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visually Exploring Transportation Schedules

IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2016年第1期22卷 170-179页

作者： Palomo, Cesar Guo, Zhan Silva, Claudio T. Freire, Juliana NYU New York NY 10003 USA

Public transportation schedules are designed by agencies to optimize service quality under multiple constraints. However, real service usually deviates from the plan. Therefore, transportation analysts need to identify, compare and explain both eventual and systemic performance issues that must be addressed so that better timetables can be created. The purely statistical tools commonly used by analysts pose many difficulties due to the large number of attributes at trip- and station-level for planned and real service. Also challenging is the need for models at multiple scales to Search for patterns at different times and stations, since analysts do not know exactly where or when relevant patterns might emerge and need to compute statistical summaries for multiple attributes at different granularities. To aid in this analysis, we worked in close collaboration with a transportation expert to design TR-EX, a visual exploration tool developed to identify, inspect and compare spatio-temporal patterns for planned and real transportation service. TR-EX combines two new visual encodings inspired by Marey's Train Schedule: Trips Explorer for trip-level analysis of frequency, deviation and speed;and Stops Explorer for station-level study of delay, wait time, reliability and performance deficiencies such as bunching. To tackle overplotting and to provide a robust representation for a large numbers of trips and stops at multiple scales, the system supports variable kernel bandwidths to achieve the level of detail required by users for different tasks. We justify our design decisions based on specific analysis needs of transportation analysts. We provide anecdotal evidence of the efficacy of TR-EX through a series of case studies that explore NYC subway service, which illustrate how TR-EX can be used to confirm hypotheses and derive new insights through visual exploration.

关键词： Transportation schedules kernel density estimation visual exploration

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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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Multi-Granular Trend Detection for Time-Series analysis

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IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2017年第1期23卷 661-670页

作者： van Goethem, Arthur Staals, Frank Loffler, Maarten Dykes, Jason Speckmann, Bettina TU Eindhoven Eindhoven Netherlands Aarhus Univ MADALGO DK-8000 Aarhus C Denmark Univ Utrecht NL-3508 TC Utrecht Netherlands City Univ London London England

Time series (such as stock prices) and ensembles (such as model runs for weather forecasts) are two important types of one-dimensional time-varying data. Such data is readily available in large quantities but visual analysis of the raw data quickly becomes infeasible, even for moderately sized data sets. Trend detection is an effective way to simplify time-varying data and to summarize salient information for visual display and interactive analysis. We propose a geometric model for trend-detection in one-dimensional time-varying data, inspired by topological grouping structures for moving objects in two-or higher-dimensional space. Our model gives provable guarantees on the trends detected and uses three natural parameters: granularity, support-size, and duration. These parameters can be changed on-demand. Our system also supports a variety of selection brushes and a time-sweep to facilitate refined searches and interactive visualization of (sub-)trends. We explore different visual styles and interactions through which trends, their persistence, and evolution can be explored.

关键词： Interactive exploration Trend Detection Time Series

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AggreSet: Rich and Scalable Set exploration using visualizations of Element Aggregations

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IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2016年第1期22卷 688-697页

作者： Yalcin, M. Adil Elmqvist, Niklas Bederson, Benjamin B. Univ Maryland College Pk MD 20742 USA

datasets commonly include multi-value (set-typed) attributes that describe set memberships over elements, such as genres per movie or courses taken per student. Set-typed attributes describe rich relations across elements, sets, and the set intersections. Increasing the number of sets results in a combinatorial growth of relations and creates scalability challenges. Exploratory tasks (e.g. selection, comparison) have commonly been designed in separation for set-typed attributes, which reduces interface consistency. To improve on scalability and to support rich, contextual exploration of set-typed data, we present AggreSet. AggreSet creates aggregations for each data dimension: sets, set-degrees, set-pair intersections, and other attributes. It visualizes the element count per aggregate using a matrix plot for set-pair intersections, and histograms for set lists, set-degrees and other attributes. Its non-overlapping visual design is scalable to numerous and large sets. AggreSet supports selection, filtering, and comparison as core exploratory tasks. It allows analysis of set relations inluding subsets, disjoint sets and set intersection strength, and also features perceptual set ordering for detecting patterns in set matrices. Its interaction is designed for rich and rapid data exploration. We demonstrate results on a wide range of datasets from different domains with varying characteristics, and report on expert reviews and a case study using student enrollment and degree data with assistant deans at a major public university.

关键词： Multi-valued attributes sets visualization set visualization data exploration interaction design scalability

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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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vISTILES: Coordinating and Combining Co-located Mobile Devices for visual data exploration

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IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2018年第1期24卷 626-636页

作者： Langner, Ricardo Horak, Tom Dachselt, Raimund Tech Univ Dresden Interact Media Lab Dresden Germany

We present vISTILES, a conceptual framework that uses a set of mobile devices to distribute and coordinate visualization views for the exploration of multivariate data. In contrast to desktop-based interfaces for information visualization, mobile devices offer the potential to provide a dynamic and user-defined interface supporting co-located collaborative data exploration with different individual workflows. As part of our framework, we contribute concepts that enable users to interact with coordinated & multiple views (CMv) that are distributed across several mobile devices. The major components of the framework are: (i) dynamic and flexible layouts for CMv focusing on the distribution of views and (ii) an interaction concept for smart adaptations and combinations of visualizations utilizing explicit side-by-side arrangements of devices. As a result, users can benefit from the possibility to combine devices and organize them in meaningful spatial layouts. Furthermore, we present a web-based prototype implementation as a specific instance of our concepts. This implementation provides a practical application case enabling users to explore a multivariate data collection. We also illustrate the design process including feedback from a preliminary user study, which informed the design of both the concepts and the final prototype.

关键词： Mobile devices coordinated & multiple views multi-display environment cross-device interaction

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Distributing a GIS using a parallel data approach

Distributing a GIS using a parallel data approach

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conference on visual data exploration and analysis v

作者： Monde, JR Wild, M USM Ctr Higher Learning Stennis Space Ctr MS 39529 USA

ISBN: (纸本)0819427381

The limitations of serial processors for managing large computationally intensive dataset problems in fields such as visualization and Geographical Information Systems (GIS) are well known. Parallel processing techniques, where one or many computational tasks are distributed across a number of processing elements, have been proposed as a solution to the problem. We describe a model for visualizing oceanographic data that extends an earlier technique of using data parallel algorithms on a dedicated parallel computer to an object-oriented distributed visualization system that forms a virtual parallel machine on a network computers. This paper presents a visualization model being developed by the University of Southern Mississippi demonstrating interactive visualization of oceanographic data. The test case involves visualization of two and three-dimensional oceanographic data (salinity, sound speed profile, currents, temperature, and depth) with Windows NT Pentium class computers serving as both servers and client workstations.

关键词： distributive parallel object inheritance DCOM GIS

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Interactions with sound parameters

Interactions with sound parameters

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conference on visual data exploration and analysis v

作者： Seetharaman, K Grinstein, G Smith, S Levkowitz, H Gen DataComm Inc Technol Res Ctr Middlebury CT USA

ISBN: (纸本)0819427381

Traditionally, visualization systems have focused on the visual sense. However, with the advent of multimedia and virtual reality systems, other senses such as sound and touch are being slowly incorporated into systems. Even in the visual channel, the majority of systems depend on the perception of geometry through graphical concepts such as lines, fillareas, windows, and raster pixmaps to provide the visualization feedback. Sound is being effectively used in visualization systems and is increasingly being integrated into mainstream systems. However, we have not made much progress in developing a fundamental understanding of interaction in non-geometric representational spaces. We are interested in extending simple interactions, such as zoom and pan, into other domains such as sound. Pitch is a perceptual quantity of sound that is associated with the physical quantity frequency. We describe how zoom and pan operations in pitch are supported. Formal definitions for these operations are also provided. Finally, we describe a prototype system for such interactions.

关键词： interaction visualization model data representations sound sonification

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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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Polyvis: Cross-Device Framework for Collaborative visual data analysis

PolyVis: Cross-Device Framework for Collaborative Visual Dat...

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IEEE International conference on Systems, Man and Cybernetics (SMC)

作者： Alsaiari, Abeer Johnson, Andrew Nishimoto, Arthur Univ Illinois Elect Visualizat Lab Chicago IL 60607 USA

ISBN: (纸本)9781728145693

Multi device environments present new opportunities for collaborative visual data analysis and sense making by utilizing each device's strengths and capabilities. However, one of the associated challenges with visual data analysis in multi device environments is the sharing of visual components across devices. We present a framework developed on top of SAGE2 platform for cross-device collaborative visual data exploration. As part of our framework, we contribute the concept of rapid development and assembling of visualizations that can span multiple devices of different modalities. It provides the users with an environment for visualization compositions that delegate the rendering to the target device, allowing them to augment their large display workspace with portable devices for further exploration territories. Facilitated by its intuitive visualization composition pipeline, users with no programming skills such as data analysts can enhance their analytical scope with no coding barriers. We describe the framework, its implementation with a use case, and the rationale behind its design.

关键词： visualization

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