The article focuses on the 10th anniversary of the ieee Computer Society's Information visualizationsymposium. At 10, information visualization is vigorous and thriving. In the early years, the symposium had diff...
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The article focuses on the 10th anniversary of the ieee Computer Society's Information visualizationsymposium. At 10, information visualization is vigorous and thriving. In the early years, the symposium had difficulty attracting enough good papers to fill the slots. Today it receives so many excellent papers that the acceptance rate is low. The field has become an academic success. Some projects have had notable commercial success. Display technologies are in the middle of a massive transition. Conventional CRTs are being swapped for large, megapixel flat-screen displays. This transition started with increasing display sizes in laptops and has accelerated as new as display technologies have moved into widely deployed consumer goods such as high-definition televisions. The result of these technology changes is that screen real estate is increasing. Seventeen- and 21-inch flat- Information visualization is domain specific. The most interesting visualizations solve problems. An emerging class of problem involves analyzing data that arrives in a stream. Massive sensor systems, video cameras, and transaction-processing systems generate real-time data streams.
We present a visual analytics paradigm and a system prototype for exploring web-scale graphs. A web-scale graph is described as a graph with similar to one trillion edges and similar to 50 billion vertices. While ther...
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ISBN:
(纸本)9781467385176
We present a visual analytics paradigm and a system prototype for exploring web-scale graphs. A web-scale graph is described as a graph with similar to one trillion edges and similar to 50 billion vertices. While there is an aggressive R&D effort in processing and exploring web-scale graphs among internet vendors such as Facebook and Google, visualizing a graph of that scale still remains an underexplored R&D area. The paper describes a nontraditional peek-and-filter strategy that facilitates the exploration of a graph database of unprecedented size for visualization and analytics. We demonstrate that our system prototype can 1) preprocess a graph with similar to 25 billion edges in less than two hours and 2) support database query and interactive visualization on the processed graph database afterward. Based on our computational performance results, we argue that we most likely will achieve the one trillion edge mark (a computational performance improvement of 40 times) for graph visual analytics in the near future.
Analyzing scientific datasets created from simulations on modern supercomputers is a daunting challenge due to the fast pace at which these datasets continue to grow. Low cost post analysis machines used by scientists...
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ISBN:
(纸本)9781538614242
Analyzing scientific datasets created from simulations on modern supercomputers is a daunting challenge due to the fast pace at which these datasets continue to grow. Low cost post analysis machines used by scientists to view and analyze these massive datasets are severely limited by their deficiencies in storage bandwidth, capacity, and computational power. Trying to simply move these datasets to these platforms is infeasible. Any approach to view and analyze these datasets on post analysis machines will have to effectively address the inevitable problem of data loss. Image based approaches are well suited for handling very largedatasets on low cost platforms. Three challenges with these approaches are how to effectively represent the original data with minimal data loss, analyze the data in regards to transfer function exploration, which is a key analysis tool, and quantify the error from data loss during analysis. We present a novel image based approach using distributions to preserve data integrity. At each view sample, view dependent data is summarized at each pixel with distributions to define a compact proxy for the original dataset. We present this representation along with how to manipulate and render large scale datasets on post analysis machines. We show that our approach is a good trade off between rendering quality and interactive speed and provides uncertainty quantification for the information that is lost.
People in different places talk about different things. This interest distribution is reflected by the newspaper articles circulated in a particular area. We use data from our large-scale newspaper analysis system (Ly...
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People in different places talk about different things. This interest distribution is reflected by the newspaper articles circulated in a particular area. We use data from our large-scale newspaper analysis system (Lydia) to make entity datamaps, a spatial visualization of the interest in a given named entity. Our goal is to identify entities which display regional biases. We develop a model of estimating the frequency of reference of an entity in any given city from the reference frequency centered in surrounding cities, and techniques for evaluating the spatial significance of this distribution.
The network management area deals with large amounts of data. Some of its protocols and techniques are not completely understood when it comes to usage patterns and most used features. The understanding of such charac...
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ISBN:
(纸本)9781424453672
The network management area deals with large amounts of data. Some of its protocols and techniques are not completely understood when it comes to usage patterns and most used features. The understanding of such characteristics is a challenging process, due to the massive data amount involved. This process can be supported by information visualization techniques. These consist in visual representations of data that make use of the unique properties of the human visual system to make insights about it in a more intuitive and effective way. In this context, interactivity has proved itself to be one of the main factors involved in providing such intuitiveness and effectiveness, specially in analysis of largedatasets. Nevertheless, few interaction possibilities are available in current network management traffic visualization systems. In this paper we present a set of interactive information visualization techniques adapted to visualize SNMP trace files. We used an insight-based evaluation to show how the presented techniques can aid on the insight achievement process.
For appreciating 3D cultural objects, e. g., artistic statues, traditional vehicles, and historical buildings or cities, visualization has mainly been used in the following styles: (1) realistic computer graphics, (2)...
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ISBN:
(纸本)9781479928736
For appreciating 3D cultural objects, e. g., artistic statues, traditional vehicles, and historical buildings or cities, visualization has mainly been used in the following styles: (1) realistic computer graphics, (2) artistic computer graphics, and (3) interactive virtual reality. However, for academic studying of 3D cultural objects, these styles are insufficient. Namely, we need more analytical styles that can extract invisible or veiled features of visualized targets. What makes such analytical visualization more important is recent rapid development of range-sensing technology to digitally archive real 3D objects. For example, modern laser scanning produces over 107 or 10(8) 3D point data for one measurement. To extract useful information from such large-scale and complex data, we need (A) precise 3D transparent visualization, (B) superposition of visual assistants, and (C) time-series visualization.
Developing visualization applications is nontrivial and poses special challenges. This is because typical visualization software processes a large amount of data, resulting in large and sometimes very complex data str...
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Developing visualization applications is nontrivial and poses special challenges. This is because typical visualization software processes a large amount of data, resulting in large and sometimes very complex data structures. Traditional debugging tools have limited use because they decouple the information they report from the spatiotemporal domain in which unexpected problems occur. This article presents a set of guidelines specifically for debugging visualization software. The guidelines come from experience in developing applications in both industry and research. The key is to exploit the strengths of computer graphics and visualization, while still using good software development practices. [ABSTRACT FROM PUBLISHER]
Performance analysis through visualization techniques usually suffers semantic limitations due to the size of parallel applications. Most performance visualization tools rely on data aggregation to work at scale, with...
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ISBN:
(纸本)9781479936069
Performance analysis through visualization techniques usually suffers semantic limitations due to the size of parallel applications. Most performance visualization tools rely on data aggregation to work at scale, without any attempt to evaluate the loss of information caused by such aggregations. This paper proposes a technique to evaluate the quality of aggregated representations - using measures from information theory - and to optimize such measures in order to build consistent multiresolution representations of large execution traces.
Efficient feature exploration in large-scale data sets using traditional post-hoc analysis approaches is becoming prohibitive due to the bottleneck stemming from I/O and output data sizes. This problem becomes more ch...
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ISBN:
(纸本)9781538614242
Efficient feature exploration in large-scale data sets using traditional post-hoc analysis approaches is becoming prohibitive due to the bottleneck stemming from I/O and output data sizes. This problem becomes more challenging when an ensemble of simulations are required to run for studying the influence of input parameters on the model output. As a result, scientists are inclining more towards analyzing the data in situ while it resides in the memory. In situ analysis aims at minimizing expensive data movement while maximizing the resource utilization for extraction of important information from the data. In this work, we study the evolution of rotating stall in jet engines using data generated from a large-scale flow simulation under various input conditions. Since the features of interest lack a precise descriptor, we adopt a fuzzy rule-based machine learning algorithm for efficient and robust extraction of such features. For scalable exploration, we advocate for an off-line learning and in situ prediction driven strategy that facilitates in-depth study of the stall. Task-specific information estimated in situ is visualized interactively during the post-hoc analysis revealing important details about the inception and evolution of stall. We verify and validate our method through comprehensive expert evaluation demonstrating the efficacy of our approach.
We describe Cartolabe, a web-based multiscale system for visualizing and exploring large textual corpora based on topics, introducing a novel mechanism for the progressive visualization of filtering queries. Initially...
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We describe Cartolabe, a web-based multiscale system for visualizing and exploring large textual corpora based on topics, introducing a novel mechanism for the progressive visualization of filtering queries. Initially designed to represent and navigate through scientific publications in different disciplines, Cartolabe has evolved to become a generic framework and accommodate various corpora, ranging from Wikipedia (4.5M entries) to the French National Debate (4.3M entries). Cartolabe is made of two modules: The first relies on natural language processing methods, converting a corpus and its entities (documents, authors, and concepts) into high-dimensional vectors, computing their projection on the two-dimensional plane, and extracting meaningful labels for regions of the plane. The second module is a web-based visualization, displaying tiles computed from the multidimensional projection of the corpus using the Umap projection method. This visualization module aims at enabling users with no expertise in visualization and dataanalysis to get an overview of their corpus, and to interact with it: exploring, querying, filtering, panning, and zooming on regions of semantic interest. Three use cases are discussed to illustrate Cartolabe's versatility and ability to bring large-scale textual corpus visualization and exploration to a wide audience.
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