EuroVis14: Eurographics Conference on Visualization

Permanent URI for this collection

https://diglib.eg.org/handle/10.2312/13889

Preface and Table of Contents

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Sets of Globally Optimal Stream Surfaces for Flow Visualization

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Schulze, Maik

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Esturo, Janick Martinez

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Günther, Tobias

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Rössl, Christian

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Seidel, Hans-Peter

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Weinkauf, Tino

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Theisel, Holger

Opacity Optimization for Surfaces

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Günther, Tobias

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Schulze, Maik

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Esturo, Janick Martinez

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Rössl, Christian

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Theisel, Holger

Extracting Features from Time-Dependent Vector Fields Using Internal Reference Frames

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Bhatia, Harsh

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Pascucci, Valerio

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Kirby, Robert M.

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Bremer, Peer-Timo

Mandatory Critical Points of 2D Uncertain Scalar Fields

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Günther, David

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Salmon, Joseph

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Tierny, Julien

Extended Branch Decomposition Graphs: Structural Comparison of Scalar Data

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Saikia, Himangshu

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Seidel, Hans-Peter

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Weinkauf, Tino

Stability of Dissipation Elements: A Case Study in Combustion

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Gyulassy, Attila

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Bremer, Peer-Timo

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Grout, Ray

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Kolla, Hemanth

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Chen, Jacqueline

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Pascucci, Valerio

Parallel Irradiance Caching for Interactive Monte-Carlo Direct Volume Rendering

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Khlebnikov, Rostislav

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Voglreiter, Philip

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Steinberger, Markus

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Kainz, Bernhard

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Schmalstieg, Dieter

RBF Volume Ray Casting on Multicore and Manycore CPUs

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Knoll, Aaron

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Wald, Ingo

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Navratil, Paul

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Bowen, Anne

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Reda, Khairi

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Papka, Mike E.

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Gaither, Kelly

Towards an Unbiased Comparison of CC, BCC, and FCC Lattices in Terms of Prealiasing

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Vad, Viktor

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Csébfalvi, Balázs

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Rautek, Peter

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Gröller, Eduard

InSpectr: Multi-Modal Exploration, Visualization, and Analysis of Spectral Data

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Amirkhanov, Artem

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Fröhler, Bernhard

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Kastner, Johann

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Gröller, Eduard

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Heinzl, Christoph

Volumetric Data Reduction in a Compressed Sensing Framework

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Xu, Xie

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Sakhaee, Elham

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Entezari, Alireza

Distortion-Guided Structure-Driven Interactive Exploration of High-Dimensional Data

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Liu, Shusen

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Wang, Bei

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Bremer, Peer-Timo

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Pascucci, Valerio

4D MRI Flow Coupled to Physics-Based Fluid Simulation for Blood-Flow Visualization

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Hoon, Niels de

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Pelt, Roy van

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Jalba, Andrei

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Vilanova, Anna

Illustrative Visualization of Molecular Reactions using Omniscient Intelligence and Passive Agents

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Muzic, Mathieu Le

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Parulek, Julius

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Stavrum, Anne Kristin

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Viola, Ivan

Comparative Blood Flow Visualization for Cerebral Aneurysm Treatment Assessment

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Pelt, Roy van

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Gasteiger, Rocco

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Lawonn, Kai

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Meuschke, Monique

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Preim, Bernhard

GuideME: Slice-guided Semiautomatic Multivariate Exploration of Volumes

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Zhou, Liang

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Hansen, Charles

Visualization of Medicine Prescription Behavior

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Corput, Paul van der

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Arends, Johan

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Wijk, Jarke J. van

Visualizing Validation of Protein Surface Classifiers

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Sarikaya, Alper

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Albers, Danielle

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Mitchell, Julie

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Gleicher, Michael

Line Integral Convolution for Real-Time Illustration of Molecular Surface Shape and Salient Regions

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Lawonn, Kai

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Krone, Michael

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Ertl, Thomas

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Preim, Bernhard

Comparative Visualization of Molecular Surfaces Using Deformable Models

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Scharnowski, Katrin

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Krone, Michael

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Reina, Guido

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Kulschewski, Tobias

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Pleiss, Jürgen

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Ertl, Thomas

Comparative Exploration of Document Collections: a Visual Analytics Approach

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Oelke, Daniela

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Strobelt, Hendrik

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Rohrdantz, Christian

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Gurevych, Iryna

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Deussen, Oliver

Networks of Names: Visual Exploration and Semi-Automatic Tagging of Social Networks from Newspaper Articles

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Kochtchi, Artjom

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Landesberger, Tatiana von

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Biemann, Chris

ConVis: A Visual Text Analytic System for Exploring Blog Conversations

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Hoque, Enamul

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Carenini, Giuseppe

Methods for Compensating Contrast Effects in Information Visualization

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Mittelstädt, Sebastian

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Stoffel, Andreas

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Keim, Daniel A.

A Gaze-enabled Graph Visualization to Improve Graph Reading Tasks

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Okoe, Mershack

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Alam, Sayeed Safayet

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Jianu, Radu

Visual Multiplexing

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Chen, Min

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Walton, Simon

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Berger, Kai

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Thiyagalingam, Jeyan

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Duffy, Brian

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Fang, Hui

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Holloway, Cameron

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Trefethen, Anne E.

Metro Transit-Centric Visualization for City Tour Planning

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Claudio, Pio

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Yoon, Sung-Eui

Visualizing Proximity-Based Spatiotemporal Behavior of Museum Visitors using Tangram Diagrams

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Lanir, Joel

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Bak, Peter

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Kuflik, Tsvi

Many Plans: Multidimensional Ensembles for Visual Decision Support in Flood Management

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Waser, Jürgen

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Konev, Artem

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Sadransky, Bernhard

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Horváth, Zsolt

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Ribicic, Hrvoje

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Carnecky, Robert

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Kluding, Patrick

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Schindler, Benjamin

Visual-interactive Exploration of Interesting Multivariate Relations in Mixed Research Data Sets

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Bernard, Jürgen

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Steiger, Martin

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Widmer, Sven

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Lücke-Tieke, Hendrik

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May, Thorsten

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Kohlhammer, Jörn

Visualizing Multidimensional Data with Glyph SPLOMs

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Yates, Andrew

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Webb, Allison

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Sharpnack, Michael

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Chamberlin, Helen

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Huang, Kun

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Machiraju, Raghu

Glyphs for Exploring Crowd-sourced Subjective Survey Classification

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Kachkaev, Alex

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Wood, Jo

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Dykes, Jason

Sparse Representation and Visualization for Direct Numerical Simulation of Premixed Combustion

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Oster, Timo

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Lehmann, Dirk J.

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Frau, Gordon

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Theisel, Holger

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Thévenin, Dominique

LoVis: Local Pattern Visualization for Model Refinement

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Zhao, Kaiyu

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Ward, Matthew O.

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Rundensteiner, Elke A.

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Higgins, Huong N.

SimilarityExplorer: A Visual Inter-Comparison Tool for Multifaceted Climate Data

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Poco, Jorge

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Dasgupta, Aritra

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Wei, Yaxing

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Hargrove, William

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Schwalm, Christopher

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Cook, Robert

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Bertini, Enrico

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Silva, Claudio

Lyra: An Interactive Visualization Design Environment

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Satyanarayan, Arvind

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Heer, Jeffrey

Authoring Narrative Visualizations with Ellipsis

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Satyanarayan, Arvind

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Heer, Jeffrey

Evaluating the Impact of User Characteristics and Different Layouts on an Interactive Visualization for Decision Making

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Conati, Cristina

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Carenini, Giuseppe

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Hoque, Enamul

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Steichen, Ben

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Toker, Dereck

Semi-Automatic Editing of Graphs with Customized Layouts

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Gladisch, Stefan

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Schumann, Heidrun

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Ernst, Mathias

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Füllen, Georg

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Tominski, Christian

Papilio: Visualizing Android Application Permissions

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Loorak, Mona Hosseinkhani

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Fong, Philip W. L.

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Carpendale, Sheelagh

Visual Analysis of Sets of Heterogeneous Matrices Using Projection-Based Distance Functions and Semantic Zoom

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Behrisch, Michael

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Davey, James

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Fischer, Fabian

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Thonnard, Olivier

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Schreck, Tobias

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Keim, Daniel

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Kohlhammer, Jörn

Visual Analysis of Time-Series Similarities for Anomaly Detection in Sensor Networks

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Steiger, Martin

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Bernard, Jürgen

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Mittelstädt, Sebastian

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Lücke-Tieke, Hendrik

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Keim, Daniel

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May, Thorsten

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Kohlhammer, Jörn

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Now showing 1 - 43 of 43

Preface and Table of Contents
(The Eurographics Association and Blackwell Publishing Ltd., 2014) H. Carr, P. Rheingans, and H. Schumann
Sets of Globally Optimal Stream Surfaces for Flow Visualization
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Schulze, Maik; Esturo, Janick Martinez; Günther, Tobias; Rössl, Christian; Seidel, Hans-Peter; Weinkauf, Tino; Theisel, Holger; H. Carr, P. Rheingans, and H. Schumann
Stream surfaces are a well-studied and widely used tool for the visualization of 3D flow fields. Usually, stream surface seeding is carried out manually in time-consuming trial and error procedures. Only recently automatic selection methods were proposed. Local methods support the selection of a set of stream surfaces, but, contrary to global selection methods, they evaluate only the quality of the seeding lines but not the quality of the whole stream surfaces. Global methods, on the other hand, only support the selection of a single optimal stream surface until now. However, for certain flow fields a single stream surface is not sufficient to represent all flow features. In our work, we overcome this limitation by introducing a global selection technique for a set of stream surfaces. All selected surfaces optimize global stream surface quality measures and are guaranteed to be mutually distant, such that they can convey different flow features. Our approach is an efficient extension of the most recent global selection method for single stream surfaces. We illustrate its effectiveness on a number of analytical and simulated flow fields and analyze the quality of the results in a user study.
Opacity Optimization for Surfaces
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Günther, Tobias; Schulze, Maik; Esturo, Janick Martinez; Rössl, Christian; Theisel, Holger; H. Carr, P. Rheingans, and H. Schumann
In flow visualization, integral surfaces rapidly tend to expand, fold and produce vast amounts of occlusion. While silhouette enhancements and local transparency mappings proved useful for semi-transparent depictions, they still introduce visual clutter when surfaces grow more complex. An effective visualization of the flow requires a balance between the presentation of interesting surface parts and the avoidance of occlusions that hinder the view. In this paper, we extend the concept of opacity optimization to surfaces to obtain a global approach to the occlusion problem. Starting with a partition of the surfaces into patches, we compute per-patch opacity as minimizer of a bounded-variable least-squares problem. For the final rendering, opacity is interpolated on the surfaces. The resulting visualization technique is interactive, frame-coherent, view-dependent and driven by domain knowledge.
Extracting Features from Time-Dependent Vector Fields Using Internal Reference Frames
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Bhatia, Harsh; Pascucci, Valerio; Kirby, Robert M.; Bremer, Peer-Timo; H. Carr, P. Rheingans, and H. Schumann
Extracting features from complex, time-dependent flow fields remains a significant challenge despite substantial research efforts, especially because most flow features of interest are defined with respect to a given reference frame. Pathline-based techniques, such as the FTLE field, are complex to implement and resource intensive, whereas scalar transforms, such as l2, often produce artifacts and require somewhat arbitrary thresholds. Both approaches aim to analyze the flow in a more suitable frame, yet neither technique explicitly constructs one. This paper introduces a new data-driven technique to compute internal reference frames for large-scale complex flows. More general than uniformly moving frames, these frames can transform unsteady fields, which otherwise require substantial processing of resources, into a sequence of individual snapshots that can be analyzed using the large body of steady-flow analysis techniques. Our approach is simple, theoretically well-founded, and uses an embarrassingly parallel algorithm for structured as well as unstructured data. Using several case studies from fluid flow and turbulent combustion, we demonstrate that internal frames are distinguished, result in temporally coherent structures, and can extract well-known as well as notoriously elusive features one snapshot at a time.
Mandatory Critical Points of 2D Uncertain Scalar Fields
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Günther, David; Salmon, Joseph; Tierny, Julien; H. Carr, P. Rheingans, and H. Schumann
This paper introduces a novel, non-local characterization of critical points and their global relation in 2D uncertain scalar fields. The characterization is based on the analysis of the support of the probability density functions (PDF) of the input data. Given two scalar fields representing reliable estimations of the bounds of this support, our strategy identifies mandatory critical points: spatial regions and function ranges where critical points have to occur in any realization of the input. The algorithm provides a global pairing scheme for mandatory critical points which is used to construct mandatory join and split trees. These trees enable a visual exploration of the common topological structure of all possible realizations of the uncertain data. To allow multi-scale visualization, we introduce a simplification scheme for mandatory critical point pairs revealing the most dominant features. Our technique is purely combinatorial and handles parametric distribution models and ensemble data. It does not depend on any computational parameter and does not suffer from numerical inaccuracy or global inconsistency. The algorithm exploits ideas of the established join/split tree computation. It is therefore simple to implement, and its complexity is output-sensitive. We illustrate, evaluate, and verify our method on synthetic and real-world data.
Extended Branch Decomposition Graphs: Structural Comparison of Scalar Data
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Saikia, Himangshu; Seidel, Hans-Peter; Weinkauf, Tino; H. Carr, P. Rheingans, and H. Schumann
We present a method to find repeating topological structures in scalar data sets. More precisely, we compare all subtrees of two merge trees against each other - in an efficient manner exploiting redundancy. This provides pair-wise distances between the topological structures defined by sub/superlevel sets, which can be exploited in several applications such as finding similar structures in the same data set, assessing periodic behavior in time-dependent data, and comparing the topology of two different data sets. To do so, we introduce a novel data structure called the extended branch decomposition graph, which is composed of the branch decompositions of all subtrees of the merge tree. Based on dynamic programming, we provide two highly efficient algorithms for computing and comparing extended branch decomposition graphs. Several applications attest to the utility of our method and its robustness against noise.
Stability of Dissipation Elements: A Case Study in Combustion
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Gyulassy, Attila; Bremer, Peer-Timo; Grout, Ray; Kolla, Hemanth; Chen, Jacqueline; Pascucci, Valerio; H. Carr, P. Rheingans, and H. Schumann
Recently, dissipation elements have been gaining popularity as a mechanism for measurement of fundamental properties of turbulent flow, such as turbulence length scales and zonal partitioning. Dissipation elements segment a domain according to the source and destination of streamlines in the gradient flow field of a scalar function f :M!R. They have traditionally been computed by numerically integrating streamlines from the center of each voxel in the positive and negative gradient directions, and grouping those voxels whose streamlines terminate at the same extremal pair. We show that the same structures map well to combinatorial topology concepts developed recently in the visualization community. Namely, dissipation elements correspond to sets of cells of the Morse- Smale complex. The topology-based formulation enables a more exploratory analysis of the nature of dissipation elements, in particular, in understanding their stability with respect to small scale variations. We present two examples from combustion science that raise significant questions about the role of small scale perturbation and indeed the definition of dissipation elements themselves.
Parallel Irradiance Caching for Interactive Monte-Carlo Direct Volume Rendering
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Khlebnikov, Rostislav; Voglreiter, Philip; Steinberger, Markus; Kainz, Bernhard; Schmalstieg, Dieter; H. Carr, P. Rheingans, and H. Schumann
We propose a technique to build the irradiance cache for isotropic scattering simultaneously with Monte Carlo progressive direct volume rendering on a single GPU, which allows us to achieve up to four times increased convergence rate for complex scenes with arbitrary sources of light. We use three procedures that run concurrently on a single GPU. The first is the main rendering procedure. The second procedure computes new cache entries, and the third one corrects the errors that may arise after creation of new cache entries. We propose two distinct approaches to allow massive parallelism of cache entry creation. In addition, we show a novel extrapolation approach which outputs high quality irradiance approximations and a suitable prioritization scheme to increase the convergence rate by dedicating more computational power to more complex rendering areas.
RBF Volume Ray Casting on Multicore and Manycore CPUs
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Knoll, Aaron; Wald, Ingo; Navratil, Paul; Bowen, Anne; Reda, Khairi; Papka, Mike E.; Gaither, Kelly; H. Carr, P. Rheingans, and H. Schumann
Modern supercomputers enable increasingly large N-body simulations using unstructured point data. The structures implied by these points can be reconstructed implicitly. Direct volume rendering of radial basis function (RBF) kernels in domain-space offers flexible classification and robust feature reconstruction, but achieving performant RBF volume rendering remains a challenge for existing methods on both CPUs and accelerators. In this paper, we present a fast CPU method for direct volume rendering of particle data with RBF kernels. We propose a novel two-pass algorithm: first sampling the RBF field using coherent bounding hierarchy traversal, then subsequently integrating samples along ray segments. Our approach performs interactively for a range of data sets from molecular dynamics and astrophysics up to 82 million particles. It does not rely on level of detail or subsampling, and offers better reconstruction quality than structured volume rendering of the same data, exhibiting comparable performance and requiring no additional preprocessing or memory footprint other than the BVH. Lastly, our technique enables multi-field, multi-material classification of particle data, providing better insight and analysis.
Towards an Unbiased Comparison of CC, BCC, and FCC Lattices in Terms of Prealiasing
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Vad, Viktor; Csébfalvi, Balázs; Rautek, Peter; Gröller, Eduard; H. Carr, P. Rheingans, and H. Schumann
In the literature on optimal regular volume sampling, the Body-Centered Cubic (BCC) lattice has been proven to be optimal for sampling spherically band-limited signals above the Nyquist limit. On the other hand, if the sampling frequency is below the Nyquist limit, the Face-Centered Cubic (FCC) lattice was demonstrated to be optimal in reducing the prealiasing effect. In this paper, we confirm that the FCC lattice is indeed optimal in this sense in a certain interval of the sampling frequency. By theoretically estimating the prealiasing error in a realistic range of the sampling frequency, we show that in other frequency intervals, the BCC lattice and even the traditional Cartesian Cubic (CC) lattice are expected to minimize the prealiasing. The BCC lattice is superior over the FCC lattice if the sampling frequency is not significantly below the Nyquist limit. Interestingly, if the original signal is drastically undersampled, the CC lattice is expected to provide the lowest prealiasing error. Additionally, we give a comprehensible clarification that the sampling efficiency of the FCC lattice is lower than that of the BCC lattice. Although this is a well-known fact, the exact percentage has been erroneously reported in the literature. Furthermore, for the sake of an unbiased comparison, we propose to rotate the Marschner-Lobb test signal such that an undue advantage is not given to either lattice
InSpectr: Multi-Modal Exploration, Visualization, and Analysis of Spectral Data
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Amirkhanov, Artem; Fröhler, Bernhard; Kastner, Johann; Gröller, Eduard; Heinzl, Christoph; H. Carr, P. Rheingans, and H. Schumann
This paper addresses the increasing demand in industry for methods to analyze and visualize multimodal data involving a spectral modality. Two data modalities are used: high-resolution X-ray computed tomography (XCT) for structural characterization and low-resolution X-ray fluorescence (XRF) spectral data for elemental decomposition. We present InSpectr, an integrated tool for the interactive exploration and visual analysis of multimodal, multiscalar data. The tool has been designed around a set of tasks identified by domain experts in the fields of XCT and XRF. It supports registered single scalar and spectral datasets optionally coupled with element maps and reference spectra. InSpectr is instantiating various linked views for the integration of spatial and non-spatial information to provide insight into an industrial component's structural and material composition: views with volume renderings of composite and individual 3D element maps visualize global material composition; transfer functions defined directly on the spectral data and overlaid pie-chart glyphs show elemental composition in 2D slice-views; a representative aggregated spectrum and spectra density histograms are introduced to provide a global overview in the spectral view. Spectral magic lenses, spectrum probing and elemental composition probing of points using a pie-chart view and a periodic table view aid the local material composition analysis. Two datasets are investigated to outline the usefulness of the presented techniques: a 3D virtually created phantom with a brass metal alloy and a real-world 2D water phantom with insertions of gold, barium, and gadolinium. Additionally a detailed user evaluation of the results is provided
Volumetric Data Reduction in a Compressed Sensing Framework
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Xu, Xie; Sakhaee, Elham; Entezari, Alireza; H. Carr, P. Rheingans, and H. Schumann
In this paper, we investigate compressed sensing principles to devise an in-situ data reduction framework for visualization of volumetric datasets. We exploit the universality of the compressed sensing framework and show that the proposed method offers a refinable data reduction approach for volumetric datasets. The accurate reconstruction is obtained from partial Fourier measurements of the original data that are sensed without any prior knowledge of specific feature domains for the data. Our experiments demonstrate the superiority of surfacelets for efficient representation of volumetric data. Moreover, we establish that the accuracy of reconstruction can further improve once a more effective basis for a sparser representation of the data becomes available.
Distortion-Guided Structure-Driven Interactive Exploration of High-Dimensional Data
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Liu, Shusen; Wang, Bei; Bremer, Peer-Timo; Pascucci, Valerio; H. Carr, P. Rheingans, and H. Schumann
Dimension reduction techniques are essential for feature selection and feature extraction of complex highdimensional data. These techniques, which construct low-dimensional representations of data, are typically geometrically motivated, computationally efficient and approximately preserve certain structural properties of the data. However, they are often used as black box solutions in data exploration and their results can be difficult to interpret. To assess the quality of these results, quality measures, such as co-ranking [LV09], have been proposed to quantify structural distortions that occur between high-dimensional and low-dimensional data representations. Such measures could be evaluated and visualized point-wise to further highlight erroneous regions [MLGH13]. In this work, we provide an interactive visualization framework for exploring high-dimensional data via its twodimensional embeddings obtained from dimension reduction, using a rich set of user interactions. We ask the following question: what new insights do we obtain regarding the structure of the data, with interactive manipulations of its embeddings in the visual space? We augment the two-dimensional embeddings with structural abstractions obtained from hierarchical clusterings, to help users navigate and manipulate subsets of the data. We use point-wise distortion measures to highlight interesting regions in the domain, and further to guide our selection of the appropriate level of clusterings that are aligned with the regions of interest. Under the static setting, point-wise distortions indicate the level of structural uncertainty within the embeddings. Under the dynamic setting, on-thefly updates of point-wise distortions due to data movement and data deletion reflect structural relations among different parts of the data, which may lead to new and valuable insights.
4D MRI Flow Coupled to Physics-Based Fluid Simulation for Blood-Flow Visualization
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Hoon, Niels de; Pelt, Roy van; Jalba, Andrei; Vilanova, Anna; H. Carr, P. Rheingans, and H. Schumann
Modern MRI measurements deliver volumetric and time-varying blood-flow data of unprecedented quality. Visual analysis of these data potentially leads to a better diagnosis and risk assessment of various cardiovascular diseases. Recent advances have improved the speed and quality of the imaging data considerably. Nevertheless, the data remains compromised by noise and a lack of spatiotemporal resolution. Besides imaging data, also numerical simulations are employed. These are based on mathematical models of specific features of physical reality. However, these models require realistic parameters and boundary conditions based on measurements. We propose to use data assimilation to bring measured data and physically-based simulation together, and to harness the mutual benefits. The accuracy and noise robustness of the coupled approach is validated using an analytic flow field. Furthermore, we present a comparative visualization that conveys the differences between using conventional interpolation and our coupled approach.
Illustrative Visualization of Molecular Reactions using Omniscient Intelligence and Passive Agents
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Muzic, Mathieu Le; Parulek, Julius; Stavrum, Anne Kristin; Viola, Ivan; H. Carr, P. Rheingans, and H. Schumann
In this paper we propose a new type of a particle systems, tailored for illustrative visualization purposes, in particular for visualizing molecular reactions in biological networks. Previous visualizations of biochemical processes were exploiting the results of agent-based modeling. Such modeling aims at reproducing accurately the stochastic nature of molecular interactions. However, it is impossible to expect events of interest happening at a certain time and location, which is impractical for storytelling. To obtain the means of controlling molecular interactions, we propose to govern passive agents with an omniscient intelligence, instead of giving to the agents the freedom of initiating reaction autonomously. This makes it possible to generate illustrative animated stories that communicate the functioning of the molecular machinery. The rendering performance delivers for interactive framerates of massive amounts of data, based on the dynamic tessellation capabilities of modern graphics cards. Finally, we report an informal expert feedback we obtained from the potential users.
Comparative Blood Flow Visualization for Cerebral Aneurysm Treatment Assessment
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Pelt, Roy van; Gasteiger, Rocco; Lawonn, Kai; Meuschke, Monique; Preim, Bernhard; H. Carr, P. Rheingans, and H. Schumann
A pathological vessel dilation in the brain, termed cerebral aneurysm, bears a high risk of rupture, and is associated with a high mortality. In recent years, incidental findings of unruptured aneurysms have become more frequent, mainly due to advances in medical imaging. The pathological condition is often treated with a stent that diverts the blood flow from the aneurysm sac back to the original vessel. Prior to treatment, neuroradiologists need to decide on the optimal stent configuration and judge the long-term rupture risk, for which blood flow information is essential. Modern patient-specific simulations can model the hemodynamics for various stent configurations, providing important indicators to support the decision-making process. However, the necessary visual analysis of these data becomes tedious and time-consuming, because of the abundance of information. We introduce a comprehensive comparative visualization that integrates morphology with blood flow indicators to facilitate treatment assessment. To deal with the visual complexity, we propose a details-on-demand approach, combining established medical visualization techniques with innovative glyphs inspired by information visualization concepts. In an evaluation we have obtained informal feedback from domain experts, gauging the value of our visualization.
GuideME: Slice-guided Semiautomatic Multivariate Exploration of Volumes
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Zhou, Liang; Hansen, Charles; H. Carr, P. Rheingans, and H. Schumann
Multivariate volume visualization is important for many applications including petroleum exploration and medicine. State-of-the-art tools allow users to interactively explore volumes with multiple linked parameter-space views. However, interactions in the parameter space using trial-and-error may be unintuitive and time consuming. Furthermore, switching between different views may be distracting. In this paper, we propose GuideME: a novel slice-guided semiautomatic multivariate volume exploration approach. Specifically, the approach comprises four stages: attribute inspection, guided uncertainty-aware lasso creation, automated feature extraction and optional spatial fine tuning and visualization. Throughout the exploration process, the user does not need to interact with the parameter views at all and examples of complex real-world data demonstrate the usefulness, efficiency and ease-of-use of our method.
Visualization of Medicine Prescription Behavior
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Corput, Paul van der; Arends, Johan; Wijk, Jarke J. van; H. Carr, P. Rheingans, and H. Schumann
Medicine prescriptions play an important role in medical treatments. More insight in medicine prescription behavior can lead to more efficient and effective treatments, as well as reflection on prescription behavior for specific physicians, types of medicines, or classes of patients. Most current medical visualization systems show health data only from the perspective of patients, whereas to understand prescription behavior multiple perspectives are relevant. We present a new approach to visualize prescription data from four different perspectives: physician, patient, medicine, and prescription. Information about physicians, patients, and medicines is shown in three tables; relations between selected items in these tables are shown using custom glyphs and histograms. These tables can also be used to define selections of prescriptions which can be compared to each other by showing a variety of metrics. This enables physicians and possibly other stakeholders to perform a wide variety of queries and inspections, while the use of familiar metaphors, such as tables and histograms, enables them to use the system in short time. This was confirmed by an evaluation session with six neurologists from an institute of epileptology. Our system is tailored to medicine prescription data, but we argue that the underlying pattern in the data is ubiquitous, and that hence our approach can be useful for many other cases where A provides B to C.
Visualizing Validation of Protein Surface Classifiers
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Sarikaya, Alper; Albers, Danielle; Mitchell, Julie; Gleicher, Michael; H. Carr, P. Rheingans, and H. Schumann
Many bioinformatics applications construct classifiers that are validated in experiments that compare their results to known ground truth over a corpus. In this paper, we introduce an approach for exploring the results of such classifier validation experiments, focusing on classifiers for regions of molecular surfaces. We provide a tool that allows for examining classification performance patterns over a test corpus. The approach combines a summary view that provides information about an entire corpus of molecules with a detail view that visualizes classifier results directly on protein surfaces. Rather than displaying miniature 3D views of each molecule, the summary provides 2D glyphs of each protein surface arranged in a reorderable, small-multiples grid. Each summary is specifically designed to support visual aggregation to allow the viewer to both get a sense of aggregate properties as well as the details that form them. The detail view provides a 3D visualization of each protein surface coupled with interaction techniques designed to support key tasks, including spatial aggregation and automated camera touring. A prototype implementation of our approach is demonstrated on protein surface classifier experiments.
Line Integral Convolution for Real-Time Illustration of Molecular Surface Shape and Salient Regions
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Lawonn, Kai; Krone, Michael; Ertl, Thomas; Preim, Bernhard; H. Carr, P. Rheingans, and H. Schumann
We present a novel line drawing algorithm that illustrates surfaces in real-time to convey their shape. We use line integral convolution (LIC) and employ ambient occlusion for illustrative surface rendering. Furthermore, our method depicts salient regions based on the illumination gradient. Our method works on animated surfaces in a frame-coherent manner. Therefore, it yields an illustrative representation of time-dependent surfaces as no preprocessing step is needed. In this paper, the method is used to highlight the structure of molecular surfaces and to illustrate important surface features like cavities, channels, and pockets. The benefit of our method was evaluated with domain experts. We also demonstrate the applicability of our method to medical visualization.
Comparative Visualization of Molecular Surfaces Using Deformable Models
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Scharnowski, Katrin; Krone, Michael; Reina, Guido; Kulschewski, Tobias; Pleiss, Jürgen; Ertl, Thomas; H. Carr, P. Rheingans, and H. Schumann
The comparison of molecular surface attributes is of interest for computer aided drug design and the analysis of biochemical simulations. Due to the non-rigid nature of molecular surfaces, partial shape matching is feasible for mapping two surfaces onto each other. We present a novel technique to obtain a mapping relation between two surfaces using a deformable model approach. This relation is used for pair-wise comparison of local surface attributes (e.g. electrostatic potential). We combine the difference value as well as the comparability as derived from the local matching quality in a 3D molecular visualization by mapping them to color. A 2D matrix shows the global dissimilarity in an overview of different data sets in an ensemble. We apply our visualizations to simulation results provided by collaborators from the field of biochemistry to evaluate the effectiveness of our results.
Comparative Exploration of Document Collections: a Visual Analytics Approach
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Oelke, Daniela; Strobelt, Hendrik; Rohrdantz, Christian; Gurevych, Iryna; Deussen, Oliver; H. Carr, P. Rheingans, and H. Schumann
We present an analysis and visualization method for computing what distinguishes a given document collection from others. We determine topics that discriminate a subset of collections from the remaining ones by applying probabilistic topic modeling and subsequently approximating the two relevant criteria distinctiveness and characteristicness algorithmically through a set of heuristics. Furthermore, we suggest a novel visualization method called DiTop-View, in which topics are represented by glyphs (topic coins) that are arranged on a 2D plane. Topic coins are designed to encode all information necessary for performing comparative analyses such as the class membership of a topic, its most probable terms and the discriminative relations. We evaluate our topic analysis using statistical measures and a small user experiment and present an expert case study with researchers from political sciences analyzing two real-world datasets.
Networks of Names: Visual Exploration and Semi-Automatic Tagging of Social Networks from Newspaper Articles
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Kochtchi, Artjom; Landesberger, Tatiana von; Biemann, Chris; H. Carr, P. Rheingans, and H. Schumann
Understanding relationships between people and organizations by reading newspaper articles is difficult to manage for humans due to the large amount of data. To address this problem, we present and evaluate a new visual analytics system, which offers interactive exploration and tagging of social networks extracted from newspapers. For the visual exploration of the network, we extract ''interesting'' neighbourhoods of nodes, using a new degree of interest (DOI) measure based on edges instead of nodes. It improves the seminal definition of DOI, which we find to produce the same ''globally interesting'' neighbourhoods in our use case, regardless of the query. Our approach allows answering different user queries appropriately, avoiding uniform search results. We propose a user-driven pattern-based classifier for discovery and tagging of non-taxonomic semantic relations. Our approach does not require any a-priori user knowledge, such as expertise in syntax or pattern creation. An evaluation shows that our classifier is capable of identifying known lexico-syntactic patterns as well as various domain-specific patters. Our classifier yields good results already with a small amount of training, and continuously improves through user feedback. We conduct a user study to evaluate whether our visual interactive system has an impact on how users tag relationships, as compared to traditional text-based interfaces. Study results suggest that users of the visual system tend to tag more concisely, avoiding too abstract or overly specific relationship labels.
ConVis: A Visual Text Analytic System for Exploring Blog Conversations
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Hoque, Enamul; Carenini, Giuseppe; H. Carr, P. Rheingans, and H. Schumann
Today it is quite common for people to exchange hundreds of comments in online conversations (e.g., blogs). Often, it can be very difficult to analyze and gain insights from such long conversations. To address this problem, we present a visual text analytic system that tightly integrates interactive visualization with novel text mining and summarization techniques to fulfill information needs of users in exploring conversations. At first, we perform a user requirement analysis for the domain of blog conversations to derive a set of design principles. Following these principles, we present an interface that visualizes a combination of various metadata and textual analysis results, supporting the user to interactively explore the blog conversations. We conclude with an informal user evaluation, which provides anecdotal evidence about the effectiveness of our system and directions for further design.
Methods for Compensating Contrast Effects in Information Visualization
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Mittelstädt, Sebastian; Stoffel, Andreas; Keim, Daniel A.; H. Carr, P. Rheingans, and H. Schumann
Color, as one of the most effective visual variables, is used in many techniques to encode and group data points according to different features. Relations between features and groups appear as visual patterns in the visualization. However, optical illusions may bias the perception at the first level of the analysis process. For instance, in pixel-based visualizations contrast effects make pixels appear brighter if surrounded by a darker area, which distorts the encoded metric quantity of the data points. Even if we are aware of these perceptual issues, our visual cognition system is not able to compensate these effects accurately. To overcome this limitation, we present a color optimization algorithm based on perceptual metrics and color perception models to reduce physiological contrast or color effects. We evaluate our technique with a user study and find that the technique doubles the accuracy of users comparing and estimating color encoded data values. Since the presented technique can be used in any application without adaption to the visualization itself, we are able to demonstrate its effectiveness on data visualizations in different domains.
A Gaze-enabled Graph Visualization to Improve Graph Reading Tasks
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Okoe, Mershack; Alam, Sayeed Safayet; Jianu, Radu; H. Carr, P. Rheingans, and H. Schumann
Performing typical network tasks such as node scanning and path tracing can be difficult in large and dense graphs. To alleviate this problem we use eye-tracking as an interactive input to detect tasks that users intend to perform and then produce unobtrusive visual changes that support these tasks. First, we introduce a novel fovea based filtering that dims out edges with endpoints far removed from a user's view focus. Second, we highlight edges that are being traced at any given moment or have been the focus of recent attention. Third, we track recently viewed nodes and increase the saliency of their neighborhoods. All visual responses are unobtrusive and easily ignored to avoid unintentional distraction and to account for the imprecise and low-resolution nature of eyetracking. We also introduce a novel gaze-correction approach that relies on knowledge about the network layout to reduce eye-tracking error. Finally, we present results from a controlled user study showing that our methods led to a statistically significant accuracy improvement in one of two network tasks and that our gaze-correction algorithm enables more accurate eye-tracking interaction.
Visual Multiplexing
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Chen, Min; Walton, Simon; Berger, Kai; Thiyagalingam, Jeyan; Duffy, Brian; Fang, Hui; Holloway, Cameron; Trefethen, Anne E.; H. Carr, P. Rheingans, and H. Schumann
The majority of display devices used in visualization are 2D displays. Inevitably, it is often necessary to overlay one piece of visual information on top of another, especially in applications such as multi-field visualization and geospatial information visualization. In this paper, we present a conceptual framework for studying the mechanisms for overlaying multiple pieces of visual information while allowing users to recover occluded information. We adopt the term 'multiplexing' from tele- and data communication to encompass all such overlapping mechanisms. We establish 10 categories of visual multiplexing mechanisms. We draw support evidence from both perception literature and existing works in visualization to support this conceptual framework. We examine the relationships between multiplexing and information theoretic measures. This new conceptual categorization provides the muchneeded theory of visualization with an integral component.
Metro Transit-Centric Visualization for City Tour Planning
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Claudio, Pio; Yoon, Sung-Eui; H. Carr, P. Rheingans, and H. Schumann
In general, city trip planning consists of two main steps: knowing Points-Of-Interest (POIs), and then planning a tour route from the current point to next preferred POIs. We mainly consider the metro for traveling around touristic cities as the main means of transportation. In this context, existing tools lack a capability to effectively visualize POIs on the metro map for trip planning. To bridge this gap, we propose an interactive framework that holistically combines presentations of POIs and a metro network. Our idea is to identify popular POIs based on visual worth computation, and to introduce POI discovery for effectively identifying POIs within reach of a metro network for users.We use octilinear layouts to highlight the metro network, and show representative POI images in the layout space visualized within a user-specified viewing window. We have implemented our working prototype showing touristic cities with a metro network. We have factored out various design guidelines that are basis for designing our method, and validated our approach with a user study surveying 70 individuals.
Visualizing Proximity-Based Spatiotemporal Behavior of Museum Visitors using Tangram Diagrams
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Lanir, Joel; Bak, Peter; Kuflik, Tsvi; H. Carr, P. Rheingans, and H. Schumann
For museum curators it is imperative to learn, analyze, and understand the behavior patterns of the visitors in their museum. Recent developments in the field of indoor positioning systems make the acquisition and availability of visitor behavior data more attainable. However, the analysis of such data remains a challenge due to its noisiness, complexity and sheer size. The current paper applies information visualization techniques to analyze this data and make it more accessible to museum curators and personnel. We first provide a detailed description of the application domain including an analysis of the curators' information needs and a description of how a dataset on visitors' spatiotemporal behavior could be acquired. In order to address the curators' needs, we designed a visualization to encode and convey the information based on a newly adjusted visual glyph that we call Tangram Diagrams. We thereby focus on the adaptability of the technique to a particular domain, rather than on the novelty aspects of the technique itself. We have evaluated our design decisions empirically, and conducted an expert study to describe the insights gained and the value of the information obtained from the visualization. The contribution of this work is twofold. First, we apply information visualization to the museum domain and discuss how it extends to general indoor spatiotemporal behavior analysis. Second, we show how a visual glyph metaphor can be applied in different ways and contexts to efficiently encode multi-faceted information.
Many Plans: Multidimensional Ensembles for Visual Decision Support in Flood Management
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Waser, Jürgen; Konev, Artem; Sadransky, Bernhard; Horváth, Zsolt; Ribicic, Hrvoje; Carnecky, Robert; Kluding, Patrick; Schindler, Benjamin; H. Carr, P. Rheingans, and H. Schumann
Uncertainties in flood predictions complicate the planning of mitigation measures. There is a consensus that many possible incident scenarios should be considered. For each scenario, a specific response plan should be prepared which is optimal with respect to criteria such as protection, costs, or realization time. None of the existing software tools is capable of creating large scenario pools, nor do they provide means for quick exploration and assessment of the associated plans. In this paper, we present an integrated solution that is based on multidimensional, timedependent ensemble simulations of incident scenarios and protective measures. We provide scalable interfaces which facilitate and accelerate setting up multiple time-varying parameters for generating a pool of pre-cooked scenarios. In case of an emergency, disaster managers can quickly extract relevant information from the pool to deal with the situation at hand. An interactive 3D-view conveys details about how a response plan has to be executed. Linked information visualization and ranking views allow for a quick assessment of many plans. In collaboration with flood managers, we demonstrate the practical applicability of our solution. We tackle the challenges of planning mobile water barriers for protecting important infrastructure. We account for real-world limitations of available resources and handle the involved logistics problems.
Visual-interactive Exploration of Interesting Multivariate Relations in Mixed Research Data Sets
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Bernard, Jürgen; Steiger, Martin; Widmer, Sven; Lücke-Tieke, Hendrik; May, Thorsten; Kohlhammer, Jörn; H. Carr, P. Rheingans, and H. Schumann
The analysis of research data plays a key role in data-driven areas of science. Varieties of mixed research data sets exist and scientists aim to derive or validate hypotheses to find undiscovered knowledge. Many analysis techniques identify relations of an entire dataset only. This may level the characteristic behavior of different subgroups in the data. Like automatic subspace clustering, we aim at identifying interesting subgroups and attribute sets. We present a visual-interactive system that supports scientists to explore interesting relations between aggregated bins of multivariate attributes in mixed data sets. The abstraction of data to bins enables the application of statistical dependency tests as the measure of interestingness. An overview matrix view shows all attributes, ranked with respect to the interestingness of bins. Complementary, a node-link view reveals multivariate bin relations by positioning dependent bins close to each other. The system supports information drill-down based on both expert knowledge and algorithmic support. Finally, visual-interactive subset clustering assigns multivariate bin relations to groups. A list-based cluster result representation enables the scientist to communicate multivariate findings at a glance. We demonstrate the applicability of the system with two case studies from the earth observation domain and the prostate cancer research domain. In both cases, the system enabled us to identify the most interesting multivariate bin relations, to validate already published results, and, moreover, to discover unexpected relations.
Visualizing Multidimensional Data with Glyph SPLOMs
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Yates, Andrew; Webb, Allison; Sharpnack, Michael; Chamberlin, Helen; Huang, Kun; Machiraju, Raghu; H. Carr, P. Rheingans, and H. Schumann
Scatterplot matrices or SPLOMs provide a feasible method of visualizing and representing multi-dimensional data especially for a small number of dimensions. For very high dimensional data, we introduce a novel technique to summarize a SPLOM, as a clustered matrix of glyphs, or a Glyph SPLOM. Each glyph visually encodes a general measure of dependency strength, distance correlation, and a logical dependency class based on the occupancy of the scatterplot quadrants. We present the Glyph SPLOM as a general alternative to the traditional correlation based heatmap and the scatterplot matrix in two examples: demography data from the World Health Organization (WHO), and gene expression data from developmental biology. By using both, dependency class and strength, the Glyph SPLOM illustrates high dimensional data in more detail than a heatmap but with more summarization than a SPLOM. More importantly, the summarization capabilities of Glyph SPLOM allow for the assertion of ''necessity'' causal relationships in the data and the reconstruction of interaction networks in various dynamic systems.
Glyphs for Exploring Crowd-sourced Subjective Survey Classification
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Kachkaev, Alex; Wood, Jo; Dykes, Jason; H. Carr, P. Rheingans, and H. Schumann
The findings drawn from opinion survey responses are usually made by producing summary charts or conducting statistical analysis. Both involve data aggregation and filtering as exploring the unaggregated data has traditionally been impractical or error-prone for large numbers of responses. We propose the use of glyphs with parallel coordinate plots to show all survey responses in a single view and design an interactive visual analytics tool around the representation to explore the data. We use this software for a 'photo content assessment' survey, where 359 participants classify 900 images by seven criteria. The proposed approach allows all 8,434 responses (49,285 answers to questions in total) to be represented in a single view and helps analysts to both clean the data and understand the nature of the survey responses. We describe the construction of the survey response glyphs and the interface to the interactive visual analytics software and generalise the design principles that arise from the approach. We apply the tool to two other datasets to evaluate the technique and to confirm its wider applicability for surveys with Likert scale responses.
Sparse Representation and Visualization for Direct Numerical Simulation of Premixed Combustion
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Oster, Timo; Lehmann, Dirk J.; Frau, Gordon; Theisel, Holger; Thévenin, Dominique; H. Carr, P. Rheingans, and H. Schumann
Direct Numerical Simulations of premixed combustion produce terabytes of raw data, which are prohibitively large to be stored, and have to be analyzed and visualized. A simultaneous and integrated treatment of data storage, data analysis and data visualization is required. For this, we introduce a sparse representation tailored to DNS data which can directly be used for both analysis and visualization. The method is based on the observation that most information is located in narrow-band regions where the chemical reactions take place, but these regions are not well defined. An approach for the visual investigation of feature surfaces of the scalar fields involved in the simulation is shown as a possible application. We demonstrate our approach on multiple real datasets.
LoVis: Local Pattern Visualization for Model Refinement
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Zhao, Kaiyu; Ward, Matthew O.; Rundensteiner, Elke A.; Higgins, Huong N.; H. Carr, P. Rheingans, and H. Schumann
Linear models are commonly used to identify trends in data. While it is an easy task to build linear models using pre-selected variables, it is challenging to select the best variables from a large number of alternatives. Most metrics for selecting variables are global in nature, and thus not useful for identifying local patterns. In this work, we present an integrated framework with visual representations that allows the user to incrementally build and verify models in three model spaces that support local pattern discovery and summarization: model complementarity, model diversity, and model representivity. Visual representations are designed and implemented for each of the model spaces. Our visualizations enable the discovery of complementary variables, i.e., those that perform well in modeling different subsets of data points. They also support the isolation of local models based on a diversity measure. Furthermore, the system integrates a hierarchical representation to identify the outlier local trends and the local trends that share similar directions in the model space. A case study on financial risk analysis is discussed, followed by a user study.
SimilarityExplorer: A Visual Inter-Comparison Tool for Multifaceted Climate Data
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Poco, Jorge; Dasgupta, Aritra; Wei, Yaxing; Hargrove, William; Schwalm, Christopher; Cook, Robert; Bertini, Enrico; Silva, Claudio; H. Carr, P. Rheingans, and H. Schumann
Inter-comparison and similarity analysis to gauge consensus among multiple simulation models is a critical visualization problem for understanding climate change patterns. Climate models, specifically, Terrestrial Biosphere Models (TBM) represent time and space variable ecosystem processes, like, simulations of photosynthesis and respiration, using algorithms and driving variables such as climate and land use. While it is widely accepted that interactive visualization can enable scientists to better explore model similarity from different perspectives and different granularity of space and time, currently there is a lack of such visualization tools. In this paper we present three main contributions. First, we propose a domain characterization for the TBM community by systematically defining the domain-specific intents for analyzing model similarity and characterizing the different facets of the data. Second, we define a classification scheme for combining visualization tasks and multiple facets of climate model data in one integrated framework, which can be leveraged for translating the tasks into the visualization design. Finally, we present SimilarityExplorer, an exploratory visualization tool that facilitates similarity comparison tasks across both space and time through a set of coordinated multiple views. We present two case studies from three climate scientists, who used our tool for a month for gaining scientific insights into model similarity. Their experience and results validate the effectiveness of our tool.
Lyra: An Interactive Visualization Design Environment
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Satyanarayan, Arvind; Heer, Jeffrey; H. Carr, P. Rheingans, and H. Schumann
We present Lyra, an interactive environment for designing customized visualizations without writing code. Using drag-and-drop interactions, designers can bind data to the properties of graphical marks to author expressive visualization designs. Marks can be moved, rotated and resized using handles; relatively positioned using connectors; and parameterized by data fields using property drop zones. Lyra also provides a data pipeline interface for iterative, visual specification of data transformations and layout algorithms. Visualizations created with Lyra are represented as specifications in Vega, a declarative visualization grammar that enables sharing and reuse. We evaluate Lyra's expressivity and accessibility through diverse examples and studies with journalists and visualization designers. We find that Lyra enables users to rapidly develop customized visualizations, covering a design space comparable to existing programming-based tools.
Authoring Narrative Visualizations with Ellipsis
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Satyanarayan, Arvind; Heer, Jeffrey; H. Carr, P. Rheingans, and H. Schumann
Data visualization is now a popular medium for journalistic storytelling. However, current visualization tools either lack support for storytelling or require significant technical expertise. Informed by interviews with journalists, we introduce a model of storytelling abstractions that includes state-based scene structure, dynamic annotations and decoupled coordination of multiple visualization components. We instantiate our model in Ellipsis: a system that combines a domain-specific language (DSL) for storytelling with a graphical interface for story authoring. User interactions are automatically translated into statements in the Ellipsis DSL. By enabling storytelling without programming, the Ellipsis interface lowers the threshold for authoring narrative visualizations. We evaluate Ellipsis through example applications and user studies with award-winning journalists. Study participants find Ellipsis to be a valuable prototyping tool that can empower journalists in the creation of interactive narratives.
Evaluating the Impact of User Characteristics and Different Layouts on an Interactive Visualization for Decision Making
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Conati, Cristina; Carenini, Giuseppe; Hoque, Enamul; Steichen, Ben; Toker, Dereck; H. Carr, P. Rheingans, and H. Schumann
There is increasing evidence that user characteristics can have a significant impact on visualization effectiveness, suggesting that visualizations could be designed to better fit each user's specific needs. Most studies to date, how-ever, have looked at static visualizations. Studies considering interactive visualizations have only looked at a li-mited number of user characteristics, and consider either low-level tasks (e.g., value retrieval), or high-level tasks (in particular: discovery), but not both. This paper contributes to this line of work by looking at the impact of a large set of user characteristics on user performance with interactive visualizations, for both low and high-level tasks. We focus on interactive visualizations that support decision making, exemplified by a visualization known as Value Charts. We include in the study two versions of ValueCharts that differ in terms of layout, to ascertain whether layout mediates the impact of individual differences and could be considered as a form of personalization. Our key findings are that (i) performance with low and high-level tasks is affected by different user characteristics, and (ii) users with low visual working memory perform better with a horizontal layout. We discuss how these find-ings can inform the provision of personalized support to visualization processing.
Semi-Automatic Editing of Graphs with Customized Layouts
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Gladisch, Stefan; Schumann, Heidrun; Ernst, Mathias; Füllen, Georg; Tominski, Christian; H. Carr, P. Rheingans, and H. Schumann
Usually visualization is applied to gain insight into data. Yet consuming the data in form of visual representation is not always enough. Instead, users need to edit the data, preferably through the same means used to visualize them. In this work, we present a semi-automatic approach to visual editing of graphs. The key idea is to use an interactive EditLens that defines where an edit operation affects an already customized and established graph layout. Locally optimal node positions within the lens and edge routes to connected nodes are calculated according to different criteria. This spares the user much manual work, but still provides sufficient freedom to accommodate applicationdependent layout constraints. Our approach utilizes the advantages of multi-touch gestures, and is also compatible with classic mouse and keyboard interaction. Preliminary user tests have been conducted with researchers from bio-informatics who need to manually maintain a slowly, but constantly growing molecular network. As the user feedback indicates, our solution significantly improves the editing procedure applied so far.
Papilio: Visualizing Android Application Permissions
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Loorak, Mona Hosseinkhani; Fong, Philip W. L.; Carpendale, Sheelagh; H. Carr, P. Rheingans, and H. Schumann
We introduce Papilio, a new visualization technique for visualizing permissions of real-world Android applications. We explore the development of layouts that exploit the directed acyclic nature of Android application permission data to develop a new explicit layout technique that incorporates aspects of set membership, node-link diagrams and matrix layouts. By grouping applications based on sets of requested permissions, a structure can be formed with partially ordered relations. The Papilio layout shows sets of applications centrally, the relations among applications on one side and application permissions, as the reason behind the existence of the partial order, on the other side. Using Papilio to explore a set of Android applications as a case study has led to new security findings regarding permission usage by Android applications
Visual Analysis of Sets of Heterogeneous Matrices Using Projection-Based Distance Functions and Semantic Zoom
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Behrisch, Michael; Davey, James; Fischer, Fabian; Thonnard, Olivier; Schreck, Tobias; Keim, Daniel; Kohlhammer, Jörn; H. Carr, P. Rheingans, and H. Schumann
Matrix visualization is an established technique in the analysis of relational data. It is applicable to large, dense networks, where node-link representations may not be effective. Recently, domains have emerged in which the comparative analysis of sets of matrices of potentially varying size is relevant. For example, to monitor computer network traffic a dynamic set of hosts and their peer-to-peer connections on different ports must be analysed. A matrix visualization focused on the display of one matrix at a time cannot cope with this task. We address the research problem of the visual analysis of sets of matrices. We present a technique for comparing matrices of potentially varying size. Our approach considers the rows and/or columns of a matrix as the basic elements of the analysis. We project these vectors for pairs of matrices into a low-dimensional space which is used as the reference to compare matrices and identify relationships among them. Bipartite graph matching is applied on the projected elements to compute a measure of distance. A key advantage of this measure is that it can be interpreted and manipulated as a visual distance function, and serves as a comprehensible basis for ranking, clustering and comparison in sets of matrices. We present an interactive system in which users may explore the matrix distances and understand potential differences in a set of matrices. A flexible semantic zoom mechanism enables users to navigate through sets of matrices and identify patterns at different levels of detail. We demonstrate the effectiveness of our approach through a case study and provide a technical evaluation to illustrate its strengths.
Visual Analysis of Time-Series Similarities for Anomaly Detection in Sensor Networks
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Steiger, Martin; Bernard, Jürgen; Mittelstädt, Sebastian; Lücke-Tieke, Hendrik; Keim, Daniel; May, Thorsten; Kohlhammer, Jörn; H. Carr, P. Rheingans, and H. Schumann
We present a system to analyze time-series data in sensor networks. Our approach supports exploratory tasks for the comparison of univariate, geo-referenced sensor data, in particular for anomaly detection. We split the recordings into fixed-length patterns and show them in order to compare them over time and space using two linked views. Apart from geo-based comparison across sensors we also support different temporal patterns to discover seasonal effects, anomalies and periodicities. The methods we use are best practices in the information visualization domain. They cover the daily, the weekly and seasonal and patterns of the data. Daily patterns can be analyzed in a clustering-based view, weekly patterns in a calendar-based view and seasonal patters in a projection-based view. The connectivity of the sensors can be analyzed through a dedicated topological network view. We assist the domain expert with interaction techniques to make the results understandable. As a result, the user can identify and analyze erroneous and suspicious measurements in the network. A case study with a domain expert verified the usefulness of our approach.

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