Modern web clickstream data consists of long, high-dimensional sequences of multivariate events, making it difficult to analyze. Following the overarching principle that the visual interface should provide information...
详细信息
Modern web clickstream data consists of long, high-dimensional sequences of multivariate events, making it difficult to analyze. Following the overarching principle that the visual interface should provide information about the dataset at multiple levels of granularity and allow users to easily navigate across these levels, we identify four levels of granularity in clickstream analysis: patterns, segments, sequences and events. We present an analytic pipeline consisting of three stages: pattern mining, pattern pruning and coordinated exploration between patterns and sequences. Based on this approach, we discuss properties of maximal sequential patterns, propose methods to reduce the number of patterns and describe design considerations for visualizing the extracted sequential patterns and the corresponding raw sequences. We demonstrate the viability of our approach through an analysis scenario and discuss the strengths and limitations of the methods based on user feedback.
The human ear has a remarkable ability to detect temporal structures and patterns even in highly complex signals. Therefore, it is profitable to use the ear in dataanalysis especially in the cases where the amount of...
详细信息
ISBN:
(纸本)0819427381
The human ear has a remarkable ability to detect temporal structures and patterns even in highly complex signals. Therefore, it is profitable to use the ear in dataanalysis especially in the cases where the amount of data is vast for any practical visualization technique. The main principle in this paper is to incorporate psychoacoustic knowledge into the system. For example, auditory frequency resolution, i.e,, ERB-scale is used in mapping datavalues to control parameters of the system. A real time computer program with a graphical user interface where various parameters of the system can be controlled is developed. For example, the time scale is continuously adjustable and there are methods to focus on some aspects or fractions of the data. The results are promising and show that this approach has potential in sonification applications. The limitation of the modulation approach is the number of simultaneously detectable parameters.
The Advanced volume visualization Display (AvvD) research program is a joint research program between the Fraunhofer Center for Research in Computer Graphics, Inc. and Innovative Research and Development Corp. It is d...
详细信息
ISBN:
(纸本)0819427381
The Advanced volume visualization Display (AvvD) research program is a joint research program between the Fraunhofer Center for Research in Computer Graphics, Inc. and Innovative Research and Development Corp. It is dedicated to the real-time visualization of high-resolution volumetric sensor data sets, maximizing the use of the human visual system to facilitate detection and classification in extremely hostile environments. The AvvD program has successfully demonstrated the application of high-speed volume visualization to a number of detection and classification problems. Recent emphasis has been on sonar for undersea imaging using data from the Naval Undersea Warfare Center - Division Newport's High Resolution Array (HRA), and rapid mine detection using data from the Coastal System Station's Toroidal volume Search Sonar (TvSS). The AvvD system introduced a new capability: the intuitive composition of several "pings" into a synthetic volumetric set. This composite data is higher resolution, approaching optical quality, with soft shadows and broad specularities.
Identification of early signs of rotating stall is essential for the study of turbine engine stability. With recent advancements of high performance computing. high-resolution unsteady flow fields allow in depth explo...
详细信息
Identification of early signs of rotating stall is essential for the study of turbine engine stability. With recent advancements of high performance computing. high-resolution unsteady flow fields allow in depth exploration of rotating stall and its possible causes. Performing stall analysis, however, involves significant effort to process large amounts of simulation data, especially when investigating abnormalities across many time steps. In order to assist scientists during the exploration process, we present a visual analytics framework to identify suspected spatiotemporal regions through a comparative visualization so that scientists are able to focus on relevant data in more detail. To achieve this, we propose efficient stall analysis algorithms derived from domain knowledge and convey the analysis results through juxtaposed interactive plots. Using our integrated visualization system, scientists can visually investigate the detected regions for potential stall initiation and further explore these regions to enhance the understanding of this phenomenon. Positive feedback from scientists demonstrate the efficacy of our system in analyzing rotating stall.
The visualanalysis of large multidimensional spatiotemporal datasets poses challenging questions regarding storage requirements and query performance. Several data structures have recently been proposed to address th...
详细信息
The visualanalysis of large multidimensional spatiotemporal datasets poses challenging questions regarding storage requirements and query performance. Several data structures have recently been proposed to address these problems that rely on indexes that pre-compute different aggregations from a known-a-priori dataset. Consider now the problem of handling streaming datasets, in which data arrive as one or more continuous data streams. Such datasets introduce challenges to the data structure, which now has to support dynamic updates (insertions/deletions) and rebalancing operations to perform self reorganizations. In this work, we present the Packed-Memory Quadtree (PMQ), a novel data structure designed to support visualexploration of streaming spatiotemporal datasets. PMQ is cache-oblivious to perform well under different cache configurations. We store streaming data in an internal index that keeps a spatiotemporal ordering over the data following a quadtree representation, with support for real-time insertions and deletions. We validate our data structure under different dynamic scenarios and compare to competing strategies. We demonstrate how PMQ could be used to answer different types of visual spatiotemporal range queries of streaming datasets. (C) 2018 Elsevier Ltd. All rights reserved.
A fundamental challenge for time-varying volume dataanalysis and visualization is the lack of capability to observe and track data change or evolution in an occlusion-free, controllable, and adaptive fashion. In this...
详细信息
A fundamental challenge for time-varying volume dataanalysis and visualization is the lack of capability to observe and track data change or evolution in an occlusion-free, controllable, and adaptive fashion. In this paper, we propose to organize a time-varying data set into a hierarchy of states. By deriving transition probabilities among states, we construct a global map that captures the essential transition relationships in the time-varying data. We introduce the TransGraph, a graph-based representation to visualize hierarchical state transition relationships. The TransGraph not only provides a visual mapping that abstracts data evolution over time in different levels of detail, but also serves as a navigation tool that guides dataexploration and tracking. The user interacts with the TransGraph and makes connection to the volumetric data through brushing and linking. A set of intuitive queries is provided to enable knowledge extraction from time-varying data. We test our approach with time-varying data sets of different characteristics and the results show that the TransGraph can effectively augment our ability in understanding time-varying data.
The enormous growth of data in the last decades led to big data challenge in the network security field. Traditional visualanalysis method for large-scale network exploration is inadequate. Efficient methods for visu...
详细信息
ISBN:
(纸本)9781467395915
The enormous growth of data in the last decades led to big data challenge in the network security field. Traditional visualanalysis method for large-scale network exploration is inadequate. Efficient methods for visual clutter reduction, network structure exploration and network behavior detection are needed. In this paper, we propose two methods: Enhanced Histogram Brush (EHB) and Flow-based Fast Newman (FFN) algorithm aim to assist the visualanalysis task in large-scale network exploration. The EHB is a novel improvement in Parallel Coordinates to guide exploratory interactions especially for big data. The FFN algorithm can efficiently discover the network hierarchy and extremely reduce the visual clutter in the network layout. A visualanalysis tool PCNET is designed and implemented on the basis of these two novel methods. PCNET is capable of visually analyzing vast amounts of network data. To better describe and demonstrate the usefulness and performance of PCNET, we utilize the Chinavis2015 Challenge dataset as a case study.
This paper presents an interactive visualization interface HiPiler for the exploration and visualization of regions-of-interest in large genome interaction matrices. Genome interaction matrices approximate the physica...
详细信息
This paper presents an interactive visualization interface HiPiler for the exploration and visualization of regions-of-interest in large genome interaction matrices. Genome interaction matrices approximate the physical distance of pairs of regions on the genome to each other and can contain up to 3 million rows and columns with many sparse regions. Regions of interest (ROls) can be defined, e.g., by sets of adjacent rows and columns, or by specific visual patterns in the matrix. However, traditional matrix aggregation or pan-and-zoom interfaces fail in supporting search, inspection, and comparison of ROls in such large matrices. In HiPiler, ROls are first-class objects, represented as thumbnail-like "snippets". Snippets can be interactively explored and grouped or laid out automatically in scatterplots, or through dimension reduction methods. Snippets are linked to the entire navigable genome interaction matrix through brushing and linking. The design of HiPiler is based on a series of semi-structured interviews with 10 domain experts involved in the analysis and interpretation of genome interaction matrices. We describe six exploration tasks that are crucial for analysis of interaction matrices and demonstrate how HiPiler supports these tasks. We report on a user study with a series of dataexploration sessions with domain experts to assess the usability of HiPiler as well as to demonstrate respective findings in the data.
Hierarchical clustering techniques complemented with visual display of data sets allow direct interpretation of the clustering results in terms of original variables. The proposed method of data ordering and display i...
详细信息
Hierarchical clustering techniques complemented with visual display of data sets allow direct interpretation of the clustering results in terms of original variables. The proposed method of data ordering and display is simple, informative and fulfils fundamental objectives of the datavisualisation techniques. In our study, it is applied for exploratory analysis of an environmental data set. (C) 2002 Elsevier Science B.v. All rights reserved.
The research field of Process Mining deals with the extraction of information from event logs. Since large amounts of event data are generated every day, analyzing these often unstructured event logs poses a research ...
详细信息
ISBN:
(纸本)9781479962273
The research field of Process Mining deals with the extraction of information from event logs. Since large amounts of event data are generated every day, analyzing these often unstructured event logs poses a research challenge. To cope with the complexity of the data and the associated mining tasks, appropriate visualizations and interactive means are needed. We present our early prototype for the visualexploration of event sequences and patterns. Our approach combines (1) a visual representation of event sequences emphasizing recurring event patterns, (2) automated pattern mining methods, as well as (3) interactive means for exploration. We provide first steps to support browsing event logs in an interactive environment and to facilitate the inspection of recurring pattern locations within the context of the surrounding events.
暂无评论