The visualexploration of large databases raises a number of unresolved inference problems and calls for new interaction patterns between multiple disciplines-both at the conceptual and technical level. We present an ...
详细信息
The visualexploration of large databases raises a number of unresolved inference problems and calls for new interaction patterns between multiple disciplines-both at the conceptual and technical level. We present an approach that is based on the interaction of four disciplines: database systems, statistical analyses, perceptual and cognitive psychology, and scientific visualization. At the conceptual level we offer perceptual and cognitive insights to guide the information visualization process. We then choose cluster surfaces to exemplify the data mining process, to discuss the tasks involved, and to work out the interaction patterns. (C) 2003 Elsevier B.v. All rights reserved.
Single-cell analysis through mass cytometry has become an increasingly important tool for immunologists to study the immune system in health and disease. Mass cytometry creates a high-dimensional description vector fo...
详细信息
Single-cell analysis through mass cytometry has become an increasingly important tool for immunologists to study the immune system in health and disease. Mass cytometry creates a high-dimensional description vector for single cells by time-of-flight measurement. Recently, t-Distributed Stochastic Neighborhood Embedding (t-SNE) has emerged as one of the state-of-the-art techniques for the visualization and exploration of single-cell data. Ever increasing amounts of data lead to the adoption of Hierarchical Stochastic Neighborhood Embedding (HSNE), enabling the hierarchical representation of the data. Here, the hierarchy is explored selectively by the analyst, who can request more and more detail in areas of interest. Such hierarchies are usually explored by visualizing disconnected plots of selections in different levels of the hierarchy. This poses problems for navigation, by imposing a high cognitive load on the analyst. In this work. we present an interactive summary-visualization to tackle this problem. CyteGuide guides the analyst through the exploration of hierarchically represented single-cell data, and provides a complete overview of the current state of the analysis. We conducted a two-phase user study with domain experts that use HSNE for dataexploration. We first studied their problems with their current workflow using HSNE and the requirements to ease this workflow in a field study. These requirements have been the basis for our visual design. In the second phase, we verified our proposed solution in a user evaluation.
Based on the hypothesis of one-to-one relationship between the external symptoms of epileptic fits and the abnormal cerebral functioning which causes it, the computerized study of epileptic fit video tapes brings new ...
详细信息
ISBN:
(纸本)0819424285
Based on the hypothesis of one-to-one relationship between the external symptoms of epileptic fits and the abnormal cerebral functioning which causes it, the computerized study of epileptic fit video tapes brings new information on abnormal neuron activity. This insight will improve specialist's analysis in their diagnoses.
The identification of significant sequences in large and complex event-based temporal data is a challenging problem with applications in many areas of today's information intensive society. Pure visual representat...
详细信息
The identification of significant sequences in large and complex event-based temporal data is a challenging problem with applications in many areas of today's information intensive society. Pure visual representations can be used for the analysis, but are constrained to small data sets. Algorithmic search mechanisms used for larger data sets become expensive as the data size increases and typically focus on frequency of occurrence to reduce the computational complexity, often overlooking important infrequent sequences and outliers. In this paper we introduce an interactive visualdata mining approach based on an adaptation of techniques developed for web searching, combined with an intuitive visual interface, to facilitate user-centred exploration of the data and identification of sequences significant to that user. The search algorithm used in the exploration executes in negligible time, even for large data, and so no pre-processing of the selected data is required, making this a completely interactive experience for the user. Our particular application area is social science diary data but the technique is applicable across many other disciplines.
The increasing availability of rating datasets (i.e., datasets containing user evaluations on items such as products and services) constitutes a new opportunity in various applications ranging from behavioral analytic...
详细信息
The increasing availability of rating datasets (i.e., datasets containing user evaluations on items such as products and services) constitutes a new opportunity in various applications ranging from behavioral analytics to recommendations. In this paper, we describe the design of vUGA, a visual enabler for the exploration of rating data and user groups. vUGA helps analysts, be they novice analysts or domain experts, acquire an understanding of their data through a seamless integration between exploring users and exploring their collective behavior via group analysis. vUGA is data-driven and does not require analysts to know the value distributions in their data. While automated systems can identify and suggest potentially interesting groups, they can do that for well-specified needs (e.g., through SQL QUERIES or constrained mining). vUGA helps analysts filter and refine their exploration as they discover what lies in the data. vUGA enables analysts to easily acquire statistics about their data, form groups, and find similar and dissimilar groups. While most visual analytics systems are data-dependent, vUGA relies on a data model that captures user data in such a way that a variety of group formation and exploration approaches can be used. We describe the architecture of vUGA and illustrate its use via tasks and a user study. We conclude with a discussion on future work enabled by vUGA. (C) 2019 Elsevier B.v. All rights reserved.
Optical coherence tomography (OCT) enables noninvasive high-resolution 3D imaging of the human retina, and thus plays a fundamental role in detecting a wide range of ocular diseases. Despite the diagnostic value of OC...
详细信息
Optical coherence tomography (OCT) enables noninvasive high-resolution 3D imaging of the human retina, and thus plays a fundamental role in detecting a wide range of ocular diseases. Despite the diagnostic value of OCT, managing and analyzing resulting data is challenging. We apply two visualanalysis strategies for supporting retinal assessment in practice. First, we provide an interface for unifying and structuring data from different sources into a common basis. Fusing that basis with medical records and augmenting it with analytically derived information facilitates thorough investigations. Second, we present a tailored visualanalysis tool for presenting, emphasizing, selecting, and comparing different aspects of the attributed data. This enables free exploration, reducing the data to relevant subsets, and focusing on details. By applying both strategies, we effectively enhance the management and the analysis of retinal OCT data for assisting medical diagnoses. Domain experts applied our solution successfully to study early retinal changes in patients suffering from type 1 diabetes mellitus.
This design study focuses on the analysis of a time sequence of categorical sequences. Such data is relevant for the geoscientific research field of landscape and climate development. It results from microscopic analy...
详细信息
This design study focuses on the analysis of a time sequence of categorical sequences. Such data is relevant for the geoscientific research field of landscape and climate development. It results from microscopic analysis of lake sediment cores. The goal is to gain hypotheses about landscape evolution and climate conditions in the past. To this end, geoscientists identify which categorical sequences are similar in the sense that they indicate similar conditions. Categorical sequences are similar if they have similar meaning (semantic similarity) and appear in similar time periods (temporal similarity). For data sets with many different categorical sequences, the task to identify similar sequences becomes a challenge. Our contribution is a tailored visualanalysis concept that effectively supports the analytical process. Our visual interface comprises coupled visualizations of semantics and temporal context for the exploration and assessment of the similarity of categorical sequences. Integrated automatic methods reduce the analytical effort substantially. They (1) extract unique sequences in the data and (2) rank sequences by a similarity measure during the search for similar sequences. We evaluated our concept by demonstrations of our prototype to a larger audience and hands-on analysis sessions for two different lakes. According to geoscientists, our approach fills an important methodological gap in the application domain.
Multidimensional visualization techniques are invaluable tools for analysis of structured and unstructured data with variable dimensionality. This paper introduces PEx-Image-Projection Explorer for Images-a tool aimed...
详细信息
Multidimensional visualization techniques are invaluable tools for analysis of structured and unstructured data with variable dimensionality. This paper introduces PEx-Image-Projection Explorer for Images-a tool aimed at supporting analysis of image collections. The tool supports a methodology that employs interactive visualizations to aid user-driven feature detection and classification tasks, thus offering improved analysis and exploration capabilities. The visual mappings employ similarity-based multidimensional projections and point placement to layout the data on a plane for visualexploration. In addition to its application to image databases, we also illustrate how the proposed approach can be successfully employed in simultaneous analysis of different data types, such as text and images, offering a common visual representation for data expressed in different modalities.
The stress states encountered in ion implanted materials are often complicated, and, so analysis, and hence presentation thereof, is incomplete due to unavailability of computational and visual tools. Stress states de...
详细信息
The stress states encountered in ion implanted materials are often complicated, and, so analysis, and hence presentation thereof, is incomplete due to unavailability of computational and visual tools. Stress states determined by X-ray and neutron diffraction are usually calculated from the gradient of sin(2)Psi curves. This process, inter alia, contracts the stress to a scalar, losing the directionality and multivariate nature of the real stress state. In this paper we present a novel approach to the stress profile analysis and presentation obtained by X-ray diffraction. Stress is considered as a tensorial quantity from the initial measurement phase to the final presentation. This discussion inherently brings in the depth resolution of stresses, which in turn are explained by means of clear visual explanations. visual tools, which are not common use in the field, are introduced and the benefits as applied to ion implantation are discussed. (C) 2007 Elsevier B.v. All rights reserved.
It is crucial to visually extrapolate the characteristics of their evolution to understand critical spatio-temporal events such as earthquakes, fires, or the spreading of a disease. Animations embedded in the spatial ...
详细信息
It is crucial to visually extrapolate the characteristics of their evolution to understand critical spatio-temporal events such as earthquakes, fires, or the spreading of a disease. Animations embedded in the spatial context can be helpful for understanding details, but have proven to be less effective for overview and comparison tasks. We present an interactive approach for the exploration of spatio-temporal data, based on a set of neighborhood-preserving 1D projections which help identify patterns and support the comparison of numerous time steps and multivariate data. An important objective of the proposed approach is the visual description of local neighborhoods in the 1D projection to reveal patterns of similarity and propagation. As this locality cannot generally be guaranteed, we provide a selection of different projection techniques, as well as a hierarchical approach, to support the analysis of different data characteristics. In addition, we offer an interactive exploration technique to reorganize and improve the mapping locally to users' foci of interest. We demonstrate the usefulness of our approach with different real-world application scenarios and discuss the feedback we received from domain and visualization experts.
暂无评论