EuroVis13: Eurographics Conference on Visualization

Permanent URI for this collection

https://diglib.eg.org/handle/10.2312/13888

Preface and Table of Contents

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Constructing Isosurfaces with Sharp Edges and Corners using Cube Merging

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Bhattacharya, Arindam

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Wenger, Rephael

Evaluating Isosurfaces with Level-set-based Information Maps

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Wei, Tzu-Hsuan

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Lee, Teng-Yok

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Shen, Han-Wei

Progressive High-Quality Response Surfaces for Visually Guided Sensitivity Analysis

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Demir, Ismael

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Westermann, Rüdiger

Evolutionary Visual Exploration: Evaluation With Expert Users

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Boukhelifa, Nadia

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Cancino, Waldo

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Bezerianos, Anastasia

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Lutton, Evelyne

EvalBench: A Software Library for Visualization Evaluation

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Aigner, Wolfgang

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Hoffmann, Stephan

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Rind, Alexander

Evaluation of Attention-Guiding Video Visualization

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Kurzhals, Kuno

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Höferlin, Markus

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Weiskopf, Daniel

Visual Analysis of Set Relations in a Graph

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Xu, Panpan

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Du, Fan

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Cao, Nan

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Shi, Conglei

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Zhou, Hong

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Qu, Huamin

VisRuption: Intuitive and Efficient Visualization of Temporal Airline Disruption Data

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Rosenthal, Paul

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Pfeiffer, Linda

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Müller, Nicholas H.

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Ohler, Peter

Maximum Entropy Summary Trees

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Karloff, Howard

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Shirley, Kenneth E.

Towards High-dimensional Data Analysis in Air Quality Research

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Engel, Daniel

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Hummel, Mathias

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Hoepel, Florian

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Bein, Keith

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Wexler, Anthony

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Garth, Christoph

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Hamann, Bernd

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Hagen, Hans

An Interactive Analysis and Exploration Tool for Epigenomic Data

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Younesy, Hamidreza

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Nielsen, Cydney B.

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Möller, Torsten

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Alder, Olivia

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Cullum, Rebecca

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Lorincz, Matthew C.

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Karimi, Mohammad M.

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Jones, Steven J. M.

HiFiVE: A Hilbert Space Embedding of Fiber Variability Estimates for Uncertainty Modeling and Visualization

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Schultz, Thomas

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Schlaffke, Lara

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Schölkopf, Bernhard

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Schmidt-Wilcke, Tobias

Complexity Plots

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Thiyagalingam, Jeyarajan

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Walton, Simon

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Duffy, Brian

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Trefethen, Anne

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Chen, Min

Visualizing Large-scale Parallel Communication Traces Using a Particle Animation Technique

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Sigovan, Carmen M.

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Muelder, Chris W.

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Ma, Kwan-Liu

Nonparametric Models for Uncertainty Visualization

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Pöthkow, Kai

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Hege, Hans-Christian

A Visual Approach to Investigating Shared and Global Memory Behavior of CUDA Kernels

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Rosen, Paul

TAMRESH - Tensor Approximation Multiresolution Hierarchy for Interactive Volume Visualization

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Suter, Susanne K.

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Makhynia, Maxim

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Pajarola, Renato

Gestaltlines

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Brandes, Ulrik

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Nick, Bobo

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Rockstroh, Brigitte

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Steffen, Astrid

Scale-Stack Bar Charts

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Hlawatsch, Marcel

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Sadlo, Filip

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Burch, Michael

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Weiskopf, Daniel

Small Multiples, Large Singles: A New Approach for Visual Data Exploration

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Elzen, Stef van den

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Wijk, Jarke J. van

Vector Field k-Means: Clustering Trajectories by Fitting Multiple Vector Fields

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Ferreira, Nivan

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Klosowski, James T.

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Scheidegger, Carlos E.

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Silva, Cláudio T.

Mass-Dependent Integral Curves in Unsteady Vector Fields

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Günther, Tobias

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Kuhn, Alexander

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Kutz, Benjamin

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Theisel, Holger

Visualizing Robustness of Critical Points for 2D Time-Varying Vector Fields

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Wang, Bei

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Rosen, Paul

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Skraba, Primoz

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Bhatia, Harsh

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Pascucci, Valerio

Vessel Visualization using Curvicircular Feature Aggregation

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Mistelbauer, Gabriel

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Morar, Anca

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Varchola, Andrej

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Schernthaner, Rüdiger

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Baclija, Ivan

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Köchl, Arnold

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Kanitsar, Armin

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Bruckner, Stefan

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Gröller, Eduard

Comparative Visualization of Tracer Uptake in In Vivo Small Animal PET/CT Imaging of the Carotid Arteries

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Diepenbrock, Stefan

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Hermann, Sven

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Schäfers, Michael

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Kuhlmann, Michael

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Hinrichs, Klaus

Spatially Efficient Design of Annotated Metro Maps

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Wu, Hsiang-Yun

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Takahashi, Shigeo

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Hirono, Daichi

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Arikawa, Masatoshi

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Lin, Chun-Cheng

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Yen, Hsu-Chun

AmniVis - A System for Qualitative Exploration of Near-Wall Hemodynamics in Cerebral Aneurysms

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Neugebauer, Mathias

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Lawonn, Kai

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Beuing, Oliver

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Berg, Philipp

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Janiga, Gabor

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Preim, Bernhard

Visualizing Interchange Patterns in Massive Movement Data

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Zeng, Wei

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Fu, Chi-Wing

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Arisona, Stefan Müller

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Qu, Huamin

AOI Rivers for Visualizing Dynamic Eye Gaze Frequencies

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Burch, Michael

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Kull, Andreas

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Weiskopf, Daniel

User-driven Feature Space Transformation

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Mamani, Gladys M. H.

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Fatore, Francisco M.

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Nonato, Luis G.

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Paulovich, Fernando V.

Visualizing Motional Correlations in Molecular Dynamics using Geometric Deformations

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Fioravante, Matthew

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Shook, Adam

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Thorpe, Ian

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Rheingans, Penny

Continuous Representation of Projected Attribute Spaces of Multifields over Any Spatial Sampling

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Molchanov, Vladimir

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Fofonov, Alexey

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Linsen, Lars

Streamlines for Illustrative Real-Time Rendering

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Lawonn, Kai

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Moench, Tobias

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Preim, Bernhard

Interactive Extraction and Tracking of Biomolecular Surfaces Features

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Krone, Michael

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Reina, Guido

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Schulz, Christoph

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Kulschewski, Tobias

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Pleiss, Jürgen

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Ertl, Thomas

A Primal/ Dual Representation for Discrete Morse Complexes on Tetrahedral Meshes

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Weiss, Kenneth

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Iuricich, Federico

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Fellegara, Riccardo

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Floriani, Leila De

dPSO-Vis: Topology-based Visualization of Discrete Particle Swarm Optimization

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Volke, Sebastian

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Middendorf, Martin

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Hlawitschka, Mario

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Kasten, Jens

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Zeckzer, Dirk

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Scheuermann, Gerik

Towards Multifield Scalar Topology Based on Pareto Optimality

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Huettenberger, Lars

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Heine, Christian

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Carr, Hamish

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Scheuermann, Gerik

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Garth, Christoph

Fingerprint Matrices: Uncovering the Dynamics of Social Networks in Prose Literature

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Oelke, Daniela

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Kokkinakis, Dimitrios

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Keim, Daniel A.

Rule-based Visual Mappings - with a Case Study on Poetry Visualization

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Abdul-Rahman, Alfie

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Lein, Julie

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Coles, Katharine

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Maguire, Eamonn

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Meyer, Miriah

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Wynne, Martin

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Johnson, Chris R.

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Trefethen, Anne

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Chen, Min

Augmenting Visualization with Natural Language Translation of Interaction: A Usability Study

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Nafari, Maryam

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Weaver, Chris

Selecting Semantically-Resonant Colors for Data Visualization

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Lin, Sharon

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Fortuna, Julie

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Kulkarni, Chinmay

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Stone, Maureen

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Heer, Jeffrey

imMens: Real-time Visual Querying of Big Data

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Liu, Zhicheng

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Jiang, Biye

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Heer, Jeffrey

An Information-Theoretic Observation Channel for Volume Visualization

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Bramon, Roger

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Ruiz, Marc

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Bardera, Anton

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Boada, Imma

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Feixas, Miquel

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Sbert, Mateu

ExPlates: Spatializing Interactive Analysis to Scaffold Visual Exploration

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Javed, Waqas

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Elmqvist, Niklas

Visual Explanation of the Complexity in Julia Sets

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Schrijvers, Okke

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Wijk, Jarke J. van

TrajectoryLenses - A Set-based Filtering and Exploration Technique for Long-term Trajectory Data

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Krüger, Robert

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Thom, Dennis

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Wörner, Michael

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Bosch, Harald

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Ertl, Thomas

ViviSection: Skeleton-based Volume Editing

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Karimov, Alexey

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Mistelbauer, Gabriel

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Schmidt, Johanna

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Mindek, Peter

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Schmidt, Elisabeth

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Sharipov, Timur

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Bruckner, Stefan

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Gröller, Eduard

Synthetic Brainbows

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Wan, Yong

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Otsuna, Hideo

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Hansen, Charles

Interactive Ray Casting of Geodesic Grids

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Xie, Jinrong

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Yu, Hongfeng

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Ma, Kwan-Liu

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Now showing 1 - 50 of 50

Preface and Table of Contents
(The Eurographics Association and Blackwell Publishing Ltd., 2013) B. Preim, P. Rheingans, and H. Theisel
Constructing Isosurfaces with Sharp Edges and Corners using Cube Merging
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Bhattacharya, Arindam; Wenger, Rephael; B. Preim, P. Rheingans, and H. Theisel
A number of papers present algorithms to construct isosurfaces with sharp edges and corners from hermite data, i.e. the exact surface normals at the exact intersection of the surface and grid edges. We discuss some fundamental problems with the previous algorithms and describe a new approach, based on merging grid cubes near sharp edges, that produces significantly better results. Our algorithm requires only gradients at the grid vertices, not at each surface-edge intersection point. We also give a method for measuring the correctness of the resulting sharp edges and corners in the isosurface.
Evaluating Isosurfaces with Level-set-based Information Maps
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Wei, Tzu-Hsuan; Lee, Teng-Yok; Shen, Han-Wei; B. Preim, P. Rheingans, and H. Theisel
While isosurfaces have been widely used for scalar data visualization, it is often difficult to determine if the selected isosurfaces for visualization are sufficient to represent the entire scalar field. In this paper, we present an information-theoretic approach to evaluate the representativeness of a given isosurface set. Our basic idea is that given two isosurfaces that enclose a subvolume, if the intermediate isosurfaces in the subvolume can be generated by smoothly morphing from one isosurface to the other, no additional isosurfaces are needed since the geometry of the true isosurfaces within the subvolume can be easily inferred. To realize this idea, given a pair of isosurfaces, to determine if such a smooth condition in the enclosed region is satisfied, we use a level-set approach to generate the intermediate surfaces. On each intermediate surface, we sample the values from the scalar field and exam the distribution. If the entropy of the distribution is low, this intermediate surface is aligned well with a true isosurface in the scalar field. For the intermediate surfaces generated by the level-set method from the boundary isosurfaces, the distributions of scalar values from the level-set surfaces form a 2D distribution, called isosurface information map. This information map can be used as an indicator of the representativeness of the boundary isosurfaces for the data in the subregion, allowing a quantitative measurement of information representable by the input isosurfaces. Based on this information-theoretic approach, this paper presents an isosurface selection algorithm that can automatically select isosurfaces for more effective visualization of scalar fields.
Progressive High-Quality Response Surfaces for Visually Guided Sensitivity Analysis
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Demir, Ismael; Westermann, Rüdiger; B. Preim, P. Rheingans, and H. Theisel
In this paper we present a technique which allows us to perform high quality and progressive response surface prediction from multidimensional input samples in an efficient manner. We utilize kriging interpolation to estimate a response surface which minimizes the expectation value and variance of the prediction error. High computational efficiency is achieved by employing parallel matrix and vector operations on the GPU. Our approach differs from previous kriging approaches in that it uses a novel progressive updating scheme for new samples based on blockwise matrix inversion. In this way we can handle very large sample sets to which new samples are continually added. Furthermore, we can monitor the incremental evolution of the surface, providing a means to early terminate the computation when no significant changes have occurred. When the generation of input samples is fast enough, our technique enables steering this generation process interactively to find relevant dependency relations.
Evolutionary Visual Exploration: Evaluation With Expert Users
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Boukhelifa, Nadia; Cancino, Waldo; Bezerianos, Anastasia; Lutton, Evelyne; B. Preim, P. Rheingans, and H. Theisel
We present an Evolutionary Visual Exploration (EVE) system that combines visual analytics with stochastic optimisation to aid the exploration of multidimensional datasets characterised by a large number of possible views or projections. Starting from dimensions whose values are automatically calculated by a PCA, an interactive evolutionary algorithm progressively builds (or evolves) non-trivial viewpoints in the form of linear and non-linear dimension combinations, to help users discover new interesting views and relationships in their data. The criteria for evolving new dimensions is not known a priori and are partially specified by the user via an interactive interface: (i) The user selects views with meaningful or interesting visual patterns and provides a satisfaction score. (ii) The system calibrates a fitness function (optimised by the evolutionary algorithm) to take into account the user input, and then calculates new views. Our method leverages automatic tools to detect interesting visual features and human interpretation to derive meaning, validate the findings and guide the exploration without having to grasp advanced statistical concepts. To validate our method, we built a prototype tool (EvoGraphDice) as an extension of an existing scatterplot matrix inspection tool, and conducted an observational study with five domain experts. Our results show that EvoGraphDice can help users quantify qualitative hypotheses and try out different scenarios to dynamically transform their data. Importantly, it allowed our experts to think laterally, better formulate their research questions and build new hypotheses for further investigation.
EvalBench: A Software Library for Visualization Evaluation
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Aigner, Wolfgang; Hoffmann, Stephan; Rind, Alexander; B. Preim, P. Rheingans, and H. Theisel
It is generally acknowledged in visualization research that it is necessary to evaluate visualization artifacts in order to provide empirical evidence on their effectiveness and efficiency as well as their usability and utility. However, the difficulties of conducting such evaluations still remain an issue. Apart from the required know-how to appropriately design and conduct user studies, the necessary implementation effort for evaluation features in visualization software is a considerable obstacle. To mitigate this, we present EvalBench, an easy-to-use, flexible, and reusable software library for visualization evaluation written in Java. We describe its design choices and basic abstractions of our conceptual architecture and demonstrate its applicability by a number of case studies. EvalBench reduces implementation effort for evaluation features and makes conducting user studies easier. It can be used and integrated with third-party visualization prototypes that need to be evaluated via loose coupling. Eval- Bench supports both, quantitative and qualitative evaluation methods such as controlled experiments, interaction logging, laboratory questionnaires, heuristic evaluations, and insight diaries.
Evaluation of Attention-Guiding Video Visualization
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Kurzhals, Kuno; Höferlin, Markus; Weiskopf, Daniel; B. Preim, P. Rheingans, and H. Theisel
We investigate four different variants of attention-guiding video visualization techniques that aim to help users distribute their attention equally among potential objects of interest: bounding box visualization, force-directed visualization, top-down visualization, grid visualization. Objects of interest are highlighted by rectangular shapes and then we concentrate on the manipulation of color, motion, and size. We conducted a controlled laboratory user study (n
Visual Analysis of Set Relations in a Graph
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Xu, Panpan; Du, Fan; Cao, Nan; Shi, Conglei; Zhou, Hong; Qu, Huamin; B. Preim, P. Rheingans, and H. Theisel
Many applications can be modeled as a graph with additional attributes attached to the nodes. For example, a graph can be used to model the relationship of people in a social media website or a bibliographical dataset. Meanwhile, additional information is often available, such as the topics people are interested in and the music they listen to. Based on this additional information, different set relationships may exist among people. Revealing the set relationships in a network can help people gain social insight and better understand their roles within a community. In this paper, we present a visualization system for exploring set relations in a graph. Our system is designed to reveal three different relationships simultaneously: the social relationship of people, the set relationship among people's items of interest, and the similarity relationship of the items. We propose two novel visualization designs: a) a glyph-based visualization to reveal people's set relationships in the context of their social networks; b) an integration of visual links and a contour map to show people and their items of interest which are clustered into different groups. The effectiveness of the designs has been demonstrated by the case studies on two representative datasets including one from a social music service website and another from an academic collaboration network.
VisRuption: Intuitive and Efficient Visualization of Temporal Airline Disruption Data
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Rosenthal, Paul; Pfeiffer, Linda; Müller, Nicholas H.; Ohler, Peter; B. Preim, P. Rheingans, and H. Theisel
The operation of an airline is a very complex task and disruptions to the planned operation can occur on very short notice. Already a small disruption like a delay of some minutes can cost the airline a tremendous amount of money. Hence, it is crucial to proactively control all operations of the airline and efficiently prioritize and handle disruptions. Due to the complex setting and the need for ad hoc decisions this task can only be carried out by human operation controllers. In the field of airline operations control there exists already a vast variety of different software in productive use. We analyze the different approaches from two of the market leaders and identify problematic design choices. We take into account this analysis and develop a set of rules for an intuitive visualization of airline disruption data. Finally, we introduce our tool for visualizing such data which complies to these rules. The visualization enables the user to gain a fast overview over the current problem situation and to intuitively prioritize different problems and problem hierarchies. The efficiency of the design is evaluated with the help of a user study which shows that the new system significantly outperforms the current state of the art.
Maximum Entropy Summary Trees
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Karloff, Howard; Shirley, Kenneth E.; B. Preim, P. Rheingans, and H. Theisel
Given a very large, node-weighted, rooted tree on, say, n nodes, if one has only enough space to display a knode summary of the tree, what is the most informative way to draw the tree? We define a type of weighted tree that we call a summary tree of the original tree that results from aggregating nodes of the original tree subject to certain constraints. We suggest that the best choice of which summary tree to use (among those with a fixed number of nodes) is the one that maximizes the information-theoretic entropy of a natural probability distribution associated with the summary tree, and we provide a (pseudopolynomial-time) dynamic-programming algorithm to compute this maximum entropy summary tree, when the weights are integral. The result is an automated way to summarize large trees and retain as much information about them as possible, while using (and displaying) only a fraction of the original node set. We illustrate the computation and use of maximum entropy summary trees on five real data sets whose weighted tree representations vary widely in structure. We also provide an additive approximation algorithm and a greedy heuristic that are faster than the optimal algorithm, and generalize to trees with real-valued weights.
Towards High-dimensional Data Analysis in Air Quality Research
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Engel, Daniel; Hummel, Mathias; Hoepel, Florian; Bein, Keith; Wexler, Anthony; Garth, Christoph; Hamann, Bernd; Hagen, Hans; B. Preim, P. Rheingans, and H. Theisel
Analysis of chemical constituents from mass spectrometry of aerosols involves non-negative matrix factorization, an approximation of high-dimensional data in lower-dimensional space. The associated optimization problem is non-convex, resulting in crude approximation errors that are not accessible to scientists. To address this shortcoming, we introduce a new methodology for user-guided error-aware data factorization that entails an assessment of the amount of information contributed by each dimension of the approximation, an effective combination of visualization techniques to highlight, filter, and analyze error features, as well as a novel means to interactively refine factorizations. A case study and the domain-expert feedback provided by the collaborating atmospheric scientists illustrate that our method effectively communicates errors of such numerical optimization results and facilitates the computation of high-quality data factorizations in a simple and intuitive manner.
An Interactive Analysis and Exploration Tool for Epigenomic Data
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Younesy, Hamidreza; Nielsen, Cydney B.; Möller, Torsten; Alder, Olivia; Cullum, Rebecca; Lorincz, Matthew C.; Karimi, Mohammad M.; Jones, Steven J. M.; B. Preim, P. Rheingans, and H. Theisel
In this design study, we present an analysis and abstraction of the data and tasks related to the domain of epigenomics, and the design and implementation of an interactive tool to facilitate data analysis and visualization in this domain. Epigenomic data can be grouped into subsets either by k-means clustering or by querying for combinations of presence or absence of signal (on/off) in different epigenomic experiments. These steps can easily be interleaved and the comparison of different workflows is explicitly supported. We took special care to contain the exponential expansion of possible on/off combinations by creating a novel querying interface. An interactive heat map facilitates the exploration and comparison of different clusters. We validated our iterative design by working closely with two groups of biologists on different biological problems. Both groups quickly found new insight into their data as well as claimed that our tool would save them several hours or days of work over using existing tools.
HiFiVE: A Hilbert Space Embedding of Fiber Variability Estimates for Uncertainty Modeling and Visualization
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Schultz, Thomas; Schlaffke, Lara; Schölkopf, Bernhard; Schmidt-Wilcke, Tobias; B. Preim, P. Rheingans, and H. Theisel
Obtaining reproducible fiber direction estimates from diffusion MRI is crucial for successful fiber tracking. Modeling and visualizing the probability distribution of the inferred fiber directions is an important step in evaluating and comparing different acquisition schemes and fiber models. However, this distribution is usually strongly dominated by its main direction, which makes it difficult to examine when plotted naively. In this work, we propose a new visualization of the fiber probability distribution. It is based on embedding the probability measure into a particular reproducing kernel Hilbert space. This permits a decomposition into an embedded delta peak, representing the main direction, and a non-negative residual. They are then combined into a new glyph representation which visually enhances the residual, in order to highlight even subtle differences. Moreover, the magnitude of the delta peak component quantifies precision of the main fiber direction. We demonstrate that our new glyph provides a more detailed impression of the uncertainty than the current standard method, cones that contain 95% of the estimated directions. We use our new method to contribute to the validation of different ways of resampling the data (bootstrapping), and to visualize the differences between alternative acquisition schemes and models for high angular resolution diffusion imaging (HARDI).
Complexity Plots
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Thiyagalingam, Jeyarajan; Walton, Simon; Duffy, Brian; Trefethen, Anne; Chen, Min; B. Preim, P. Rheingans, and H. Theisel
In this paper, we present a novel visualization technique for assisting the observation and analysis of algorithmic complexity. In comparison with conventional line graphs, this new technique is not sensitive to the units of measurement, allowing multivariate data series of different physical qualities (e.g., time, space and energy) to be juxtaposed together conveniently and consistently. It supports multivariate visualization as well as uncertainty visualization. It enables users to focus on algorithm categorization by complexity classes, while reducing visual impact caused by constants and algorithmic components that are insignificant to complexity analysis. It provides an effective means for observing the algorithmic complexity of programs with a mixture of algorithms and blackbox software through visualization. Through two case studies, we demonstrate the effectiveness of complexity plots in complexity analysis in research, education and application.
Visualizing Large-scale Parallel Communication Traces Using a Particle Animation Technique
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Sigovan, Carmen M.; Muelder, Chris W.; Ma, Kwan-Liu; B. Preim, P. Rheingans, and H. Theisel
Large-scale scientific simulations require execution on parallel computing systems in order to yield useful results in a reasonable time frame. But parallel execution adds communication overhead. The impact that this overhead has on performance may be difficult to gauge, as parallel application behaviors are typically harder to understand than the sequential types. We introduce an animation-based interactive visualization technique for the analysis of communication patterns occurring in parallel application execution. Our method has the advantages of illustrating the dynamic communication patterns in the system as well as a static image of MPI (Message Passing Interface) utilization history. We also devise a data streaming mechanism that allows for the exploration of very large data sets. We demonstrate the effectiveness of our approach scaling up to 16 thousand processes using a series of trace data sets of ScaLAPACK matrix operations functions.
Nonparametric Models for Uncertainty Visualization
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Pöthkow, Kai; Hege, Hans-Christian; B. Preim, P. Rheingans, and H. Theisel
An uncertain (scalar, vector, tensor) field is usually perceived as a discrete random field with a priori unknown probability distributions. To compute derived probabilities, e.g. for the occurrence of certain features, an appropriate probabilistic model has to be selected. The majority of previous approaches in uncertainty visualization were restricted to Gaussian fields. In this paper we extend these approaches to nonparametric models, which are much more flexible, as they can represent various types of distributions, including multimodal and skewed ones. We present three examples of nonparametric representations: (a) empirical distributions, (b) histograms and (c) kernel density estimates (KDE). While the first is a direct representation of the ensemble data, the latter two use reconstructed probability density functions of continuous random variables. For KDE we propose an approach to compute valid consistent marginal distributions and to efficiently capture correlations using a principal component transformation. Furthermore, we use automatic bandwidth selection, obtaining a model for probabilistic local feature extraction. The methods are demonstrated by computing probabilities of level crossings, critical points and vortex cores in simulated biofluid dynamics and climate data.
A Visual Approach to Investigating Shared and Global Memory Behavior of CUDA Kernels
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Rosen, Paul; B. Preim, P. Rheingans, and H. Theisel
We present an approach to investigate the memory behavior of a parallel kernel executing on thousands of threads simultaneously within the CUDA architecture. Our top-down approach allows for quickly identifying any significant differences between the execution of the many blocks and warps. As interesting warps are identified, we allow further investigation of memory behavior by visualizing the shared memory bank conflicts and global memory coalescence, first with an overview of a single warp with many operations and, subsequently, with a detailed view of a single warp and a single operation. We demonstrate the strength of our approach in the context of a parallel matrix transpose kernel and a parallel 1D Haar Wavelet transform kernel.
TAMRESH - Tensor Approximation Multiresolution Hierarchy for Interactive Volume Visualization
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Suter, Susanne K.; Makhynia, Maxim; Pajarola, Renato; B. Preim, P. Rheingans, and H. Theisel
Interactive visual analysis of large and complex volume datasets is an ongoing and challenging problem. We tackle this challenge in the context of state-of-the-art out-of-core multiresolution volume rendering by introducing a novel hierarchical tensor approximation (TA) volume visualization approach. The TA framework allows us (a) to use a rank-truncated basis for compact volume representation, (b) to visualize features at multiple scales, and (c) to visualize the data at multiple resolutions. In this paper, we exploit the special properties of the TA factor matrix bases and define a novel multiscale and multiresolution volume rendering hierarchy. Different from previous approaches, to represent one volume dataset we use but one set of global bases (TA factor matrices) to reconstruct at all resolution levels and feature scales. In particular, we propose a coupling of multiscalable feature visualization and multiresolution DVR through the properties of global TA bases. We demonstrate our novel TA multiresolution hierarchy based volume representation and visualization on a number of mCT volume datasets.
Gestaltlines
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Brandes, Ulrik; Nick, Bobo; Rockstroh, Brigitte; Steffen, Astrid; B. Preim, P. Rheingans, and H. Theisel
We propose a general technique to visualize multivariate data sequences. It is based on a symbiotic combination of three powerful concepts from information visualization: sparklines, glyphs and gestalt theory. By visualizing several well-known data sets in new ways we first demonstrate how explicit consideration of gestalt principles can be used to leverage visual perception capabilities for the identification of patterns such as trends, periodicities, change points, or outliers. A more detailed case study with complex and noisy data from a psychological experiment then demonstrates how basic design ideas for gestaltlines can be applied in less controlled, and thus more realistic, situations. The case study is complemented with reports on feedback from domain experts and a user study, both indicating that gestaltlines can be a convenient and valid means to explore and communicate patterns in micro-visualizations.
Scale-Stack Bar Charts
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Hlawatsch, Marcel; Sadlo, Filip; Burch, Michael; Weiskopf, Daniel; B. Preim, P. Rheingans, and H. Theisel
It is difficult to create appropriate bar charts for data that cover large value ranges. The usual approach for these cases employs a logarithmic scale, which, however, suffers from issues inherent to its non-linear mapping: for example, a quantitative comparison of different values is difficult. We present a new approach for bar charts that combines the advantages of linear and logarithmic scales, while avoiding their drawbacks. Our scale-stack bar charts use multiple scales to cover a large value range, while the linear mapping within each scale preserves the ability to visually compare quantitative ratios. Scale-stack bar charts can be used for the same applications as classic bar charts; in particular, they can readily handle stacked bar representations and negative values. Our visualization technique is demonstrated with results for three different application areas and is assessed by an expert review and a quantitative user study confirming advantages of our technique for quantitative comparisons.
Small Multiples, Large Singles: A New Approach for Visual Data Exploration
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Elzen, Stef van den; Wijk, Jarke J. van; B. Preim, P. Rheingans, and H. Theisel
We present a novel visual exploration method based on small multiples and large singles for effective and efficient data analysis. Users are enabled to explore the state space by offering multiple alternatives from the current state. Users can then select the alternative of choice and continue the analysis. Furthermore, the intermediate steps in the exploration process are preserved and can be revisited and adapted using an intuitive navigation mechanism based on the well-known undo-redo stack and filmstrip metaphor. As proof of concept the exploration method is implemented in a prototype. The effectiveness of the exploration method is tested using a formal user study comparing four different interaction methods. By using Small Multiples as data exploration method users need fewer steps in answering questions and also explore a significantly larger part of the state space in the same amount of time, providing them with a broader perspective on the data, hence lowering the chance of missing important features. Also, users prefer visual exploration with small multiples over non-small multiple variants.
Vector Field k-Means: Clustering Trajectories by Fitting Multiple Vector Fields
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Ferreira, Nivan; Klosowski, James T.; Scheidegger, Carlos E.; Silva, Cláudio T.; B. Preim, P. Rheingans, and H. Theisel
Scientists study trajectory data to understand trends in movement patterns, such as human mobility for traffic analysis and urban planning. In this paper, we introduce a novel trajectory clustering technique whose central idea is to use vector fields to induce a notion of similarity between trajectories, letting the vector fields themselves define and represent each cluster. We present an efficient algorithm to find a locally optimal clustering of trajectories into vector fields, and demonstrate how vector-field k-means can find patterns missed by previous methods. We present experimental evidence of its effectiveness and efficiency using several datasets, including historical hurricane data, GPS tracks of people and vehicles, and anonymous cellular radio handoffs from a large service provider.
Mass-Dependent Integral Curves in Unsteady Vector Fields
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Günther, Tobias; Kuhn, Alexander; Kutz, Benjamin; Theisel, Holger; B. Preim, P. Rheingans, and H. Theisel
Recent research in flow visualization is focusing on the analysis of time-dependent, but mass-less particles. However, in many application scenarios, the mass of particles - and their resulting inertia - is essential in understanding fluid mechanics. This includes critical processes, such as dust particles interacting with aircraft (e.g., brownor white-out effects) and particle separation based on density variation. In this paper, we contribute a generalized description of mass-dependent particle trajectories and apply existing unsteady flow visualization methods to the mass-dependent case. This comprises the extension of common concepts, i.e., path lines, streak lines, and time lines. Furthermore, we introduce a new class of integral curves, called mass lines that effectively visualizes mass separation and captures mass-related features in unsteady flow fields that are inaccessible using traditional methods. We demonstrate the applicability of our method, using a number of real-world and artificial data sets, in which mass is a crucial parameter. In particular, we focus on the analysis of brown-out conditions, introduced by a helicopter in forward flight close to the ground.
Visualizing Robustness of Critical Points for 2D Time-Varying Vector Fields
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Wang, Bei; Rosen, Paul; Skraba, Primoz; Bhatia, Harsh; Pascucci, Valerio; B. Preim, P. Rheingans, and H. Theisel
Analyzing critical points and their temporal evolutions plays a crucial role in understanding the behavior of vector fields. A key challenge is to quantify the stability of critical points: more stable points may represent more important phenomena or vice versa. The topological notion of robustness is a tool which allows us to quantify rigorously the stability of each critical point. Intuitively, the robustness of a critical point is the minimum amount of perturbation necessary to cancel it within a local neighborhood, measured under an appropriate metric. In this paper, we introduce a new analysis and visualization framework which enables interactive exploration of robustness of critical points for both stationary and time-varying 2D vector fields. This framework allows the end-users, for the first time, to investigate how the stability of a critical point evolves over time. We show that this depends heavily on the global properties of the vector field and that structural changes can correspond to interesting behavior. We demonstrate the practicality of our theories and techniques on several datasets involving combustion and oceanic eddy simulations and obtain some key insights regarding their stable and unstable features.
Vessel Visualization using Curvicircular Feature Aggregation
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Mistelbauer, Gabriel; Morar, Anca; Varchola, Andrej; Schernthaner, Rüdiger; Baclija, Ivan; Köchl, Arnold; Kanitsar, Armin; Bruckner, Stefan; Gröller, Eduard; B. Preim, P. Rheingans, and H. Theisel
Radiological investigations are common medical practice for the diagnosis of peripheral vascular diseases. Existing visualization methods such as Curved Planar Reformation (CPR) depict calcifications on vessel walls to determine if blood is still able to flow. While it is possible with conventional CPR methods to examine the whole vessel lumen by rotating around the centerline of a vessel, we propose Curvicircular Feature Aggregation (CFA), which aggregates these rotated images into a single view. By eliminating the need for rotation, vessels can be investigated by inspecting only one image. This method can be used as a guidance and visual analysis tool for treatment planning. We present applications of this technique in the medical domain and give feedback from radiologists.
Comparative Visualization of Tracer Uptake in In Vivo Small Animal PET/CT Imaging of the Carotid Arteries
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Diepenbrock, Stefan; Hermann, Sven; Schäfers, Michael; Kuhlmann, Michael; Hinrichs, Klaus; B. Preim, P. Rheingans, and H. Theisel
Cardiovascular diseases are the main cause of death in the western world. Medical research on atherosclerosis is therefore of great interest and a very active research topic. We present a visualization system that supports scientists in exploring plaque development and evaluating the applicability of PET tracers for early diagnosis of cardiovascular diseases. In our application case a cone shaped cuff has been implanted around the carotid artery of ApoE knockout mice, fed with a high cholesterol western type diet. As a result, vascular lesions develop upstream and downstream from the cuff. Tracer uptake induced by these lesions needs to be analyzed in order to evaluate the effectiveness of different PET tracers. We discuss the approach previously utilized to perform this kind of analysis, the problems arising from in vivo image acquisition (in contrast to ex vivo) and the design process of our application. In close cooperation with domain experts we have developed new visualization techniques that display PET activity in the vessel wall and surrounding tissue in a single image. We use the vessel wall detected in the CT image to perform a normalized circular projection which allows the user to judge PET signal distribution in relation to the deformed vessel. Based on this projection a quantitative analysis of a defined region adjacent to the vessel wall can be performed and compared to the artery without the cuff.
Spatially Efficient Design of Annotated Metro Maps
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Wu, Hsiang-Yun; Takahashi, Shigeo; Hirono, Daichi; Arikawa, Masatoshi; Lin, Chun-Cheng; Yen, Hsu-Chun; B. Preim, P. Rheingans, and H. Theisel
Annotating metro maps with thumbnail photographs is a commonly used technique for guiding travelers. However, conventional methods usually suffer from small labeling space around the metro stations, especially when they are interchange stations served by two or more metro lines. This paper presents an approach for aesthetically designing schematic metro maps while ensuring effective placement of large annotation labels that are sufficiently close to their corresponding stations. Our idea is to distribute such labels in a well-balanced manner to labeling regions around the metro network first and then adjust the lengths of metro line and leader line segments, which allows us to fully maximize the space coverage of the entire annotated map. This is accomplished by incorporating additional constraints into the conventional mixed-integer programming formulation, while we devised a three-step algorithm for accelerating the overall optimization process. We include several design examples to demonstrate the spatial efficiency of the map layout generated using the proposed approach through minimal user intervention.
AmniVis - A System for Qualitative Exploration of Near-Wall Hemodynamics in Cerebral Aneurysms
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Neugebauer, Mathias; Lawonn, Kai; Beuing, Oliver; Berg, Philipp; Janiga, Gabor; Preim, Bernhard; B. Preim, P. Rheingans, and H. Theisel
The qualitative exploration of near-wall hemodynamics in cerebral aneurysms provides important insights for risk assessment. For instance, a direct relation between complex flow patterns and aneurysm formation could be observed. Due to the high complexity of the underlying time-dependent flow data, the exploration is challenging, in particular for medical researchers not familiar with such data. We present the AmniVis-Explorer, a system that is designed for the preparation of a qualitative medical study. The provided features were developed in close collaboration with medical researchers involved in the study. This comprises methods for a purposeful selection of surface regions of interest and a novel approach to provide a 2D overview of flow patterns that are represented by streamlines at these regions. Furthermore, we present a specialized interface that supports binary classification of patterns and temporal exploration as well as methods for selection, highlighting and automatic 3D navigation to particular patterns. Based on eight representative datasets, we conducted informal interviews with two bordcertified radiologists and a flow expert to evaluate the system. It was confirmed that the AmniVis-Explorer allows for an easy selection, qualitative exploration and classification of near-wall flow patterns that are represented by streamlines.
Visualizing Interchange Patterns in Massive Movement Data
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Zeng, Wei; Fu, Chi-Wing; Arisona, Stefan Müller; Qu, Huamin; B. Preim, P. Rheingans, and H. Theisel
Massive amount of movement data, such as daily trips made by millions of passengers in a city, are widely available nowadays. They are a highly valuable means not only for unveiling human mobility patterns, but also for assisting transportation planning, in particular for metropolises around the world. In this paper, we focus on a novel aspect of visualizing and analyzing massive movement data, i.e., the interchange pattern, aiming at revealing passenger redistribution in a traffic network. We first formulate a new model of circos figure, namely the interchange circos diagram, to present interchange patterns at a junction node in a bundled fashion, and optimize the color assignments to respect the connections within and between junction nodes. Based on this, we develop a family of visual analysis techniques to help users interactively study interchange patterns in a spatiotemporal manner: 1) multi-spatial scales: from network junctions such as train stations to people flow across and between larger spatial areas; and 2) temporal changes of patterns from different times of the day. Our techniques have been applied to real movement data consisting of hundred thousands of trips, and we present also two case studies on how transportation experts worked with our interface.
AOI Rivers for Visualizing Dynamic Eye Gaze Frequencies
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Burch, Michael; Kull, Andreas; Weiskopf, Daniel; B. Preim, P. Rheingans, and H. Theisel
It is difficult to explore and analyze eye gaze trajectories for commonly applied visual task solution strategies because such data shows complex spatio-temporal structure. In particular, the traditional eye gaze plots of scan paths fail for a large number of study participants since these plots lead to much visual clutter. To address this problem we introduce the AOI Rivers technique as a novel interactive visualization method for investigating timevarying fixation frequencies, transitions between areas of interest (AOIs), and the sequential order of gaze visits to AOIs in a visual stimulus of an eye tracking experiment. To this end, we extend the ThemeRiver technique by influents, effluents, and transitions similar to the concept of Sankey diagrams. The AOI Rivers visualization is complemented by linked spatial views of the data in the form of heatmaps, gaze plots, or display of the visual stimulus. The usefulness of our technique is demonstrated for gaze trajectory data recorded in a previously conducted eye tracking experiment.
User-driven Feature Space Transformation
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Mamani, Gladys M. H.; Fatore, Francisco M.; Nonato, Luis G.; Paulovich, Fernando V.; B. Preim, P. Rheingans, and H. Theisel
Interactive visualization systems for exploring and manipulating high-dimensional feature spaces have experienced a substantial progress in the last few years. State-of-art methods rely on solid mathematical and computational foundations that enable sophisticated and flexible interactive tools. Current methods are even capable of modifying data attributes during interaction, highlighting regions of potential interest in the feature space, and building visualizations that bring out the relevance of attributes. However, those methodologies rely on complex and non-intuitive interfaces that hamper the free handling of the feature spaces. Moreover, visualizing how neighborhood structures are affected during the space manipulation is also an issue for existing methods. This paper presents a novel visualization-assisted methodology for interacting and transforming data attributes embedded in feature spaces. The proposed approach relies on a combination of multidimensional projections and local transformations to provide an interactive mechanism for modifying attributes. Besides enabling a simple and intuitive visual layout, our approach allows the user to easily observe the changes in neighborhood structures during interaction. The usefulness of our methodology is shown in an application geared to image retrieval.
Visualizing Motional Correlations in Molecular Dynamics using Geometric Deformations
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Fioravante, Matthew; Shook, Adam; Thorpe, Ian; Rheingans, Penny; B. Preim, P. Rheingans, and H. Theisel
In macromolecules, an allosteric effect is said to occur when a change at one site of a molecule affects a distant site. Understanding these allosteric effects can be important for understanding how the functions of complex molecules such as proteins are regulated. One potential application of this knowledge is the development of small molecules that alter the function of proteins involved in diseases. Studying motional correlation can help researchers to discover how a change at a source site affects the target site and thus how allosteric ligands that could serve as drugs are able to exert their therapeutic effects. By improving our ability to analyze these correlated relationships, it may be possible to develop new medications to combat deadly diseases such as Hepatitis C. We present four visual techniques which represent motional correlation on rendered three-dimensional molecular models, providing new ways to view clusters of correlated residues and paths of allosteric interactions. These techniques give us a new way of investigating the presence of motional correlations in complex molecules. We compare each of these techniques to determine which are the most useful for representing motional correlations.
Continuous Representation of Projected Attribute Spaces of Multifields over Any Spatial Sampling
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Molchanov, Vladimir; Fofonov, Alexey; Linsen, Lars; B. Preim, P. Rheingans, and H. Theisel
For the visual analysis of multidimensional data, dimension reduction methods are commonly used to project to a lower-dimensional visual space. In the context of multifields, i.e., volume data with a multidimensional attribute space, the spatial arrangement of the samples in the volumetric domain can be exploited to generate a Continuous Representation of the Projected Attribute Space (CoRPAS). Here, the sample locations in the volumetric domain may be arranged in a structured or unstructured way and may or may not be connected by a grid or a mesh. We propose an approach to generate CoRPAS for any sample arrangement using an isotropic density function. An interactive visual exploration system with three coordinated views of volume visualization, CoRPAS, and an interaction widget based on star coordinates is presented. The star-coordinates widget provides an intuitive means for the user to change the projection matrix. The coordinated views allow for feature selection in form of brushing and linking. The approach is applied to both synthetic data and data resulting from numerical simulations of physical phenomena. In particular, simulations based on Smoothed Particle Hydrodynamics are addressed, where the simulation kernel can be used to produce a CoRPAS that is consistent with the simulation. We also show how a logarithmic scaling of attribute values in CoRPAS is supported, which is of high practical relevance.
Streamlines for Illustrative Real-Time Rendering
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Lawonn, Kai; Moench, Tobias; Preim, Bernhard; B. Preim, P. Rheingans, and H. Theisel
Line drawing techniques are important methods to illustrate shapes. Existing feature line methods, e.g., suggestive contours, apparent ridges, or photic extremum lines, solely determine salient regions and illustrate them with separate lines. Hatching methods convey the shape by drawing a wealth of lines on the whole surface. Both approaches are often not sufficient for a faithful visualization of organic surface models, e.g., in biology or medicine. In this paper, we present a novel object-space line drawing algorithm that conveys the shape of such surface models in real-time. Our approach employs contour- and feature-based illustrative streamlines to convey surface shape (ConFIS). For every triangle, precise streamlines are calculated on the surface with a given curvature vector field. Salient regions are detected by determining maxima and minima of a scalar field. Compared with existing feature lines and hatching methods, ConFIS uses the advantages of both categories in an effective and flexible manner. We demonstrate this with different anatomical and artificial surface models. In addition, we conducted a qualitative evaluation of our technique to compare our results with exemplary feature line and hatching methods.
Interactive Extraction and Tracking of Biomolecular Surfaces Features
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Krone, Michael; Reina, Guido; Schulz, Christoph; Kulschewski, Tobias; Pleiss, Jürgen; Ertl, Thomas; B. Preim, P. Rheingans, and H. Theisel
We present a coordinated-view application for the analysis of molecular surface features like cavities, channels and pockets. Our tool employs object-space ambient occlusion for the detection of such features and tracks them over time. It offers time-dependent graphs of metrics concerning those features and allows analyzing the temporal relationship of the features, i.e. when they (dis)appear, split or merge and which features participate in each of these events. The automated analysis process is performed in real time while the user interactively explores a dynamic data set. The system supports linking and brushing to allow for a user-guided visual analysis based on different aspects of the data. We demonstrate the effectiveness of our approach by applying it to data sets from biochemistry and report the insights that can be gained. We also evaluate the benefits of our method with respect to recent advancements in the field. The algorithmic pipeline leverages the computing power of modern GPUs, thus achieving interactive frame rates without any precomputation for fully dynamic data sets.
A Primal/ Dual Representation for Discrete Morse Complexes on Tetrahedral Meshes
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Weiss, Kenneth; Iuricich, Federico; Fellegara, Riccardo; Floriani, Leila De; B. Preim, P. Rheingans, and H. Theisel
We consider the problem of computing discrete Morse and Morse-Smale complexes on an unstructured tetrahedral mesh discretizing the domain of a 3D scalar field. We use a duality argument to define the cells of the descending Morse complex in terms of the supplied (primal) tetrahedral mesh and those of the ascending complex in terms of its dual mesh. The Morse-Smale complex is then described combinatorially as collections of cells from the intersection of the primal and dual meshes. We introduce a simple compact encoding for discrete vector fields attached to the mesh tetrahedra that is suitable for combination with any topological data structure encoding just the vertices and tetrahedra of the mesh. We demonstrate the effectiveness and scalability of our approach over large unstructured tetrahedral meshes by developing algorithms for computing the discrete gradient field and for extracting the cells of the Morse and Morse-Smale complexes. We compare implementations of our approach on an adjacency-based topological data structure and on the PR-star octree, a compact spatio-topological data structure.
dPSO-Vis: Topology-based Visualization of Discrete Particle Swarm Optimization
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Volke, Sebastian; Middendorf, Martin; Hlawitschka, Mario; Kasten, Jens; Zeckzer, Dirk; Scheuermann, Gerik; B. Preim, P. Rheingans, and H. Theisel
Particle swarm optimization (PSO) is a metaheuristic that has been applied successfully to many continuous and combinatorial optimization problems, e.g., in the fields of economics, engineering, and natural sciences. In PSO, a swarm of particles moves within a search space in order to find an optimal solution. Unfortunately, it is hard to understand in detail why and how changes in the design of PSO algorithms affect the optimization behavior. Visualizing the particle states could provide substantially better insight into PSO algorithms. Though in case of combinatorial optimization problems, it often raises the problem of illustrating the states within the discrete search space that cannot be embedded spatially. We propose a visualization approach to depict the optimization problem topologically using a landscape metaphor. This visualization is augmented by an illustration of the time-dependent states of the particles. Thus, the user of dPSO-Vis is able to analyze the swarm's behavior within the search space. In principle, our method can be used for any optimization algorithm where a swarm of individuals searches within a discrete search space. Our approach is verified with a case study for the PSO algorithm HelixPSO that predicts the secondary structure of RNA molecules.
Towards Multifield Scalar Topology Based on Pareto Optimality
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Huettenberger, Lars; Heine, Christian; Carr, Hamish; Scheuermann, Gerik; Garth, Christoph; B. Preim, P. Rheingans, and H. Theisel
How can the notion of topological structures for single scalar fields be extended to multifields? In this paper we propose a definition for such structures using the concepts of Pareto optimality and Pareto dominance. Given a set of piecewise-linear, scalar functions over a common simplical complex of any dimension, our method finds regions of ''consensus'' among single fields' critical points and their connectivity relations. We show that our concepts are useful to data analysis on real-world examples originating from fluid-flow simulations; in two cases where the consensus of multiple scalar vortex predictors is of interest and in another case where one predictor is studied under different simulation parameters. We also compare the properties of our approach with current alternatives.
Fingerprint Matrices: Uncovering the Dynamics of Social Networks in Prose Literature
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Oelke, Daniela; Kokkinakis, Dimitrios; Keim, Daniel A.; B. Preim, P. Rheingans, and H. Theisel
In prose literature often complex dynamics of interpersonal relationships can be observed between the different characters. Traditionally, node-link diagrams are used to depict the social network of a novel. However, static graphs can only visualize the overall social network structure but not the development of the networks over the course of the story, while dynamic graphs have the serious problem that there are many sudden changes between different portions of the overall social network. In this paper we explore means to show the relationships between the characters of a plot and at the same time their development over the course of a novel. Based on a careful exploration of the design space, we suggest a new visualization technique called Fingerprint Matrices. A case study exemplifies the usage of Fingerprint Matrices and shows that they are an effective means to analyze prose literature with respect to the development of relationships between the different characters.
Rule-based Visual Mappings - with a Case Study on Poetry Visualization
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Abdul-Rahman, Alfie; Lein, Julie; Coles, Katharine; Maguire, Eamonn; Meyer, Miriah; Wynne, Martin; Johnson, Chris R.; Trefethen, Anne; Chen, Min; B. Preim, P. Rheingans, and H. Theisel
In this paper, we present a user-centered design study on poetry visualization. We develop a rule-based solution to address the conflicting needs for maintaining the flexibility of visualizing a large set of poetic variables and for reducing the tedium and cognitive load in interacting with the visual mapping control panel. We adopt Munzner's nested design model to maintain high-level interactions with the end users in a closed loop. In addition, we examine three design options for alleviating the difficulty in visualizing poems latitudinally. We present several example uses of poetry visualization in scholarly research on poetry.
Augmenting Visualization with Natural Language Translation of Interaction: A Usability Study
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Nafari, Maryam; Weaver, Chris; B. Preim, P. Rheingans, and H. Theisel
As visualization tools get more complicated, users often find it increasingly difficult to learn interaction sequences, recall past queries, and interpret visual states.We examine a query-to-question (Q2Q) supporting system that takes advantage of natural language generation (NLG) techniques to automatically translate and display query interactions as natural language questions. We focus on a symmetric pattern of multiple coordinated views, cross-filtered views, that involves only nominal/categorical data. We describe a study of the effects of pairing a visualization with a Q2Q interface on several aspects of usability. Q2Q produces considerable improvements in learnability, efficiency, and memorability of visualization in terms of speed and the length of interaction sequences that users follow, along with a modest decrease in error ratio. From a visual language perspective, we analyze how Q2Q speeds up users' comprehension of interaction, particularly when a visualization representation has deficiencies in illustrating hidden items or relationships.
Selecting Semantically-Resonant Colors for Data Visualization
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Lin, Sharon; Fortuna, Julie; Kulkarni, Chinmay; Stone, Maureen; Heer, Jeffrey; B. Preim, P. Rheingans, and H. Theisel
We introduce an algorithm for automatic selection of semantically-resonant colors to represent data (e.g., using blue for data about ''oceans'', or pink for ''love''). Given a set of categorical values and a target color palette, our algorithm matches each data value with a unique color. Values are mapped to colors by collecting representative images, analyzing image color distributions to determine value-color affinity scores, and choosing an optimal assignment. Our affinity score balances the probability of a color with how well it discriminates among data values. A controlled study shows that expert-chosen semantically-resonant colors improve speed on chart reading tasks compared to a standard palette, and that our algorithm selects colors that lead to similar gains. A second study verifies that our algorithm effectively selects colors across a variety of data categories.
imMens: Real-time Visual Querying of Big Data
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Liu, Zhicheng; Jiang, Biye; Heer, Jeffrey; B. Preim, P. Rheingans, and H. Theisel
Data analysts must make sense of increasingly large data sets, sometimes with billions or more records.We present methods for interactive visualization of big data, following the principle that perceptual and interactive scalability should be limited by the chosen resolution of the visualized data, not the number of records. We first describe a design space of scalable visual summaries that use data reduction methods (such as binned aggregation or sampling) to visualize a variety of data types. We then contribute methods for interactive querying (e.g., brushing & linking) among binned plots through a combination of multivariate data tiles and parallel query processing. We implement our techniques in imMens, a browser-based visual analysis system that uses WebGL for data processing and rendering on the GPU. In benchmarks imMens sustains 50 frames-per-second brushing & linking among dozens of visualizations, with invariant performance on data sizes ranging from thousands to billions of records.
An Information-Theoretic Observation Channel for Volume Visualization
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Bramon, Roger; Ruiz, Marc; Bardera, Anton; Boada, Imma; Feixas, Miquel; Sbert, Mateu; B. Preim, P. Rheingans, and H. Theisel
Different quality metrics have been proposed in the literature to evaluate how well a visualization represents the underlying data. In this paper, we present a new information-theoretic framework that quantifies the information transfer between the source data set and the rendered image. This approach is based on the definition of an observation channel whose input and output are given by the intensity values of the volumetric data set and the pixel colors, respectively. From this channel, the mutual information, a measure of information transfer or correlation between the input and the output, is used as a metric to evaluate the visualization quality. The usefulness of the proposed observation channel is illustrated with three fundamental visualization applications: selection of informative viewpoints, transfer function design, and light positioning.
ExPlates: Spatializing Interactive Analysis to Scaffold Visual Exploration
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Javed, Waqas; Elmqvist, Niklas; B. Preim, P. Rheingans, and H. Theisel
Visual exploration involves using visual representations to investigate data where the goals of the process are unclear and poorly defined. However, this often places unduly high cognitive load on the user, particularly in terms of keeping track of multiple investigative branches, remembering earlier results, and correlating between different views. We propose a new methodology for automatically spatializing the individual steps in visual exploration onto a large visual canvas, allowing users to easily recall, reflect, and assess their progress. We also present a webbased implementation of our methodology called EXPLATESJS where users can manipulate multidimensional data in their browsers, automatically building visual queries as they explore the data.
Visual Explanation of the Complexity in Julia Sets
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Schrijvers, Okke; Wijk, Jarke J. van; B. Preim, P. Rheingans, and H. Theisel
Julia sets based on quadratic polynomials have a very simple definition, yet a highly intricate shape. Our contribution is to provide a visual explanation for this complexity. To this end we show the construction of Julia sets as a dynamic process, in contrast to showing just a static image of the set itself. Our method is based on the Inverse Iteration Method (IIM). We start with a disk, which is successively distorted. The crucial step is to show an animation of the effect of taking a root of a subset of the complex plane. We present four different approaches for this, using a Riemann surface, a corkscrew, a fan, and disks as metaphors. We packaged our results in an interactive tool with a simple interface, such that everybody can view and inspect these for different Julia sets. The results are useful for teaching complex analysis, promoting mathematics, entertainment, and, above all, as a visual explanation for the complexity of Julia sets.
TrajectoryLenses - A Set-based Filtering and Exploration Technique for Long-term Trajectory Data
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Krüger, Robert; Thom, Dennis; Wörner, Michael; Bosch, Harald; Ertl, Thomas; B. Preim, P. Rheingans, and H. Theisel
The visual analysis of spatiotemporal movement is a challenging task. There may be millions of routes of different length and shape with different origin and destination, extending over a long time span. Furthermore there can be various correlated attributes depending on the data domain, e.g. engine measurements for mobility data or sensor data for animal tracking. Visualizing such data tends to produce cluttered and incomprehensible images that need to be accompanied by sophisticated filtering methods. We present TrajectoryLenses, an interaction technique that extends the exploration lens metaphor to support complex filter expressions and the analysis of long time periods. Analysts might be interested only in movements that occur in a given time range, traverse a certain region, or end at a given area of interest (AOI). Our lenses can be placed on an interactive map to identify such geospatial AOIs. They can be grouped with set operations to create powerful geospatial queries. For each group of lenses, users can access aggregated data for different attributes like the number of matching movements, covered time, or vehicle performance. We demonstrate the applicability of our technique on a large, real-world dataset of electric scooter tracks spanning a 2-year period.
ViviSection: Skeleton-based Volume Editing
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Karimov, Alexey; Mistelbauer, Gabriel; Schmidt, Johanna; Mindek, Peter; Schmidt, Elisabeth; Sharipov, Timur; Bruckner, Stefan; Gröller, Eduard; B. Preim, P. Rheingans, and H. Theisel
Volume segmentation is important in many applications, particularly in the medical domain. Most segmentation techniques, however, work fully automatically only in very restricted scenarios and cumbersome manual editing of the results is a common task. In this paper, we introduce a novel approach for the editing of segmentation results. Our method exploits structural features of the segmented object to enable intuitive and robust correction and verification. We demonstrate that our new approach can significantly increase the segmentation quality even in difficult cases such as in the presence of severe pathologies.
Synthetic Brainbows
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Wan, Yong; Otsuna, Hideo; Hansen, Charles; B. Preim, P. Rheingans, and H. Theisel
Brainbow is a genetic engineering technique that randomly colorizes cells. Biological samples processed with this technique and imaged with confocal microscopy have distinctive colors for individual cells. Complex cellular structures can then be easily visualized. However, the complexity of the Brainbow technique limits its applications. In practice, most confocal microscopy scans use different florescence staining with typically at most three distinct cellular structures. These structures are often packed and obscure each other in rendered images making analysis difficult. In this paper, we leverage a process known as GPU framebuffer feedback loops to synthesize Brainbow-like images. In addition, we incorporate ID shuffling and Monte-Carlo sampling into our technique, so that it can be applied to single-channel confocal microscopy data. The synthesized Brainbow images are presented to domain experts with positive feedback. A user survey demonstrates that our synthetic Brainbow technique improves visualizations of volume data with complex structures for biologists.
Interactive Ray Casting of Geodesic Grids
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Xie, Jinrong; Yu, Hongfeng; Ma, Kwan-Liu; B. Preim, P. Rheingans, and H. Theisel
Geodesic grids are commonly used to model the surface of a sphere and are widely applied in numerical simulations of geoscience applications. These applications range from biodiversity, to climate change and to ocean circulation. Direct volume rendering of scalar fields defined on a geodesic grid facilitates scientists in visually understanding their large scale data. Previous solutions requiring to first transform the geodesic grid into another grid structure (e.g., hexahedral or tetrahedral grid) for using graphics hardware are not acceptable for large data, because such approaches incur significant computing and storage overhead. In this paper, we present a new method for efficient ray casting of geodesic girds by leveraging the power of Graphics Processing Units (GPUs). A geodesic grid can be directly fetched from storage or streamed from simulations to the rendering stage without the need of any intermediate grid transformation. We have designed and implemented a new analytic scheme to efficiently perform value interpolation for ray integration and gradient calculations for lighting. This scheme offers a more cost-effective rendering solution over the existing direct rendering approach. We demonstrate the effectiveness of our rendering solution using real-world geoscience data.

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