-02-22T12:01:33Z (GMT). No. of bitstreams: 1 arquvo total.pdf: 18917608 bytes, checksum: fcfcd686ecacb39c53f8f45267048264 (MD5) Previous issue date: 2016-11-10 / This study deals with an innovative theme regarding the scenario of contemporary science. This perspective presents a new spectrum related to open science and changes that occur in current scientific practices. These practices are being improved and present new meanings, towards the new dynamics related to scientific outcomes and publishing. The Fourth Scientific Paradigm leads to a science that is based on intensive use of scientific information through the practices of the emerging model called e-Science. This type of science reflects a collaborative scientific environment that considers sharing, convergence, connectivity, interactivity, use and reuse of scientific data. This environment is based on the assumptions of a more open science and emerging models. In this context, the data life cycle model is adopted in order to drive and support scientific data management. Thus, this thesis constitutes a multidimensional and multidisciplinary study that relies on the confluence between Information Science and Law Sciences and its intersections with Economy and Technology. Theoretically, the study is supported by Commons Theory and Creative Economy; considering current intellectual property regulations and legislations as well as international guidelines for the new dynamics of e-Science. The core argument of this thesis is that in e-Science authority is collaborative practice; promoted by authorship rewards. The study object of the research is centered on authorship of scientific data considered as an intellectual asset. The work aims to elaborate standards that promote reward towards collaborative authority in e-Science. The research is predominantly qualitative. Bardin´s content analysis was used for categorizing, coding and performing inferences. The research also relied on the six dimensions (epistemological, theoretical, technical, morphological, political and ethical) according to study of Bufrem that guided the development of the chapters, content analysis and the conceptual model. The NVivo software was used for categorization, codification and corpus analysis. The multidimensional view and thematic connections resulted in five categories and thirteen subcategories that helped achieve the objective and indicate the standards of the proposed model for the representation of authorship in e-Science. It concludes that in the context of e- Science, authority is collaborative and ensured by copyright rewards through attribution, citation and accountability. Authorship attribution and citation are usual procedures, but in contemporary practice the responsibility is assigned to each collaborator proportionally. Thus, the thesis is confirmed and is represented by the conceptual model of collaborative authority in e-Science. The model is composed of multi-dimensional patterns that represent the scenario of collaborative open science that focuses on sharing, accessibility; oriented towards to the use and reuse of scientific data. Finally, each standard model represents guiding axioms that will help authors, researchers, curators, librarians, stakeholders, academic institutions, scientific and development agencies to conduct and share scientific data management projects in the context of e–Science to minimally guarantee authorship behalf of all the parties involved. / apresenta um novo espectro de uma ciência aberta com mudanças nas práticas científicas vigentes. Essas práticas estão sendo aprimoradas, ressignificadas e reconduzidas para as novas dinâmicas no fazer e publicar a pesquisa científica. O quarto paradigma científico conduz essa ciência que é baseada no uso intensivo de dados científicos através das práticas do modelo emergente da e-Science. A e-Science reflete um ambiente científico de colaboração, compartilhamento, convergência, conectividade, interatividade, uso e reuso de dados científicos. Esse ambiente constitui os pressupostos da ciência aberta e do modelo emergente. O ciclo de vida dos dados é adotado para conduzir e apoiar o gerenciamento de dados científicos. Dessa forma, a tese traz um estudo multidimensional e multidisciplinar através da confluência entre a Ciência da Informação e as Ciências Jurídicas e suas interseções com a Economia e Tecnologia. Teoricamente, o estudo apoia-se na vertente do commons preconizado pela Teoria do Commons e Economia Criativa, nas regulações e legislações da Propriedade Intelectual vigentes e em diretrizes internacionais para as novas dinâmicas da e- Science. O argumento de tese propõe que na e-Science a autoralidade é colaborativa e promovida pela recompensa autoral. O objeto de estudo está centrado na autoralidade dos dados científicos como bens intelectuais e o objetivo geral busca elaborar padrões que promovam a recompensa autoral na e-Science. A pesquisa é predominantemente qualitativa e adotou a análise de conteúdo de Bardin para a categorização, codificação e inferências do corpus de análise. Foi substanciada pelas seis dimensões (epistemológica, teórica, técnica, morfológica, política e ética) do estudo de Bufrem. Tal estudo foi norteador para o desenvolvimento dos capítulos, análise de conteúdo e constituição do modelo conceitual. Utilizou-se para a categorização e codificação do corpus de análise o software NVivo. A visão multidimensional e conexões temáticas resultaram em cinco categorias e treze subcategorias que ajudaram a alcançar o objetivo e constituir os padrões do modelo proposto para a representação da autoralidade na e-Science. Concluiu-se que a autoralidade no contexto da e- Science é colaborativa. A autoralidade colaborativa é garantida mediante a recompensa autoral através da atribuição, citação e responsabilização. A atribuição e citação são procedimentos usuais, contudo nas práticas contemporâneas a responsabilidade é atribuída a cada colaborador na proporcionalidade de sua participação. Assim, a tese se confirmou e está representada pelo modelo conceitual de autoralidade colaborativa na e-Science. O modelo é composto por padrões multidimensionais que representam o cenário da ciência aberta colaborativa, compartilhada e acessível orientada ao uso e reuso dos dados científicos. Por fim, cada padrão do modelo constitui-se em axiomas norteadores que auxiliarão autores, pesquisadores, curadores, bibliotecários e demais colaboradores, bem como instituições acadêmicas, científicas e agências de fomento a conduzirem projetos de compartilhamento e gerenciamento de dados científicos no contexto da e-Science com garantia mínima à autoralidade de todos os envolvidos.

Data from present day scientific simulations and observations of physical processes often consist of multiple scalar fields. It is important to study the interactions between the fields to understand the underlying phenomena. A visual representation of these interactions would assist the scientist by providing quick insights into complex relationships that exist between the fields. We describe new techniques for visual analysis of multifield scalar data where the relationships can be quantified by the gradients of the individual scalar fields and their mutual alignment. Empirically, gradients along with their mutual alignment have been shown to be a good indicator of the relationships between the different scalar variables. The Jacobi set, defined as the set of points where the gradients are linearly dependent, describes the relationship between the gradient fields. The Jacobi set of two piecewise linear functions may contain several components indicative of noisy or a feature-rich dataset. For two dimensional domains, we pose the problem of simplification as the extraction of level sets and offset contours and describe a robust technique to simplify and create a multi-resolution representation of the Jacobi set. Existing isosurface-based techniques for scalar data exploration like Reeb graphs, contour spectra, isosurface statistics, etc., study a scalar field in isolation. We argue that the identification of interesting isovalues in a multifield data set should necessarily be based on the interaction between the different fields. We introduce a variation density function that profiles the relationship between multiple scalar fields over isosurfaces of a given scalar field. This profile serves as a valuable tool for multifield data exploration because it provides the user with cues to identify interesting isovalues of scalar fields. Finally, we introduce a new multifield comparison measure to capture relationships between scalar variables. We also show that our measure is insensitive to noise in the scalar fields and to noise in their gradients. Further, it can be computed robustly and efficiently. The comparison measure can be used to identify regions of interest in the domain where interactions between the scalar fields are significant. Subsequent visualization of the data focuses on these regions of interest leading to effective visual analysis. We demonstrate the effectiveness of our techniques by applying them to real world data from different domains like combustion studies, climate sciences and computer graphics.

Scalar fields are used to represent physical quantities measured over a domain of interest. Study of symmetric or repeating patterns in scalar fields is important in scientific data analysis because it gives deep insights into the properties of the underlying phenomenon. This thesis proposes three methods to detect symmetry in scalar fields. The first method models symmetry detection as a subtree matching problem in the contour tree, which is a topological graph abstraction of the scalar field. The contour tree induces a hierarchical segmentation of features at different scales and hence this method can detect symmetry at different scales. The second method identifies symmetry by comparing distances between extrema from each symmetric region. The distance is computed robustly using a topological abstraction called the extremum graph. Hence, this method can detect symmetry even in the presence of significant noise. The above methods compare pairs of regions to identify symmetry instead of grouping the entire set of symmetric regions as a cluster. This motivates the third method which uses a clustering analysis for symmetry detection. In this method, the contours of a scalar field are mapped to points in a high-dimensional descriptor space such that points corresponding to similar contours lie in close proximity to each other. Symmetry is identified by clustering the points in the descriptor space. We show through experiments on real world data sets that these methods are robust in the presence of noise and can detect symmetry under different types of transformations. Extraction of symmetry information helps users in visualization and data analysis. We design novel applications that use symmetry information to enhance visualization of scalar field data and to facilitate their exploration.

The radio astronomy and space geodesy scientific instrumentation of the Hartebeesthoek Radio Astronomy Observatory (HartRAO) in Gauteng, South Africa, generate large volumes of data. Additional large data volumes will be generated by new geodesy instruments that are currently under construction and implementation, including a lunar laser ranging (LLR) system, seismic and meteorological systems and a Very Long Baseline Interferometry (VLBI) global observing system (VGOS) radio telescope. The existing HartRAO data management and storage system is outdated, incompatible and has limited storage capacity. This necessitates the design of a new geodetic research data management system (GRDMS). The focus of this dissertation is on providing a contextual framework for the design of the new system, including criteria, characteristics, components, an infrastructure architectural model and data structuring and organisation. An exploratory research methodology and qualitative research techniques were applied. Results attained from interviews conducted and literature consulted indicates a gap in the literature regarding the design of a data management system, specifically for geodetic data generated by HartRAO instrumentation. This necessitates the development of a conceptual framework for the design of a new GRDMS. Results are in alignment with the achievement of the research questions and objectives set for this study. / Information Science / M.A. (Information Science)