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conference on data Mining and Knowledge Discovery - Theory, Tools, and Technology ii

作者： Wachowicz, M Wageningen UR Ctr Geoinformat Wageningen Netherlands

ISBN: (纸本)0819436836

This paper proposes the integration of KDD, GVis and STDB as a long-term strategy, which will allow users to apply knowledge discovery methods for uncovering spatio-temporal patterns in environmental data. The main goal is to combine innovative techniques and associated tools for exploring very large environmental data sets in order to arrive at valid, novel, potentially useful, and ultimately understandable spatio-temporal patterns. The GeoInsight approach is described using the principles and key developments in the research domains of KDD, GVis, and STDB. The GeoInsight approach aims at the integration of these research domains in order to provide tools for performing information retrieval, exploration, analysis, and visualisation. The result is a knowledge-based design, which involves visual thinking (perceptual-cognitive process) and automated information processing (computer-analytical process).

关键词： data mining knowledge discovery geographic visualisation spatio-temporal databases geographical image databases exploratory data analysis and exploratory visual analysis

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visual exploration of Nasal Airflow

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IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2009年第6期15卷 1407-1414页

作者： Zachow, Stefan Muigg, Philipp Hildebrandt, Thomas Doleisch, Helmut Hege, Hans-Christian ZIB Berlin Germany Vienna Univ Technol Inst Comp Graph & Algorithms Vienna Austria

Rhinologists are often faced with the challenge of assessing nasal breathing from a functional point of view to derive effective therapeutic interventions. While the complex nasal anatomy can be revealed by visual inspection and medical imaging, only vague information is available regarding the nasal airflow itself: Rhinomanometry delivers rather unspecific integral information on the pressure gradient as well as on total flow and nasal flow resistance. In this article we demonstrate how the understanding of physiological nasal breathing can be improved by simulating and visually analyzing nasal airflow, based on an anatomically correct model of the upper human respiratory tract. In particular we demonstrate how various Information visualization (InfoVis) techniques, such as a highly scalable implementation of parallel coordinates, time series visualizations, as well as unstructured grid multi-volume rendering, all integrated within a multiple linked views framework, can be utilized to gain a deeper understanding of nasal breathing. Evaluation is accomplished by visual exploration of spatio-temporal airflow characteristics that include not only information on flow features but also on accompanying quantities such as temperature and humidity. To our knowledge, this is the first in-depth visual exploration of the physiological function of the nose over several simulated breathing cycles under consideration of a complete model of the nasal airways, realistic boundary conditions, and all physically relevant time-varying quantities.

关键词： Flow visualization exploratory data analysis interactive visual analysis of scientific data time-dependent data

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Mobility Graphs: visual analysis of Mass Mobility Dynamics via Spatio-Temporal Graphs and Clustering

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IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2016年第1期22卷 11-20页

作者： von Landesberger, Tatiana Brodkorb, Felix Roskosch, Philipp Andrienko, Natalia Andrienko, Gennady Kerren, Andreas Tech Univ Darmstadt Darmstadt Germany Fraunhofer IAIS Bonn Germany City Univ London London EC1V 0HB England Linnaeus Univ Vaxjo Sweden

Learning more about people mobility is an important task for official decision makers and urban planners. Mobility data sets characterize the variation of the presence of people in different places over time as well as movements (or flows) of people between the places. The analysis of mobility data is challenging due to the need to analyze and compare spatial situations (i.e., presence and flows of people at certain time moments) and to gain an understanding of the spatio-temporal changes (variations of situations over time). Traditional flow visualizations usually fail due to massive clutter. Modern approaches offer limited support for investigating the complex variation of the movements over longer time periods. We propose a visual analytics methodology that solves these issues by combined spatial and temporal simplifications. We have developed a graph-based method, called Mobility Graphs, which reveals movement patterns that were occluded in flow maps. Our method enables the visual representation of the spatio-temporal variation of movements for long time series of spatial situations originally containing a large number of intersecting flows. The interactive system supports data exploration from various perspectives and at various levels of detail by interactive setting of clustering parameters. The feasibility our approach was tested on aggregated mobility data derived from a set of geolocated Twitter posts within the Greater London city area and mobile phone call data records in Abidjan, Ivory Coast. We could show that Mobility Graphs support the identification of regular daily and weekly movement patterns of resident population.

关键词： visual analytics movement data networks graphs temporal aggregation spatial aggregation flows clustering

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visual Process Mining: Event data exploration and analysis

Visual Process Mining: Event Data Exploration and Analysis

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IEEE conference visual Analytics Sci Technology

作者： Bodesinsky, Peter Alsallakh, Bilal Gschwandtner, Theresia Miksch, Silvia Vienna Univ Technol Vienna Austria

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 visual exploration 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.

关键词： data mining data visualisation interactive systems automated pattern mining method browsing event logs event data exploration interactive environment visual exploration visual process mining Business data mining data visualization Inspection Prototypes Sorting visualization data visualisation Interactive environment data mining visualization interactive systems Business PROTOTYPE event log sorting programs mining Inspection exploration event patterns

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visual exploration of migration patterns in gull data

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INFORMATION visualIZATION 2019年第1期18卷 138-152页

作者： Konzack, Maximilian Gijsbers, Pieter Timmers, Ferry van Loon, Emiel Westenberg, Michel A. Buchin, Kevin TU Eindhoven POB 513 NL-5600 MB Eindhoven Netherlands Univ Amsterdam Amsterdam Netherlands

We present a visual analytics approach to explore and analyze movement data as collected by ecologists interested in understanding migration. Migration is an important and intriguing process in animal ecology, which may be better understood through the study of tracks for individuals in their environmental context. Our approach enables ecologists to explore the spatio-temporal characteristics of such tracks interactively. It identifies and aggregates stopovers depending on a scale at which the data is visualized. Statistics of stopover sites and links between them are shown on a zoomable geographic map which allows to interactively explore directed sequences of stopovers from an origin to a destination. In addition, the spatio-temporal properties of the trajectories are visualized by means of a density plot on a geographic map and a calendar view. To evaluate our visual analytics approach, we applied it on a data set of 75 migrating gulls that were tracked over a period of 3 years. The evaluation by an expert user confirms that our approach supports ecologists in their analysis workflow by helping to identifying interesting stopover locations, environmental conditions or (groups of) individuals with characteristic migratory behavior, and allows therefore to focus on visual data analysis.

关键词： visual analytics animal behavior data visualization spatio-temporal visualization geovisualization

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HiPiler: visual exploration of Large Genome Interaction Matrices with Interactive Small Multiples

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IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2018年第1期24卷 522-531页

作者： Lekschas, Fritz Bach, Benjamin Kerpedjiev, Peter Gehlenborg, Nils Pfister, Hanspeter Harvard Univ Cambridge MA 02138 USA Harvard Med Sch Boston MA USA

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 data exploration sessions with domain experts to assess the usability of HiPiler as well as to demonstrate respective findings in the data.

关键词： Interactive Small Multiples Matrix Comparison Biomedical visualization Genomics

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visual exploration and functional document labeling 6

Visual exploration and functional document labeling

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6th International conference on Document analysis and Recognition (ICDAR)

作者： Eglin, V Gagneux, A Inst Natl Sci Appl Lab Reconnaissance Formes & Vis RFV F-69621 Villeurbanne France

ISBN: (纸本)0769512631

This paper presents a new approach to textual data labeling based on texture analysis. Texture is used here to show the impact of document composition on visual exploration. We demonstrate how textural properties are well adapted to typography characterization by categorizing document regions into visual text classes (such as headings, head- and footnotes, paragraphs, abstracts, etc.). We reference and classify different types of text fonts according to their visual aspect and the visual impression that emerges from the textual data. Experiments on a set of various document images show a good accuracy and robustness for our method.

关键词： visualization

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MASSIVELY PARALLEL SURFACE RENDERING 2

MASSIVELY PARALLEL SURFACE RENDERING

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conference on visual data exploration and analysis ii

作者： DATTA, S GUHA, R UNIV CENT FLORIDA DEPT COMP SCIORLANDOFL 32816

In this parallel surface rendering algorithm based on dividing cube2 on a SIMD machine MasPar MP-1, we address the problem of load balancing and image composition. We divide a 3D array of Nx x Ny x Nz volume data into... 详细信息

ISBN: (纸本)0819417572

In this parallel surface rendering algorithm based on dividing cube² on a SIMD machine MasPar MP-1, we address the problem of load balancing and image composition. We divide a 3D array of N_x x N_y x N_z volume data into N_x x N_y columns, each N_z deep. Each processor in the mesh receives a subvolume of such data columns. All processors synchronously traverse its subvolume to determine the voxels intersecting the isosurface. Intersecting voxels are called isovoxels. Partial load balancing distributes the isovoxels contained in a row of processors evenly among the processors in that row to reduce the network traffic and complexity of the rendering phase. Each isovoxel is subdivided into point primitives using dividing cube algorithm. Rendering algorithm transforms the surface points and their normals and projects them into the view plane.

关键词： data processing Algorithm development data communications Raster graphics Transform theory 3D displays Medical imaging Volume rendering Computer graphics Computer science

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visual exploration of Local Interest Points in Sets of Time Series

Visual Exploration of Local Interest Points in Sets of Time ...

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IEEE conference on visual Analytics Science and Technology (VAST)

作者： Schreck, Tobias Sharalieva, Lyubka Wanner, Franz Bernard, Juergen Ruppert, Tobias von Landesberger, Tatiana Bustos, Benjamin Univ Konstanz Constance Germany

ISBN: (纸本)9781467347532;9781467347525

visual analysis of time series data is an important, yet challenging task with many application examples in fields such as financial or news stream data analysis. Many visual time series analysis approaches consider a global perspective on the time series. Fewer approaches consider visual analysis of local patterns in time series, and often rely on interactive specification of the local area of interest. We present initial results of an approach that is based on automatic detection of local interest points. We follow an overview-first approach to find useful parameters for the interest point detection, and details-on-demand to relate the found patterns. We present initial results and detail possible extensions of the approach.

关键词： time series data Time series visual analytics Corner detection SETTING automatic detection visualization exploration news

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Prefetching for visual data exploration 8

Prefetching for visual data exploration

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8th International conference on database Systems for Advanced Applications

作者： Doshi, PR Rundensteiner, EA Ward, MO Worcester Polytech Inst Dept Comp Sci Worcester MA 01609 USA

ISBN: (纸本)0769518958

Modern computer applications, from business decision support to scientific data analysis, utilize data visualization tools to support exploratory activities. visual exploration tools typically do not scale well when applied to huge data sets, partially because being interactive necessitates real-time responses. However we observe that interactive visual explorations exhibit several properties that can be exploited for data access optimization, including locality of exploration, contiguous queries, and significant delays between user operations. We thus apply semantic caching of active query sets on the client side to exploit some of the above characteristics. We also introduce several prefetching strategies, each exploiting characteristics of our visual exploration environment. We have incorporated caching and prefetching strategies into XmdvTool, a public-domain tool for visual exploration of multivariate data sets. Experimental studies using synthetic as well as real user traces are conducted. Our results demonstrate that these proposed optimization techniques achieve significant performance improvements in our exploratory analysis system.

关键词： Computer applications Computer science data analysis data visualization Delay Marketing and sales Navigation Performance analysis Prefetching Stock markets

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