1,721,129 research outputs found
Towards Automatic Feature-based Visualization
Get PDFVisualizations are well suited to communicate large amounts of complex data. With increasing resolution in the spatial and temporal domain simple imaging techniques meet their limits, as it is quite difficult to display multiple variables in 3D or analyze long video sequences. Feature detection techniques reduce the data-set to the essential structures and allow for a highly abstracted representation of the data. However, current feature detection algorithms commonly rely on a detailed description of each individual feature. In this paper, we present a feature-based visualization technique that is solely based on the data. Using concepts from computational mechanics and information theory, a measure, local statistical complexity, is defined that extracts distinctive structures in the data-set. Local statistical complexity assigns each position in the (multivariate) data-set a scalar value indicating regions with extraordinary behavior. Local structures with high local statistical complexity form the features of the data-set. Volume-rendering and iso-surfacing are used to visualize the automatically extracted features of the data-set. To illustrate the ability of the technique, we use examples from diffusion, and flow simulations in two and three dimensions
Tracking Lines in Higher Order Tensor Fields
Get PDFWhile tensors occur in many areas of science and engineering, little has been done to visualize tensors with order higher than two. Tensors of higher orders can be used for example to describe complex diffusion patterns in magnetic resonance imaging (MRI). Recently, we presented a method for tracking lines in higher order tensor fields that is a generalization of methods known from first order tensor fields (vector fields) and symmetric second order tensor fields. Here, this method is applied to magnetic resonance imaging where tensor fields are used to describe diffusion patterns for example of hydrogen in the human brain. These patterns align to the internal structure and can be used to analyze interconnections between different areas of the brain, the so called tractography problem. The advantage of using higher order tensor lines is the ability to detect crossings locally, which is not possible in second order tensor fields. In this paper, the theoretical details will be extended and tangible results will be given on MRI data sets
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
WebGL-based Geodata Visualization for Policy Support and Decision Making
No full textAccessible data visualizations are crucial to reaching a wide audience and supporting the decision making processes. With increasing support of WebGL and the new HTML5 standard, the Internet becomes an interesting platform for visualization and data analysis. In contrast to standalone applications, WebGL-based visualizations are easily accessible, cross-platform compatible, and do not require additional software installation. In this work, we propose a WebGL-based visualization that combines various web technologies to interactively explore, analyze, and communicate environmental geodata. As an application case study, we chose an energy consumption dataset for Maricopa County, Arizona, USA. Our study highlights the power of web visualizations and how they can support decision making in collaborative environments.Workshop on Visualisation in Environmental Sciences (EnvirVis
Utilizing GeoTemCo for Visualizing Environmental Data
No full textWe demonstrate the use of the open source library GeoTemCo for the visualization and exploration of geospatialtemporal datasets from environmental sciences. With use cases from biodiversity, climatology and geophysics we investigate the capabilities and limitations of GeoTemCo, which types of research questions can be handled and how the observer is able to gain new insights about the given data.Workshop on Visualisation in Environmental Sciences (EnvirVis
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