EuroVis12: Eurographics Conference on Visualization

Permanent URI for this collection

https://diglib.eg.org/handle/10.2312/393

Preface and Table of Contents

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Computing Voronoi Treemaps: Faster, Simpler, and Resolution-independent

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Nocaj, Arlind

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Brandes, Ulrik

Graph Bundling by Kernel Density Estimation

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Hurter, Christophe

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Ersoy, Ozan

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Telea, Alex

Kelp Diagrams: Point Set Membership Visualization

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Dinkla, Kasper

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Kreveld, Marc van

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Speckmann, Bettina

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Westenberg, Michel A.

Interactive Visualization of Generalized Virtual 3D City Models using Level-of-Abstraction Transitions

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Semmo, Amir

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Trapp, Matthias

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Kyprianidis, Jan Eric

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Döllner, Jürgen

Illustrative Membrane Clipping

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Birkeland, Åsmund

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Bruckner, Stefan

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Brambilla, Andrea

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Viola, Ivan

Multi-layer Illustrative Dense Flow Visualization

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Carnecky, Robert

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Schindler, Benjamin

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Fuchs, Raphael

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Peikert, Ronald

Scalable Detection of Spatiotemporal Encounters in Historical Movement Data

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Bak, Peter

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Marder, Mattias

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Harary, Sivan

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Yaeli, Avi

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Ship, Harold J.

Travel-Route-Centered Metro Map Layout and Annotation

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Wu, Hsiang-Yun

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Takahashi, Shigeo

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Lin, Chun-Cheng

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Yen, Hsu-Chun

A Quantized Boundary Representation of 2D Flows

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Levine, Joshua

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Jadhav, Shreeraj

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Bhatia, Harsh

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Pascucci, Valerio

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Bremer, Peer-Timo

The World's Languages Explorer: Visual Analysis of Language Features in Genealogical and Areal Contexts

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Rohrdantz, Christian

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Hund, Michael

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Mayer, Thomas

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Wälchli, Bernhard

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Keim, Daniel A.

Magnetic Flux Topology of 2D Point Dipoles

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Bachthaler, Sven

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Sadlo, Filip

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Weeber, Rudolf

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Kantorovich, Sofia

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Holm, Christian

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Weiskopf, Daniel

Drawing Large Graphs by Low-Rank Stress Majorization

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Khoury, Marc

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Hu, Yifan

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Krishnan, Shankar

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Scheidegger, Carlos

Comparative Evaluation of an Interactive Time-Series Visualization that Combines Quantitative Data with Qualitative Abstractions

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Aigner, Wolfgang

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Rind, Alexander

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Hoffmann, Stephan

Parallel Computation of 3D Morse-Smale Complexes

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Shivashankar, Nithin

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Natarajan, Vijay

Using Signposts for Navigation in Large Graphs

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May, Thorsten

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Steiger, Martin

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Davey, James

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Kohlhammer, Jörn

Conceptualizing Visual Uncertainty in Parallel Coordinates

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Dasgupta, Aritra

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Chen, Min

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Kosara, Robert

A Qualitative Study on the Exploration of Temporal Changes in Flow Maps with Animation and Small-Multiples

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Boyandin, Ilya

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Bertini, Enrico

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Lalanne, Denis

Visualization of Global Correlation Structures in Uncertain 2D Scalar Fields

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Pfaffelmoser, Tobias

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Westermann, Rüdiger

Vortex Analysis in Uncertain Vector Fields

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Otto, Mathias

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Theisel, Holger

Probabilistic Local Features in Uncertain Vector Fields with Spatial Correlation

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Petz, Christoph

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Pöthkow, Kai

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Hege, Hans-Christian

Visualization of 4D Blood-Flow Fields by Spatiotemporal Hierarchical Clustering

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Pelt, Roy van

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Jacobs, Sander

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Romeny, Bart ter Haar

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Vilanova, Anna

Reliable Adaptive Modelling of Vascular Structures with Non-Circular Cross-Sections

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Kretschmer, Jan

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Beck, Thomas

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Tietjen, Christian

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Preim, Bernhard

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Stamminger, Marc

Employing 2D Projections for Fast Visual Exploration of Large Fiber Tracking Data

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Poco, Jorge

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Eler, Danilo M.

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Paulovich, Fernando

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Minghim, Rosane

Biopsy Planner - Visual Analysis for Needle Pathway Planning in Deep Seated Brain Tumor Biopsy

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Herghelegiu, Paul-Corneliu

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Manta, Vasile-Ion

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Perin, Radu

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Bruckner, Stefan

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Gröller, Eduard

Automatic Stream Surface Seeding: A Feature Centered Approach

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Edmunds, Matt

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Laramee, Robert S.

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Malki, Rami

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Masters, Ian

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Croft, Nick

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Chen, Guoning

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Zhang, Eugene

Visualization of Advection-Diffusion in Unsteady Fluid Flow

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Karch, Grzegorz Karol

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Sadlo, Filip

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Weiskopf, Daniel

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Munz, Claus-Dieter

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Ertl, Thomas

Nearly Recurrent Components in 3D Piecewise Constant Vector Fields

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Szymczak, Andrzej

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Brunhart-Lupo, Nicholas

Rolled-out Wordles: A Heuristic Method for Overlap Removal of 2D Data Representatives

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Strobelt, Hendrik

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Spicker, Marc

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Stoffel, Andreas

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Keim, Daniel

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Deussen, Oliver

Interface Exchange as an Indicator for Eddy Heat Transport

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Williams, Sean

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Petersen, Mark

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Hecht, Matthew

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Maltrud, Mathew

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Patchett, John

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Ahrens, James

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Hamann, Bernd

Semantic Wordification of Document Collections

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Paulovich, Fernando V.

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Toledo, Franklina M. B.

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Telles, Guilherme P.

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Minghim, Rosane

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Nonato, Luis Gustavo

Document Thumbnails with Variable Text Scaling

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Stoffel, Andreas

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Strobelt, Hendrik

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Deussen, Oliver

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Keim, Daniel A.

iVisClustering: An Interactive Visual Document Clustering via Topic Modeling

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Lee, Hanseung

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Kihm, Jaeyeon

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Choo, Jaegul

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Stasko, John

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Park, Haesun

StratomeX: Visual Analysis of Large-Scale Heterogeneous Genomics Data for Cancer Subtype Characterization

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Lex, Alexander

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Streit, Marc

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Schulz, Hans-Joerg

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Partl, Christian

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Schmalstieg, Dieter

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Park, Peter J.

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Gehlenborg, Nils

Porosity Maps - Interactive Exploration and Visual Analysis of Porosity in Carbon Fiber Reinforced Polymers

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Reh, Andreas

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Plank, Bernhard

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Kastner, Johann

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Gröller, M. Eduard

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Heinzl, Christoph

Comparative Visual Analysis of 2D Function Ensembles

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Piringer, Harald

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Pajer, Stephan

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Berger, Wolfgang

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Teichmann, Heike

Perception of Animated Node-Link Diagrams for Dynamic Graphs

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Ghani, Sohaib

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Elmqvist, Niklas

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Yi, Ji Soo

Visualizing Motion Data in Virtual Reality: Understanding the Roles of Animation, Interaction, and Static Presentation

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Coffey, Dane

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Korsakov, Fedor

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Ewert, Marcus

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Hagh-Shenas, Heleh

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Thorson, Lauren

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Ellingson, Arin

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Nuckley, David

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Keefe, Daniel

A Design Study of Direct-Touch Interaction for Exploratory 3D Scientific Visualization

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Klein, Tijmen

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Guéniat, Florimond

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Pastur, Luc

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Vernier, Frédéric

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Isenberg, Tobias

Vismon: Facilitating Analysis of Trade-Offs, Uncertainty, and Sensitivity In Fisheries Management Decision Making

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Booshehrian, Maryam

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Möller, Torsten

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Peterman, Randall M.

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Munzner, Tamara

MarketAnalyzer: An Interactive Visual Analytics System for Analyzing Competitive Advantage Using Point of Sale Data

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Ko, Sungahn

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Maciejewski, Ross

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Jang, Yun

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Ebert, David S.

MatchPad: Interactive Glyph-Based Visualization for Real-Time Sports Performance Analysis

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Legg, Philip

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Chung, David H. S.

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Parry, Matthew L.

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Jones, Mark W.

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Long, Rhys

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Griffiths, Iwan W.

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Chen, Min

PORGY: A Visual Graph Rewriting Environment for Complex Systems

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Pinaud, Bruno

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Melançon, Guy

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Dubois, Jonathan

I-SI: Scalable Architecture of Analyzing Latent Topical-Level Information From Social Media Data

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Wang, Xiaoyu

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Dou, Wenwen

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Ma, Zhiqiang

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Villalobos, Jeremy

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Chen, Yang

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Kraft, Thomas

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Ribarsky, William

ConnectedCharts: Explicit Visualization of Relationships between Data Graphics

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Viau, Christophe

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McGuffin, Michael

Automating Transfer Function Design with Valley Cell-Based Clustering of 2D Density Plots

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Wang, Yunhai

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Zhang, Jian

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Lehmann, Dirk J.

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Theisel, Holger

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Chi, Xuebin

Importance Driven Automatic Color Design for Direct Volume Rendering

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Wang, Lei

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Kaufman, Arie

COVRA: A Compression-domain Output-sensitive Volume Rendering Architecture Based on a Sparse Representation of Voxel Blocks

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Gobbetti, Enrico

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Guitian, José Antonio Iglesias

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Marton, Fabio

Interactive Rendering of Materials and Biological Structures on Atomic and Nanoscopic Scale

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Lindow, Norbert

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Baum, Daniel

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Hege, Hans-Christian

A Taxonomy of Visual Cluster Separation Factors

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Sedlmair, Michael

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Tatu, Andrada

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Munzner, Tamara

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Tory, Melanie

Semi-Supervised Dimensionality Reduction based on Partial Least Squares for Visual Analysis of High Dimensional Data

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Paiva, Jose Gustavo S.

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Schwartz, William Robson

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Pedrini, Helio

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Minghim, Rosane

Procedural Texture Synthesis for Zoom-Independent Visualization of Multivariate Data

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Khlebnikov, Rostislav

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Kainz, Bernhard

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Steinberger, Markus

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Streit, Marc

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Schmalstieg, Dieter

Tracing Tuples Across Dimensions: A Comparison of Scatterplots and Parallel Coordinate Plots

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Kuang, Xiaole

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Zhang, Haimo

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Zhao, Shengdong

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McGuffin, Michael J.

Browse

Now showing 1 - 53 of 53

Preface and Table of Contents
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Stefan Bruckner and Silvia Miksch and Hanspeter Pfister
Computing Voronoi Treemaps: Faster, Simpler, and Resolution-independent
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Nocaj, Arlind; Brandes, Ulrik; S. Bruckner, S. Miksch, and H. Pfister
Voronoi treemaps represent hierarchies as nested polygons. We here show that, contrary to the apparent popular belief, utilization of an algorithm for weighted Voronoi diagrams is not only feasible, but also more efficient than previous low-resolution approximations, even when the latter are implemented on graphics hardware. More precisely, we propose an instantiation of Lloyd's method for centroidal Voronoi diagrams with Aurenhammer's algorithm for power diagrams that yields an algorithm running in O(n log n) rather than Ω(n2) time per iteration, with n the number of sites. We describe its implementation and present evidence that it is faster also in practice.
Graph Bundling by Kernel Density Estimation
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Hurter, Christophe; Ersoy, Ozan; Telea, Alex; S. Bruckner, S. Miksch, and H. Pfister
We present a fast and simple method to compute bundled layouts of general graphs. For this, we first transform a given graph drawing into a density map using kernel density estimation. Next, we apply an image sharpening technique which progressively merges local height maxima by moving the convolved graph edges into the height gradient flow. Our technique can be easily and efficiently implemented using standard graphics acceleration techniques and produces graph bundlings of similar appearance and quality to state-of-the-art methods at a fraction of the cost. Additionally, we show how to create bundled layouts constrained by obstacles and use shading to convey information on the bundling quality. We demonstrate our method on several large graphs.
Kelp Diagrams: Point Set Membership Visualization
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Dinkla, Kasper; Kreveld, Marc van; Speckmann, Bettina; Westenberg, Michel A.; S. Bruckner, S. Miksch, and H. Pfister
We present Kelp Diagrams, a novel method to depict set relations over points, i.e., elements with predefined positions. Our method creates schematic drawings and has been designed to take aesthetic quality, efficiency, and effectiveness into account. This is achieved by a routing algorithm, which links elements that are part of the same set by constructing minimum cost paths over a tangent visibility graph. There are two styles of Kelp Diagrams to depict overlapping sets, a nested and a striped style, each with its own strengths and weaknesses.We compare Kelp Diagrams with two existing methods and show that our approach provides a more consistent and clear depiction of both element locations and their set relations
Interactive Visualization of Generalized Virtual 3D City Models using Level-of-Abstraction Transitions
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Semmo, Amir; Trapp, Matthias; Kyprianidis, Jan Eric; Döllner, Jürgen; S. Bruckner, S. Miksch, and H. Pfister
Virtual 3D city models play an important role in the communication of complex geospatial information in a growing number of applications, such as urban planning, navigation, tourist information, and disaster management. In general, homogeneous graphic styles are used for visualization. For instance, photorealism is suitable for detailed presentations, and non-photorealism or abstract stylization is used to facilitate guidance of a viewer's gaze to prioritized information. However, to adapt visualization to different contexts and contents and to support saliencyguided visualization based on user interaction or dynamically changing thematic information, a combination of different graphic styles is necessary. Design and implementation of such combined graphic styles pose a number of challenges, specifically from the perspective of real-time 3D visualization. In this paper, the authors present a concept and an implementation of a system that enables different presentation styles, their seamless integration within a single view, and parametrized transitions between them, which are defined according to tasks, camera view, and image resolution. The paper outlines potential usage scenarios and application fields together with a performance evaluation of the implementation.
Illustrative Membrane Clipping
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Birkeland, Åsmund; Bruckner, Stefan; Brambilla, Andrea; Viola, Ivan; S. Bruckner, S. Miksch, and H. Pfister
Clipping is a fast, common technique for resolving occlusions. It only requires simple interaction, is easily understandable, and thus has been very popular for volume exploration. However, a drawback of clipping is that the technique indiscriminately cuts through features. Illustrators, for example, consider the structures in the vicinity of the cut when visualizing complex spatial data and make sure that smaller structures near the clipping plane are kept in the image and not cut into fragments. In this paper we present a new technique, which combines the simple clipping interaction with automated selective feature preservation using an elastic membrane. In order to prevent cutting objects near the clipping plane, the deformable membrane uses underlying data properties to adjust itself to salient structures. To achieve this behaviour, we translate data attributes into a potential field which acts on the membrane, thus moving the problem of deformation into the soft-body dynamics domain. This allows us to exploit existing GPU-based physics libraries which achieve interactive frame rates. For manual adjustment, the user can insert additional potential fields, as well as pinning the membrane to interesting areas. We demonstrate that our method can act as a flexible and non-invasive replacement of traditional clipping planes.
Multi-layer Illustrative Dense Flow Visualization
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Carnecky, Robert; Schindler, Benjamin; Fuchs, Raphael; Peikert, Ronald; S. Bruckner, S. Miksch, and H. Pfister
We present a dense visualization of vector fields on multi-layered surfaces. The method is based on the illustration buffer, which provides a screen space representation of the surface, where each pixel stores a list of all surface layers. This representation is implemented on the GPU using shaders and leads to a fast, output sensitive technique. In our approach, we first use procedural noise to create an initial spot pattern on the surface that has both an almost constant screen space frequency and is view independent. Then, we perform anisotropic diffusion simultaneously on all surface layers using a discretization scheme that maintains second order convergence while only accessing the four neighboring pixels. Finally, we enhance this result with illustrative techniques and composite the final image. Our method works with time-evolving surfaces, time-dependent vector fields, and moving cameras. We apply our method to CFD data sets from engineering and astronomy as well as synthetic velocity fields.
Scalable Detection of Spatiotemporal Encounters in Historical Movement Data
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Bak, Peter; Marder, Mattias; Harary, Sivan; Yaeli, Avi; Ship, Harold J.; S. Bruckner, S. Miksch, and H. Pfister
The widespread adoption of location-aware devices is resulting in the generation of large amounts of spatiotemporal movement data, collected and stored in digital repositories. This forms a fertile ground for domain experts and scientists to analyze such historical data and discover interesting movement behavioral patterns. Experts in many domains, such as transportation, logistics and retail, are interested in detecting and understanding movement patterns and behavior of objects in relation to each other. Their insights can point to optimization potential and reveal deviations from planned behavior. In this paper, we focus on the detection of the encounter patterns as one possible type in movement behavior. These patterns refer to objects being close to one another in terms of space and time. We define scalability as a core requirement when dealing with historical movement data, in order to allow the domain expert to set parameters of the encounter detection algorithm. Our approach leverages a designated data structure and requires only a single pass over chronological data, thus resulting in highly scalable and fast technique to detect encounters. Consequently, users are able to explore their data by interactively specifying the spatial and temporal windows that define encounters. We evaluate our proposed method as a function of its input parameters and data size. We instantiate the proposed method on urban public transportation data, where we found a large number of encounters. We show that single encounters emerge into higher level patterns that are of particular interest and value to the domain.
Travel-Route-Centered Metro Map Layout and Annotation
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Wu, Hsiang-Yun; Takahashi, Shigeo; Lin, Chun-Cheng; Yen, Hsu-Chun; S. Bruckner, S. Miksch, and H. Pfister
When providing travel guides for a specific route in a metro network, we often place the route around the center of the map and annotate stations on the route with thumbnail photographs. Nonetheless, existing methods do not offer an effective means of customizing the network layout in order to accommodate such large annotation labels while preserving its planar embedding. This paper presents a new approach for designing the metro map layout in order to annotate stations on a specific travel route with large annotation labels. Our idea is to elongate the travel route to be straight along the centerline of the map so that we can systematically annotate such stations with external labels. This is accomplished by extending the conventional mixed-integer programming technique for computing octilinear layouts where orientations inherent to the metro line segments are plausibly rearranged. The stations are then connected with external labels through leaders while minimizing intersections with metro lines for enhancing visual clarity. We present several design examples of metro maps and user studies to demonstrate that the proposed aesthetic criteria successfully direct viewers' attention to specific travel routes.
A Quantized Boundary Representation of 2D Flows
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Levine, Joshua; Jadhav, Shreeraj; Bhatia, Harsh; Pascucci, Valerio; Bremer, Peer-Timo; S. Bruckner, S. Miksch, and H. Pfister
Analysis and visualization of complex vector fields remain major challenges when studying large scale simulation of physical phenomena. The primary reason is the gap between the concepts of smooth vector field theory and their computational realization. In practice, researchers must choose between either numerical techniques, with limited or no guarantees on how they preserve fundamental invariants, or discrete techniques which limit the precision at which the vector field can be represented. We propose a new representation of vector fields that combines the advantages of both approaches. In particular, we represent a subset of possible streamlines by storing their paths as they traverse the edges of a triangulation. Using only a finite set of streamlines creates a fully discrete version of a vector field that nevertheless approximates the smooth flow up to a user controlled error bound. The discrete nature of our representation enables us to directly compute and classify analogues of critical points, closed orbits, and other common topological structures. Further, by varying the number of divisions (quantizations) used per edge, we vary the resolution used to represent the field, allowing for controlled precision. This representation is compact in memory and supports standard vector field operations.
The World's Languages Explorer: Visual Analysis of Language Features in Genealogical and Areal Contexts
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Rohrdantz, Christian; Hund, Michael; Mayer, Thomas; Wälchli, Bernhard; Keim, Daniel A.; S. Bruckner, S. Miksch, and H. Pfister
This paper presents a novel Visual Analytics approach that helps linguistic researchers to explore the world's languages with respect to several important tasks: (1) The comparison of manually and automatically extracted language features across languages and within the context of language genealogy, (2) the exploration of interrelations among several of such features as well as their homogeneity and heterogeneity within subtrees of the language genealogy, and (3) the exploration of genealogical and areal influences on the features. We introduce the WORLD'S LANGUAGES EXPLORER, which provides the required functionalities in one single Visual Analytics environment. Contributions are made for different parts of the system: We introduce an extended Sunburst visualization whose so-called feature-rings allow for a cross-comparison of a large number of features at once, within the hierarchical context of the language genealogy. We suggest a mapping of homogeneity measures to all levels of the hierarchy. In addition, we suggest an integration of information from the areal data space into the hierarchical data space. With our approach we bring Visual Analytics research to a new application field, namely Historical Comparative Linguistics, and Linguistic and Areal Typology. Finally, we provide evidence of the good performance of our system in this area through two application case studies conducted by domain experts.
Magnetic Flux Topology of 2D Point Dipoles
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Bachthaler, Sven; Sadlo, Filip; Weeber, Rudolf; Kantorovich, Sofia; Holm, Christian; Weiskopf, Daniel; S. Bruckner, S. Miksch, and H. Pfister
Magnetic fields exhibit higher-order, nonlinear singularities in the form of point-dipole singularities. In addition, due to absence of divergence, they feature only a subset of invariant structures from traditional vector field topology. For magnetic fields of sets of point dipoles - widely present in physics and often used as an approximation - we present a technique revealing the topology of magnetic flux. The flux topology is identified with areas covered by field lines that directly connect pairs of dipoles. We introduce the dipole connectrix as a reduced one-manifold representation of those areas. The set of connectrices serves as our concise visualization of the global structure of magnetic flux. In addition, the quantitative values of flux are displayed by the thickness of the connectrices. We evaluate our technique for simulations of ferroparticle monolayers and magnetic gels.
Drawing Large Graphs by Low-Rank Stress Majorization
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Khoury, Marc; Hu, Yifan; Krishnan, Shankar; Scheidegger, Carlos; S. Bruckner, S. Miksch, and H. Pfister
Optimizing a stress model is a natural technique for drawing graphs: one seeks an embedding into Rd which best preserves the induced graph metric. Current approaches to solving the stress model for a graph with jVj nodes and jEj edges require the full all-pairs shortest paths (APSP) matrix, which takes O(jVj2 log jEj+jVjjEj) time and O(jVj2) space. We propose a novel algorithm based on a low-rank approximation to the required matrices. The crux of our technique is an observation that it is possible to approximate the full APSP matrix, even when only a small subset of its entries are known. Our algorithm takes time O(kjVj+jVj logjVj+jEj) per iteration with a preprocessing time of O(k3 +k(jEj+jVj logjVj)+k2jVj) and memory usage of O(kjVj), where a user-defined parameter k trades off quality of approximation with running time and space. We give experimental results which show, to the best of our knowledge, the largest (albeit approximate) full stress model based layouts to date.
Comparative Evaluation of an Interactive Time-Series Visualization that Combines Quantitative Data with Qualitative Abstractions
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Aigner, Wolfgang; Rind, Alexander; Hoffmann, Stephan; S. Bruckner, S. Miksch, and H. Pfister
In many application areas, analysts have to make sense of large volumes of multivariate time-series data. Explorative analysis of this kind of data is often difficult and overwhelming at the level of raw data. Temporal data abstraction reduces data complexity by deriving qualitative statements that reflect domain-specific key characteristics. Visual representations of abstractions and raw data together with appropriate interaction methods can support analysts in making their data easier to understand. Such a visualization technique that applies smooth semantic zooming has been developed in the context of patient data analysis. However, no empirical evidence on its effectiveness and efficiency is available. In this paper, we aim to fill this gap by reporting on a controlled experiment that compares this technique with another visualization method used in the well-known KNAVE-II framework. Both methods integrate quantitative data with qualitative abstractions whereas the first one uses a composite representation with color-coding to display the qualitative data and spatial position coding for the quantitative data. The second technique uses juxtaposed representations for quantitative and qualitative data with spatial position coding for both. Results show that the test persons using the composite representation were generally faster, particularly for more complex tasks that involve quantitative values as well as qualitative abstractions.
Parallel Computation of 3D Morse-Smale Complexes
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Shivashankar, Nithin; Natarajan, Vijay; S. Bruckner, S. Miksch, and H. Pfister
The Morse-Smale complex is a topological structure that captures the behavior of the gradient of a scalar function on a manifold. This paper discusses scalable techniques to compute the Morse-Smale complex of scalar functions defined on large three-dimensional structured grids. Computing the Morse-Smale complex of three-dimensional domains is challenging as compared to two-dimensional domains because of the non-trivial structure introduced by the two types of saddle criticalities. We present a parallel shared-memory algorithm to compute the Morse- Smale complex based on Forman's discrete Morse theory. The algorithm achieves scalability via synergistic use of the CPU and the GPU. We first prove that the discrete gradient on the domain can be computed independently for each cell and hence can be implemented on the GPU. Second, we describe a two-step graph traversal algorithm to compute the 1-saddle-2-saddle connections efficiently and in parallel on the CPU. Simultaneously, the extremasaddle connections are computed using a tree traversal algorithm on the GPU.
Using Signposts for Navigation in Large Graphs
(The Eurographics Association and Blackwell Publishing Ltd., 2012) May, Thorsten; Steiger, Martin; Davey, James; Kohlhammer, Jörn; S. Bruckner, S. Miksch, and H. Pfister
In this paper we present a new Focus & Context technique for the exploration of large, abstract graphs. Most Focus & Context techniques present context in a visual way. In contrast, our technique uses a symbolic representation: while the focus is a set of visible nodes, labelled signposts provide cues for the context - off-screen regions of the graph - and indicate the direction of the shortest path linking the visible nodes to these regions. We show how the regions are defined and how they are selected dynamically, depending on the visible nodes. To define the set of visible nodes we use an approach developed by van Ham and Perer that dynamically extracts a subgraph based on an initial focal node and a degree-of-interest function. This approach is extended to support multiple focal nodes. With the symbolic visualization, potentially interesting regions of a graph may be represented with a very small visual footprint. We conclude the paper with an initial user study to evaluate the effectiveness of the signposts for navigation tasks.
Conceptualizing Visual Uncertainty in Parallel Coordinates
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Dasgupta, Aritra; Chen, Min; Kosara, Robert; S. Bruckner, S. Miksch, and H. Pfister
Uncertainty is an intrinsic part of any visual representation in visualization, no matter how precise the input data. Existing research on uncertainty in visualization mainly focuses on depicting data-space uncertainty in a visual form. Uncertainty is thus often seen as a problem to deal with, in the data, and something to be avoided if possible. In this paper, we highlight the need for analyzing visual uncertainty in order to design more effective visual representations. We study various forms of uncertainty in the visual representation of parallel coordinates and propose a taxonomy for categorizing them. By building a taxonomy, we aim to identify different sources of uncertainty in the screen space and relate them to different effects of uncertainty upon the user. We examine the literature on parallel coordinates and apply our taxonomy to categorize various techniques for reducing uncertainty. In addition, we consider uncertainty from a different perspective by identifying cases where increasing certain forms of uncertainty may even be useful, with respect to task, data type and analysis scenario. This work suggests that uncertainty is a feature that can be both useful and problematic in visualization, and it is beneficial to augment an information visualization pipeline with a facility for visual uncertainty analysis.
A Qualitative Study on the Exploration of Temporal Changes in Flow Maps with Animation and Small-Multiples
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Boyandin, Ilya; Bertini, Enrico; Lalanne, Denis; S. Bruckner, S. Miksch, and H. Pfister
We present a qualitative user study analyzing findings made while exploring changes over time in spatial interactions. We analyzed findings made by the study participants with flow maps, one of the most popular representations of spatial interactions, using animation and small-multiples as two alternative ways of representing temporal changes. Our goal was not to measure the subjects' performance with the two views, but to find out whether there are qualitative differences between the types of findings users make with these two representations. To achieve this goal we performed a deep analysis of the collected findings, the interaction logs, and the subjective feedback from the users. We observed that with animation the subjects tended to make more findings concerning geographically local events and changes between subsequent years. With small-multiples more findings concerning longer time periods were made. Besides, our results suggest that switching from one view to the other might lead to an increase in the numbers of findings of specific types made by the subjects which can be beneficial for certain tasks.
Visualization of Global Correlation Structures in Uncertain 2D Scalar Fields
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Pfaffelmoser, Tobias; Westermann, Rüdiger; S. Bruckner, S. Miksch, and H. Pfister
Visualizing correlations, i.e., the tendency of uncertain data values at different spatial positions to change contrarily or according to each other, allows inferring on the possible variations of structures in the data. Visualizing global correlation structures, however, is extremely challenging, since it is not clear how the visualization of complicated long-range dependencies can be integrated into standard visualizations of spatial data. Furthermore, storing correlation information imposes a memory requirement that is quadratic in the number of spatial sample positions. This paper presents a novel approach for visualizing both positive and inverse global correlation structures in uncertain 2D scalar fields, where the uncertainty is modeled via a multivariate Gaussian distribution. We introduce a new measure for the degree of dependency of a random variable on its local and global surroundings, and we propose a spatial clustering approach based on this measure to classify regions of a particular correlation strength. The clustering performs a correlation filtering, which results in a representation that is only linear in the number of spatial sample points. Via cluster coloring the correlation information can be embedded into visualizations of other statistical quantities, such as the mean and the standard deviation. We finally propose a hierarchical cluster subdivision scheme to further allow for the simultaneous visualization of local and global correlations.
Vortex Analysis in Uncertain Vector Fields
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Otto, Mathias; Theisel, Holger; S. Bruckner, S. Miksch, and H. Pfister
We present an approach to extract and visualize vortex structures in uncertain vector fields. For this, we generalize the concepts of the most common vortex detectors to uncertain vector fields, namely the λ <sub>2</sub>-criterion, Q-criterion, and the concept of parallel vectors at the example of the method by Sujudi and Haimes. All these methods base on the computation of derivatives of the uncertain vector field which are uncertain fields as well. Since they generally cannot be computed in a closed form, we provide a Monte Carlo algorithm to compute the respective probability distributions. Based on this, uncertain versions of vortex regions and core structures are introduced. We present results of our approach on three real world data sets in order to give a proof of concept.
Probabilistic Local Features in Uncertain Vector Fields with Spatial Correlation
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Petz, Christoph; Pöthkow, Kai; Hege, Hans-Christian; S. Bruckner, S. Miksch, and H. Pfister
In this paper methods for extraction of local features in crisp vector fields are extended to uncertain fields. While in a crisp field local features are either present or absent at some location, in an uncertain field they are present with some probability. We model sampled uncertain vector fields by discrete Gaussian random fields with empirically estimated spatial correlations. The variability of the random fields in a spatial neighborhood is characterized by marginal distributions. Probabilities for the presence of local features are formulated in terms of low-dimensional integrals over such marginal distributions. Specifically, we define probabilistic equivalents for critical points and vortex cores. The probabilities are computed by Monte Carlo integration. For identification of critical points and cores of swirling motion we employ the Poincaré index and the criterion by Sujudi and Haimes. In contrast to previous global methods we take a local perspective and directly extract features in divergence-free fields as well. The method is able to detect saddle points in a straight forward way and works on various grid types. It is demonstrated by applying it to simulated unsteady flows of biofluid and climate dynamics.
Visualization of 4D Blood-Flow Fields by Spatiotemporal Hierarchical Clustering
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Pelt, Roy van; Jacobs, Sander; Romeny, Bart ter Haar; Vilanova, Anna; S. Bruckner, S. Miksch, and H. Pfister
Advancements in the acquisition and modeling of flow fields result in unsteady volumetric flow fields of unprecedented quality. An important example is found in the analysis of unsteady blood-flow data. Preclinical research strives for a better understanding of correlations between the hemodynamics and the progression of cardiovascular diseases. Modern-day computer models and MRI acquisition provide time-resolved volumetric blood-flow velocity fields. Unfortunately, these fields often remain unexplored, as high-dimensional data are difficult to conceive. We present a spatiotemporal, i.e., four-dimensional, hierarchical clustering, yielding a sparse representation of the velocity data. The clustering results underpin an illustrative visualization approach, facilitating visual analysis. The hierarchy allows an intuitive level-of-detail selection, largely retaining important flow patterns. The clustering employs dissimilarity measures to construct the hierarchy. We have adapted two existing measures for steady vector fields for use in the spacetime domain. Because of the inherent computational complexity of the multidimensional clustering, we introduce a coarse hierarchical clustering approach, which closely approximates the full hierarchy generation, and considerably improves the performance. The resulting clusters are visualized by representative patharrows, in combination with an illustrative anatomical context. We present various seeding approaches and visualization styles, providing sparse overviews of the unsteady behavior of volumetric flow fields.
Reliable Adaptive Modelling of Vascular Structures with Non-Circular Cross-Sections
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Kretschmer, Jan; Beck, Thomas; Tietjen, Christian; Preim, Bernhard; Stamminger, Marc; S. Bruckner, S. Miksch, and H. Pfister
Accurate visualizations of complex vascular structures are essential for medical applications, such as diagnosis, therapy planning and medical education. Vascular trees are usually described using centerlines, since they capture both the topology and the geometry of the vasculature in an intuitive manner. State-of-the-art vessel segmentation algorithms deliver vascular outlines as free-form contours along the centerline, since this allows capturing anatomical pathologies. However, existing methods for generating surface representations from centerlines can only cope with circular outlines. We present a novel model-based technique that is capable of generating intersection-free surfaces from centerlines with complex outlines. Vascular segments are described by local signed distance functions and combined using Boolean operations. An octree-based surface generation strategy automatically computes watertight, scale-adaptive meshes with a controllable quality. In contrast to other approaches, our method generates a reliable representation that guarantees to capture all vessels regardless of their size.
Employing 2D Projections for Fast Visual Exploration of Large Fiber Tracking Data
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Poco, Jorge; Eler, Danilo M.; Paulovich, Fernando; Minghim, Rosane; S. Bruckner, S. Miksch, and H. Pfister
Fiber tracts detection is an increasingly common technology for diagnosis and also understanding of brain function. Although tools for tracing and presenting brain fibers are advanced, it is still difficult for physicians or students to explore the dataset in 3D due to their intricate topology. In this work we present a visual exploration approach for fiber tracts data aimed at supporting exploration of such data. The work employs a local, precise and fast 2D multidimensional projection technique that allows a large number of fibers to be handled simultaneously and to select groups of bundled fibers for further exploration. In this approach, a DTI feature dataset, including curvature as well as spatial features, is projected on a 2D or 3D view. By handling groups formed in this view, exploration is linked to corresponding brain fibers in object space. The link exists in both directions and fibers selected in object space are also mapped to feature space. Our approach also allows users to modify the projection, controlling and improving, if necessary, the definition of groups of fibers for small and large datasets, due to the local nature of the projection. Compared to other related work, the method presented here is faster for creating visual representations, making it possible to explore complete sets of fibers tracts up to 250K fibers, which was not possible previously. Additionally, the ability to change configuration of the feature space representation adds a high degree of flexibility to the process.
Biopsy Planner - Visual Analysis for Needle Pathway Planning in Deep Seated Brain Tumor Biopsy
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Herghelegiu, Paul-Corneliu; Manta, Vasile-Ion; Perin, Radu; Bruckner, Stefan; Gröller, Eduard; S. Bruckner, S. Miksch, and H. Pfister
Biopsies involve taking samples from living tissue using a biopsy needle. In current clinical practice they are a first mandatory step before any further medical actions are planned. Performing a biopsy on a deep seated brain tumor requires considerable time for establishing and validating the desired biopsy needle pathway to avoid damage. In this paper, we present a system for the visualization, analysis, and validation of biopsy needle pathways. Our system uses a multi-level approach for identifying stable needle placements which minimize the risk of hitting blood vessels. This is one of the major dangers in this type of intervention. Our approach helps in identifying and visualizing the point on the pathway that is closest to a surrounding blood vessel, requiring a closer inspection by the neurosurgeon. An evaluation by medical experts is performed to demonstrate the utility of our system.
Automatic Stream Surface Seeding: A Feature Centered Approach
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Edmunds, Matt; Laramee, Robert S.; Malki, Rami; Masters, Ian; Croft, Nick; Chen, Guoning; Zhang, Eugene; S. Bruckner, S. Miksch, and H. Pfister
The ability to capture and visualize information within the flow poses challenges for visualizing 3D flow fields. Stream surfaces are one of many useful integration based techniques for visualizing 3D flow. However seeding integral surfaces can be challenging. Previous research generally focuses on manual placement of stream surfaces. Little attention has been given to the problem of automatic stream surface seeding. This paper introduces a novel automatic stream surface seeding strategy based on vector field clustering. It is important that the user can define and target particular characteristics of the flow. Our framework provides this ability. The user is able to specify different vector clustering parameters enabling a range of abstraction for the density and placement of seeding curves and their associated stream surfaces. We demonstrate the effectiveness of this automatic stream surface approach on a range of flow simulations and incorporate illustrative visualization techniques. Domain expert evaluation of the results provides valuable insight into the users requirements and effectiveness of our approach.
Visualization of Advection-Diffusion in Unsteady Fluid Flow
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Karch, Grzegorz Karol; Sadlo, Filip; Weiskopf, Daniel; Munz, Claus-Dieter; Ertl, Thomas; S. Bruckner, S. Miksch, and H. Pfister
Advection has been the standard transport mechanism in flow visualization. Diffusion, in contrast, has not been considered important in visual flow field analysis so far, although it is inherent to many physical processes. We present a novel technique that allows for interactive 3D visualization of both advection and diffusion in unsteady fluid flow. We extend texture-based flow visualization, which is advection-oriented, by diffusion. Our finite volume approach based on WENO (weighted essentially non-oscillatory) reconstruction is well parallelizable and features low numerical diffusion at interactive rates. Our scheme contributes to three different applications: (a) highquality dye advection at low numerical diffusion, (b) physically-based dye advection accounting for diffusivity of virtual media, and (c) visualization of advection-diffusion fluxes in physical media where the velocity field is accompanied by a concentration field. Interactive rendering of the virtual dye is accomplished by ray casting. We apply our GPU implementation to CFD examples of thermal convection and evaporation phenomena.
Nearly Recurrent Components in 3D Piecewise Constant Vector Fields
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Szymczak, Andrzej; Brunhart-Lupo, Nicholas; S. Bruckner, S. Miksch, and H. Pfister
We present an algorithm for computing nearly recurrent components, that represent areas of close to circulating or stagnant flow, for 3D piecewise constant (PC) vector fields defined on regular grids. Using a number of analytical and simulated data sets, we demonstrate that nearly recurrent components can provide interesting insight into the topological structure of 3D vector fields. Our approach is based on prior work on Morse decompositions for PC vector fields on surfaces and extends concepts previously developed with this goal in mind to the case of 3D vector fields defined on regular grids. Our contributions include a description of trajectories of 3D piecewise constant vector fields and an extension of the transition graph, a finite directed graph that represents all trajectories, to the 3D case. Nearly recurrent components are defined by strongly connected components of the transition graph.
Rolled-out Wordles: A Heuristic Method for Overlap Removal of 2D Data Representatives
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Strobelt, Hendrik; Spicker, Marc; Stoffel, Andreas; Keim, Daniel; Deussen, Oliver; S. Bruckner, S. Miksch, and H. Pfister
When representing 2D data points with spacious objects such as labels, overlap can occur. We present a simple algorithm which modifies the (Mani-)Wordle idea with scan-line based techniques to allow a better placement. We give an introduction to common placement techniques from different fields and compare our method to these techniques w.r.t. euclidean displacement, changes in orthogonal ordering as well as shape and size preservation. Especially in dense scenarios our method preserves the overall shape better than known techniques and allows a good trade-off between the other measures. Applications on real world data are given and discussed.
Interface Exchange as an Indicator for Eddy Heat Transport
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Williams, Sean; Petersen, Mark; Hecht, Matthew; Maltrud, Mathew; Patchett, John; Ahrens, James; Hamann, Bernd; S. Bruckner, S. Miksch, and H. Pfister
The ocean contains many large-scale, long-lived vortices, called mesoscale eddies, that are believed to have a role in the transport and redistribution of salt, heat, and nutrients throughout the ocean. Determining this role, however, has proven to be a challenge, since the mechanics of eddies are only partly understood; a standard definition for these ocean eddies does not exist and, therefore, scientifically meaningful, robust methods for eddy extraction, characterization, tracking and visualization remain a challenge. To shed light on the nature and potential roles of eddies, we extend our previous work on eddy identification and tracking to construct a new metric to characterize the transfer of water into and out of eddies across their boundary, and produce several visualizations of this new metric to provide clues about the role eddies play in the global ocean.
Semantic Wordification of Document Collections
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Paulovich, Fernando V.; Toledo, Franklina M. B.; Telles, Guilherme P.; Minghim, Rosane; Nonato, Luis Gustavo; S. Bruckner, S. Miksch, and H. Pfister
Word clouds have become one of the most widely accepted visual resources for document analysis and visualization, motivating the development of several methods for building layouts of keywords extracted from textual data. Existing methods are effective to demonstrate content, but are not capable of preserving semantic relationships among keywords while still linking the word cloud to the underlying document groups that generated them. Such representation is highly desirable for exploratory analysis of document collections. In this paper we present a novel approach to build document clouds, named ProjCloud that aim at solving both semantical layouts and linking with document sets. ProjCloud generates a semantically consistent layout from a set of documents. Through a multidimensional projection, it is possible to visualize the neighborhood relationship between highly related documents and their corresponding word clouds simultaneously. Additionally, we propose a new algorithm for building word clouds inside polygons, which employs spectral sorting to maintain the semantic relationship among words. The effectiveness and flexibility of our methodology is confirmed when comparisons are made to existing methods. The technique automatically constructs projection based layouts the user may choose to examine in the form of the point clouds or corresponding word clouds, allowing a high degree of control over the exploratory process.
Document Thumbnails with Variable Text Scaling
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Stoffel, Andreas; Strobelt, Hendrik; Deussen, Oliver; Keim, Daniel A.; S. Bruckner, S. Miksch, and H. Pfister
Document reader applications usually offer an overview of the layout for each page as thumbnail views. Reading the text in these becomes impossible when the font size becomes very small. We improve the readability of these thumbnails using a distortion method, which retains a readable font size of interesting text while shrinking less interesting text further. In contrast to existing approaches, our method preserves the global layout of a page and is able to show context around important terms. We evaluate our technique and show application examples.
iVisClustering: An Interactive Visual Document Clustering via Topic Modeling
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Lee, Hanseung; Kihm, Jaeyeon; Choo, Jaegul; Stasko, John; Park, Haesun; S. Bruckner, S. Miksch, and H. Pfister
Clustering plays an important role in many large-scale data analyses providing users with an overall understand- ing of their data. Nonetheless, clustering is not an easy task due to noisy features and outliers existing in the data, and thus the clustering results obtained from automatic algorithms often do not make clear sense. To remedy this problem, automatic clustering should be complemented with interactive visualization strategies. This paper proposes an interactive visual analytics system for document clustering, called iVisClustering, based on a widely- used topic modeling method, latent Dirichlet allocation (LDA). iVisClustering provides a summary of each cluster in terms of its most representative keywords and visualizes soft clustering results in parallel coordinates. The main view of the system provides a 2D plot that visualizes cluster similarities and the relation among data items with a graph-based representation. iVisClustering provides several other views, which contain useful interaction methods. With help of these visualization modules, we can interactively refine the clustering results in various ways. Keywords can be adjusted so that they characterize each cluster better. In addition, our system can filter out noisy data and re-cluster the data accordingly. Cluster hierarchy can be constructed using a tree structure and for this purpose, the system supports cluster-level interactions such as sub-clustering, removing unimportant clusters, merging the clusters that have similar meanings, and moving certain clusters to any other node in the tree structure. Furthermore, the system provides document-level interactions such as moving mis-clustered documents to another cluster and removing useless documents. Finally, we present how interactive clustering is performed via iVisClustering by using real-world document data sets.
StratomeX: Visual Analysis of Large-Scale Heterogeneous Genomics Data for Cancer Subtype Characterization
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Lex, Alexander; Streit, Marc; Schulz, Hans-Joerg; Partl, Christian; Schmalstieg, Dieter; Park, Peter J.; Gehlenborg, Nils; S. Bruckner, S. Miksch, and H. Pfister
Identification and characterization of cancer subtypes are important areas of research that are based on the integrated analysis of multiple heterogeneous genomics datasets. Since there are no tools supporting this process, much of this work is done using ad-hoc scripts and static plots, which is inefficient and limits visual exploration of the data. To address this, we have developed StratomeX, an integrative visualization tool that allows investigators to explore the relationships of candidate subtypes across multiple genomic data types such as gene expression, DNA methylation, or copy number data. StratomeX represents datasets as columns and subtypes as bricks in these columns. Ribbons between the columns connect bricks to show subtype relationships across datasets. Drill-down features enable detailed exploration. StratomeX provides insights into the functional and clinical implications of candidate subtypes by employing small multiples, which allow investigators to assess the effect of subtypes on molecular pathways or outcomes such as patient survival. As the configuration of viewing parameters in such a multi-dataset, multi-view scenario is complex, we propose a meta visualization and configuration interface for dataset dependencies and data-view relationships. StratomeX is developed in close collaboration with domain experts.We describe case studies that illustrate how investigators used the tool to explore subtypes in large datasets and demonstrate how they efficiently replicated findings from the literature and gained new insights into the data.
Porosity Maps - Interactive Exploration and Visual Analysis of Porosity in Carbon Fiber Reinforced Polymers
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Reh, Andreas; Plank, Bernhard; Kastner, Johann; Gröller, M. Eduard; Heinzl, Christoph; S. Bruckner, S. Miksch, and H. Pfister
In this work a novel method for the characterization of porosity in carbon fiber reinforced polymers (CFRP) is presented. A visualization pipeline for the interactive exploration and visual analysis of CFRP specimens is developed to enhance the evaluation workflow for non-destructive testing (NDT) practitioners based on specified tasks. Besides quantitative porosity determination and the calculation of local pore properties, i.e., volume, surface, dimensions and shape factors, we employ a drill-down approach to explore pores in a CFRP specimen. We introduce Porosity Maps (PM), to allow for a fast porosity evaluation of the specimen. Pores are filtered in two stages. First a region of interest is selected in the porosity maps. Second, pores are filtered with parallel coordinates according to their local properties. Furthermore a histogram-based best-viewpoint widget was implemented to visualize the quality of viewpoints on a sphere. The advantages of our approach are demonstrated using real world CFRP specimens. We are able to show that our visualization-driven approach leads to a better evaluation of CFRP components than existing reference methods.
Comparative Visual Analysis of 2D Function Ensembles
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Piringer, Harald; Pajer, Stephan; Berger, Wolfgang; Teichmann, Heike; S. Bruckner, S. Miksch, and H. Pfister
In the development process of powertrain systems, 2D function ensembles frequently occur in the context of multirun simulations. An analysis has many facets, including distributions of extracted features, comparisons between ensemble members and target functions, and details-on-demand. The primary contribution of this paper is a design study of an interactive approach for a comparative visual analysis of 2D function ensembles. The design focuses on a tight integration of domain-oriented and member-oriented visualization techniques, and it seeks to preserve the mental model of 2D functions on multiple levels of detail. In this context, we propose a novel focus+context approach for visualizations relying on data-driven placement which is based on labeling. We also extend work on feature-preserving downsampling of 2D functions. Our design supports a comparison of 2D functions based on juxtaposition, overlay, and explicit differences. It also enables an analysis in terms of extracted scalar features and 1D aggregations. An evaluation illustrates a workflow in our application context. User feedback indicates a time saving of 70% for common tasks and a qualitative gain for the entire development process.
Perception of Animated Node-Link Diagrams for Dynamic Graphs
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Ghani, Sohaib; Elmqvist, Niklas; Yi, Ji Soo; S. Bruckner, S. Miksch, and H. Pfister
Effective visualization of dynamic graphs remains an open research topic, and many state-of-the-art tools use animated node-link diagrams for this purpose. Despite its intuitiveness, the effectiveness of animation in nodelink diagrams has been questioned, and several empirical studies have shown that animation is not necessarily superior to static visualizations. However, the exact mechanics of perceiving animated node-link diagrams are still unclear. In this paper, we study the impact of different dynamic graph metrics on user perception of the animation. After deriving candidate visual graph metrics, we perform an exploratory user study where participants are asked to reconstruct the event sequence in animated node-link diagrams. Based on these findings, we conduct a second user study where we investigate the most important visual metrics in depth. Our findings show that node speed and target separation are prominent visual metrics to predict the performance of event sequencing tasks.
Visualizing Motion Data in Virtual Reality: Understanding the Roles of Animation, Interaction, and Static Presentation
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Coffey, Dane; Korsakov, Fedor; Ewert, Marcus; Hagh-Shenas, Heleh; Thorson, Lauren; Ellingson, Arin; Nuckley, David; Keefe, Daniel; S. Bruckner, S. Miksch, and H. Pfister
We present a study of interactive virtual reality visualizations of scientific motions as found in biomechanics experiments. Our approach is threefold. First, we define a taxonomy of motion visualizations organized by the method (animation, interaction, or static presentation) used to depict both the spatial and temporal dimensions of the data. Second, we design and implement a set of eight example visualizations suggested by the taxonomy and evaluate their utility in a quantitative user study. Third, together with biomechanics collaborators, we conduct a qualitative evaluation of the eight example visualizations applied to a current study of human spinal kinematics. Results suggest that visualizations in this style that use interactive control for the time dimension of the data are preferable to others. Within this category, quantitative results support the utility of both animated and interactive depictions for space; however, qualitative feedback suggest that animated depictions for space should be avoided in biomechanics applications.
A Design Study of Direct-Touch Interaction for Exploratory 3D Scientific Visualization
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Klein, Tijmen; Guéniat, Florimond; Pastur, Luc; Vernier, Frédéric; Isenberg, Tobias; S. Bruckner, S. Miksch, and H. Pfister
We present an interaction design study of several non-overlapping direct-touch interaction widgets, postures, and bi-manual techniques to support the needs of scientists who are exploring a dataset. The final interaction design supports navigation/zoom, cutting plane interaction, a drilling exploration, the placement of seed particles in 3D space, and the exploration of temporal data evolution. To ground our design, we conducted a requirements analysis and used a participatory design approach throughout development. We chose simulations in the field of fluid mechanics as our example domain and, in the paper, discuss our choice of techniques, their adaptation to our target domain, and discuss how they facilitate the necessary combination of visualization control and data exploration. We evaluated our resulting interactive data exploration system with seven fluid mechanics experts and report on their qualitative feedback. While we use flow visualization as our application domain, the developed techniques were designed with generalizability in mind and we discuss several implications of our work on further development of direct-touch data exploration techniques for scientific visualization in general.
Vismon: Facilitating Analysis of Trade-Offs, Uncertainty, and Sensitivity In Fisheries Management Decision Making
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Booshehrian, Maryam; Möller, Torsten; Peterman, Randall M.; Munzner, Tamara; S. Bruckner, S. Miksch, and H. Pfister
In this design study, we present an analysis and abstraction of the data and task in the domain of fisheries management, and the design and implementation of the Vismon tool to address the identified requirements. Vismon was designed to support sophisticated data analysis of simulation results by managers who are highly knowledgeable about the fisheries domain but not experts in simulation software and statistical data analysis. The previous workflow required the scientists who built the models to spearhead the analysis process. The features of Vismon include sensitivity analysis, comprehensive and global trade-offs analysis, and a staged approach to the visualization of the uncertainty of the underlying simulation model. The tool was iteratively refined through a multi-year engagement with fisheries scientists with a two-phase approach, where an initial diverging experimentation phase to test many alternatives was followed by a converging phase where the set of multiple linked views that proved effective were integrated together in a useable way. Several fisheries scientists have used Vismon to communicate with policy makers, and it is scheduled for deployment to policy makers in Alaska.
MarketAnalyzer: An Interactive Visual Analytics System for Analyzing Competitive Advantage Using Point of Sale Data
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Ko, Sungahn; Maciejewski, Ross; Jang, Yun; Ebert, David S.; S. Bruckner, S. Miksch, and H. Pfister
Competitive intelligence is a systematic approach for gathering, analyzing, and managing information to make informed business decisions. Many companies use competitive intelligence to identify risks and opportunities within markets. Point of sale data that retailers share with vendors is of critical importance in developing competitive intelligence. However, existing tools do not easily enable the analysis of such large and complex data. therefore, new approaches are needed in order to facilitate better analysis and decision making. In this paper, we present MarketAnalyzer, an interactive visual analytics system designed to allow vendors to increase their competitive intelligence. MarketAnalyzer utilizes pixel-based matrices to present sale data, trends, and market share growths of products of the entire market within a single display. These matrices are augmented by advanced underlying analytical methods to enable the quick evaluation of growth and risk within market sectors. Furthermore, our system enables the aggregation of point of sale data in geographical views that provide analysts with the ability to explore the impact of regional demographics and trends. Additionally, overview and detailed information is provided through a series of coordinated multiple views. In order to demonstrate the effectiveness of our system, we provide two use-case scenarios as well as feedback from market analysts.
MatchPad: Interactive Glyph-Based Visualization for Real-Time Sports Performance Analysis
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Legg, Philip; Chung, David H. S.; Parry, Matthew L.; Jones, Mark W.; Long, Rhys; Griffiths, Iwan W.; Chen, Min; S. Bruckner, S. Miksch, and H. Pfister
Today real-time sports performance analysis is a crucial aspect of matches in many major sports. For example, in soccer and rugby, team analysts may annotate videos during the matches by tagging specific actions and events, which typically result in some summary statistics and a large spreadsheet of recorded actions and events. To a coach, the summary statistics (e.g., the percentage of ball possession) lacks sufficient details, while reading the spreadsheet is time-consuming and making decisions based on the spreadsheet in real-time is thereby impossible. In this paper, we present a visualization solution to the current problem in real-time sports performance analysis. We adopt a glyph-based visual design to enable coaching staff and analysts to visualize actions and events at a glance . We discuss the relative merits of metaphoric glyphs in comparison with other types of glyph designs in this particular application. We describe an algorithm for managing the glyph layout at different spatial scales in interactive visualization. We demonstrate the use of this technical approach through its application in rugby, for which we delivered the visualization software, MatchPad, on a tablet computer. The MatchPad was used by the Welsh Rugby Union during the Rugby World Cup 2011. It successfully helped coaching staff and team analysts to examine actions and events in detail whilst maintaining a clear overview of the match, and assisted in their decision making during the matches. It also allows coaches to convey crucial information back to the players in a visually-engaging manner to help improve their performance.
PORGY: A Visual Graph Rewriting Environment for Complex Systems
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Pinaud, Bruno; Melançon, Guy; Dubois, Jonathan; S. Bruckner, S. Miksch, and H. Pfister
Graph rewriting systems (GRSs) operate on graphs by substituting local patterns according to a set of rewriting rules. The apparent simplicity of GRSs hides an incredible complexity and turns the study of these systems into an involved task requiring high-level expertise. We designed PORGY, an interactive visual environment to fully support GRSs related tasks, exploiting a long historical tradition of GRSs with node-link representations of graphs. PORGY enables rule-based modeling and simulation steering through graphical representations and direct manipulation of all GRSs components. This paper contributes a design study and task taxonomy relevant to the interactive visualization of GRSs.
I-SI: Scalable Architecture of Analyzing Latent Topical-Level Information From Social Media Data
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Wang, Xiaoyu; Dou, Wenwen; Ma, Zhiqiang; Villalobos, Jeremy; Chen, Yang; Kraft, Thomas; Ribarsky, William; S. Bruckner, S. Miksch, and H. Pfister
We present a general visual analytics architecture that is designed and implemented to effectively analyze unstructured social media data on a large scale. Pipelined on a high-performance cluster configuration, MPI processing, and interactive visual analytics interfaces, our architecture, I-SI, closely integrates data-driven analytical methods and user-centered visual analytics. It creates a coherent analysis environment for identifying event structures, geographical distributions, and key indicators of emerging events. This environment supports monitoring, analyzing, and responding to latent information extracted from social media. We have applied the I-SI architecture to collect social media data, analyze the data on a large scale and uncover the latent social phenomena. To demonstrate the efficacy and applicability of I-SI, we describe several social media use cases in multiple domains that were evaluated by experts. The use cases demonstrate that I-SI can benefit a range of users by constructing meaningful event structures and identifying precursors to critical events within a rich, evolving set of topics.
ConnectedCharts: Explicit Visualization of Relationships between Data Graphics
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Viau, Christophe; McGuffin, Michael; S. Bruckner, S. Miksch, and H. Pfister
Multidimensional multivariate data can be visualized using many different well-known charts, such as bar charts, stacked bar charts, grouped bar charts, scatterplots, or pivot tables, or also using more advanced highdimensional techniques such as scatterplot matrices (SPLOMs) or parallel coordinate plots (PCPs). These many techniques have different advantages, and users may wish to use several charts or data graphics to understand a dataset from different perspectives. We present ConnectedCharts, a technique for displaying relationships between multiple charts. ConnectedCharts allow for hybrid combinations of bar charts, scatterplots, and parallel coordinates, with curves drawn to show the conceptual links between charts. The charts can be thought of as coordinated views, where linking is achieved not only through interactive brushing, but also with explicitly drawn curves that connect corresponding data tuples or axes. We present a formal description of a design space of many simple charts, and also identify different kinds of connections that can be displayed between related charts. Our prototype implementation demonstrates how the connections between multiple charts can make relationships clearer and can serve to document the history of a user's analytical process, leading to potential applications in visual analytics and dashboard design.
Automating Transfer Function Design with Valley Cell-Based Clustering of 2D Density Plots
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Wang, Yunhai; Zhang, Jian; Lehmann, Dirk J.; Theisel, Holger; Chi, Xuebin; S. Bruckner, S. Miksch, and H. Pfister
Two-dimensional transfer functions are an effective and well-accepted tool in volume classification. The design of them mostly depends on the user's experience and thus remains a challenge. Therefore, we present an approach in this paper to automate the transfer function design based on 2D density plots. By exploiting their smoothness, we adopted the Morse theory to automatically decompose the feature space into a set of valley cells. We design a simplification process based on cell separability to eliminate cells which are mainly caused by noise in the original volume data. Boundary persistence is first introduced to measure the separability between adjacent cells and to suitably merge them. Afterward, a reasonable classification result is achieved where each cell represents a potential feature in the volume data. This classification procedure is automatic and facilitates an arbitrary number and shape of features in the feature space. The opacity of each feature is determined by its persistence and size. To further incorporate the user's prior knowledge, a hierarchical feature representation is created by successive merging of the cells. With this representation, the user is allowed to merge or split features of interest and set opacity and color freely. Experiments on various volumetric data sets demonstrate the effectiveness and usefulness of our approach in transfer function generation.
Importance Driven Automatic Color Design for Direct Volume Rendering
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Wang, Lei; Kaufman, Arie; S. Bruckner, S. Miksch, and H. Pfister
This paper introduces an automatic color design method that is driven by an importance function of the objects within a volumetric dataset. Our method allows the user to intuitively modify the object classification and the importance distribution function in the 2D rendered image. It automatically computes the transfer function, especially the color distribution, to convey the importance of the objects. In our approach, the importance of an object is represented as the attentiveness of a color. In addition, we preserve the color harmony in the rendered image in order to provide a visually pleasing result. In this paper, we propose a set of computational measurements to compute the color attentiveness and color harmony. Our color assignment algorithm supports arbitrary-dimensional transfer functions and obtains interactive frame rates. Our method involves three color spaces, namely Coloroid system, CIE LChuv, and Adobe RGB color space. It calculates the color attentiveness in CIE LChuv space, and the color harmony in Coloroid system. It, then, assigns the transfer function in a dual space of Adobe RGB space and renders the resulting image in Adobe RGB space. We conducted a detailed user study, which proves that our method successfully conveys the importance distributions. Our contribution in this paper is not only our importance driven approach, but also our computational measurements and our color assignment algorithm.
COVRA: A Compression-domain Output-sensitive Volume Rendering Architecture Based on a Sparse Representation of Voxel Blocks
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Gobbetti, Enrico; Guitian, José Antonio Iglesias; Marton, Fabio; S. Bruckner, S. Miksch, and H. Pfister
We present a novel multiresolution compression-domain GPU volume rendering architecture designed for inter- active local and networked exploration of rectilinear scalar volumes on commodity platforms. In our approach, the volume is decomposed into a multiresolution hierarchy of bricks. Each brick is further subdivided into smaller blocks, which are compactly described by sparse linear combinations of prototype blocks stored in an overcomplete dictionary. The dictionary is learned, using limited computational and memory resources, by applying the K-SVD algorithm to a re-weighted non-uniformly sampled subset of the input volume, harnessing the recently introduced method of coresets. The result is a scalable high quality coding scheme, which allows very large volumes to be compressed off-line and then decompressed on-demand during real-time GPU-accelerated rendering. Volumetric information can be maintained in compressed format through all the rendering pipeline. In order to efficiently support high quality filtering and shading, a specialized real-time renderer closely coordinates decompression with rendering, combining at each frame images produced by raycasting selectively decompressed portions of the current view- and transfer-function-dependent working set. The quality and performance of our approach is demonstrated on massive static and time-varying datasets.
Interactive Rendering of Materials and Biological Structures on Atomic and Nanoscopic Scale
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Lindow, Norbert; Baum, Daniel; Hege, Hans-Christian; S. Bruckner, S. Miksch, and H. Pfister
The properties of both inorganic and organic materials and the function of biological structures can often only be understood by analyzing them simultaneously on atomic and nanoscopic, if not mesoscopic, scale. Here, the problem arises to render millions to billions of atoms. We propose a method by which it is possible to interactively visualize atomic data, bridging five orders of magnitude in length scale. For this, we propose a simple yet efficient GPU rendering method that enables interactive visualization of biological structures consisting of up to several billions of atoms. To be able to load all atomic data onto the GPU, we exploit the fact that biological structures often consist of recurring molecular substructures. We also exploit that these objects typically are rendered opaquely, so that only a fraction of the atoms is visible. The method is demonstrated on both biological structures as well as atom probe tomography data of an inorganic specimen. We conclude with a discussion about when during ascension from atomic to mesoscopic scale level-of-detail representations become necessary.
A Taxonomy of Visual Cluster Separation Factors
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Sedlmair, Michael; Tatu, Andrada; Munzner, Tamara; Tory, Melanie; S. Bruckner, S. Miksch, and H. Pfister
We provide two contributions, a taxonomy of visual cluster separation factors in scatterplots, and an in-depth qualitative evaluation of two recently proposed and validated separation measures. We initially intended to use these measures to provide guidance for the use of dimension reduction (DR) techniques and visual encoding (VE) choices, but found that they failed to produce reliable results. To understand why, we conducted a systematic qualitative data study covering a broad collection of 75 real and synthetic high-dimensional datasets, four DR techniques, and three scatterplot-based visual encodings. Two authors visually inspected over 800 plots to determine whether or not the measures created plausible results. We found that they failed in over half the cases overall, and in over two-thirds of the cases involving real datasets. Using open and axial coding of failure reasons and separability characteristics, we generated a taxonomy of visual cluster separability factors. We iteratively refined its explanatory clarity and power by mapping the studied datasets and success and failure ranges of the measures onto the factor axes. Our taxonomy has four categories, ordered by their ability to influence successors: Scale, Point Distance, Shape, and Position. Each category is split into Within-Cluster factors such as density, curvature, isotropy, and clumpiness, and Between-Cluster factors that arise from the variance of these properties, culminating in the overarching factor of class separation. The resulting taxonomy can be used to guide the design and the evaluation of cluster separation measures.
Semi-Supervised Dimensionality Reduction based on Partial Least Squares for Visual Analysis of High Dimensional Data
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Paiva, Jose Gustavo S.; Schwartz, William Robson; Pedrini, Helio; Minghim, Rosane; S. Bruckner, S. Miksch, and H. Pfister
Dimensionality reduction is employed for visual data analysis as a way to obtaining reduced spaces for high dimensional data or to mapping data directly into 2D or 3D spaces. Although techniques have evolved to improve data segregation on reduced or visual spaces, they have limited capabilities for adjusting the results according to user's knowledge. In this paper, we propose a novel approach to handling both dimensionality reduction and visualization of high dimensional data, taking into account user's input. It employs Partial Least Squares (PLS), a statistical tool to perform retrieval of latent spaces focusing on the discriminability of the data. The method employs a training set for building a highly precise model that can then be applied to a much larger data set very effectively. The reduced data set can be exhibited using various existing visualization techniques. The training data is important to code user's knowledge into the loop. However, this work also devises a strategy for calculating PLS reduced spaces when no training data is available. The approach produces increasingly precise visual mappings as the user feeds back his or her knowledge and is capable of working with small and unbalanced training sets.
Procedural Texture Synthesis for Zoom-Independent Visualization of Multivariate Data
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Khlebnikov, Rostislav; Kainz, Bernhard; Steinberger, Markus; Streit, Marc; Schmalstieg, Dieter; S. Bruckner, S. Miksch, and H. Pfister
Simultaneous visualization of multiple continuous data attributes in a single visualization is a task that is important for many application areas. Unsurprisingly, many methods have been proposed to solve this task. However, the behavior of such methods during the exploration stage, when the user tries to understand the data with panning and zooming, has not been given much attention. In this paper, we propose a method that uses procedural texture synthesis to create zoom-independent visualizations of three scalar data attributes. The method is based on random-phase Gabor noise, whose frequency is adapted for the visualization of the first data attribute. We ensure that the resulting texture frequency lies in the range that is perceived well by the human visual system at any zoom level. To enhance the perception of this attribute, we also apply a specially constructed transfer function that is based on statistical properties of the noise. Additionally, the transfer function is constructed in a way that it does not introduce any aliasing to the texture. We map the second attribute to the texture orientation. The third attribute is color coded and combined with the texture by modifying the value component of the HSV color model. The necessary contrast needed for texture and color perception was determined in a user study. In addition, we conducted a second user study that shows significant advantages of our method over current methods with similar goals. We believe that our method is an important step towards creating methods that not only succeed in visualizing multiple data attributes, but also adapt to the behavior of the user during the data exploration stage.
Tracing Tuples Across Dimensions: A Comparison of Scatterplots and Parallel Coordinate Plots
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Kuang, Xiaole; Zhang, Haimo; Zhao, Shengdong; McGuffin, Michael J.; S. Bruckner, S. Miksch, and H. Pfister
One of the fundamental tasks for analytic activity is retrieving (i.e., reading) the value of a particular quantity in an information visualization. However, few previous studies have compared user performance in such value retrieval tasks for different visualizations. We present an experimental comparison of user performance (time and error distance) across four multivariate data visualizations. Three variants of scatterplot (SCP) visualizations, namely SCPs with common vertical axes (SCP-common), SCPs with a staircase layout (SCP-staircase), and SCPs with rotated axes between neighboring cells (SCP-rotated), and a baseline parallel coordinate plots (PCP) were compared. Results show that the baseline PCP is better than SCP-rotated and SCP-staircase under all conditions, while the difference between SCP-common and PCP depends on the dimensionality and density of the dataset. PCP shows advantages over SCP-common when the dimensionality and density of the dataset are low, but SCP- common eventually outperforms PCP as data dimensionality and density increase. The results suggest guidelines for the use of SCPs and PCPs that can benefit future researchers and practitioners.

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