EuroVis11: Eurographics/ IEEE Symposium on Visualization

Permanent URI for this collection

https://diglib.eg.org/handle/10.2312/394

Curve Density Estimates

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Lampe, Ove Daae

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Hauser, Helwig

Progressive Splatting of Continuous Scatterplots and Parallel Coordinates

[meta data] [files: ]

Heinrich, Julian

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Bachthaler, S.

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Weiskopf, Daniel

Visual Coherence for Large-Scale Line-Plot Visualizations

[meta data] [files: ]

Muigg, Philipp

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Hadwiger, Markus

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Doleisch, Helmut

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Gröller, Eduard

Topology-based Visualization of Transformation Pathways in Complex Chemical Systems

[meta data] [files: ]

Beketayev, Kenes

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Weber, G. H.

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Haranczyk, M.

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Bremer, P.-T.

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Hlawitschka, M.

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Hamann, B.

Interactive Exploration of Protein Cavities

[meta data] [files: ]

Krone, M.

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Falk, M.

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Rehm, S.

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Pleiss, J.

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Ertl, T.

Illustrative Molecular Visualization with Continuous Abstraction

[meta data] [files: ]

Zwan, Matthew van der

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Lueks, Wouter

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Bekker, Henk

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Isenberg, Tobias

Visual Exploration of Time-Series Data with Shape Space Projections

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Ward, Matthew O.

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Guo, Zhenyu

A Visual Analytics Approach for Peak-Preserving Prediction of Large Seasonal Time Series

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Hao, M. C.

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Janetzko, H.

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Mittelstädt, S.

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Hill, W.

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Dayal, U.

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Keim, D. A.

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Marwah, M.

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Sharma, R. K.

Interactive Visual Analysis of Temporal Cluster Structures

[meta data] [files: ]

Turkay, Cagatay

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Parulek, J.

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Reuter, N.

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Hauser, Helwig

PaperVis: Literature Review Made Easy

[meta data] [files: ]

Chou, Jia -Kai

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Yang, C. -K.

Efficient Parallel Vectors Feature Extraction from Higher-Order Data

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Pagot, Christian

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Osmari, D.

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Sadlo, F.

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Weiskopf, Daniel

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Ertl, Thomas

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Comba, J.

Semantic-Preserving Word Clouds by Seam Carving

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Wu, Yingcai

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Provan, Thomas

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Wei, Furu

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Liu, Shixia

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Ma, Kwan-Liu

Exploring Collections of Tagged Text for Literary Scholarship

[meta data] [files: ]

Correll, Michael

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Witmore, M.

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Gleicher, M.

Lagrangian Coherent Structures with Guaranteed Material Separation

[meta data] [files: ]

Germer, Tobias

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Otto, Mathias

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Peikert, R.

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Theisel, H.

A User Study of Visualization Effectiveness Using EEG and Cognitive Load

[meta data] [files: ]

Anderson, Erik W.

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Potter, K. C.

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Matzen, L. E.

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Shepherd, J. F.

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Preston, G. A.

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Silva, C. T.

Energy-scale Aware Feature Extraction for Flow Visualization

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Pobitzer, A.

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Tutkun, M.

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Andreassen, Ø.

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Fuchs, R.

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Peikert, R.

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Hauser, H.

Visual Reconstructability as a Quality Metric for Flow Visualization

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Jänicke, Heike

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Weidner, Thomas

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Chung, David

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Laramee, Robert S.

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Townsend, Peter

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Chen, Min

Perceptual Evaluation of Ghosted View Techniques for the Exploration of Vascular Structures and Embedded Flow

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Baer, Alexandra

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Gasteiger, Rocco

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Cunningham, Douglas

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Preim, Bernhard

Evaluation of the Visibility of Vessel Movement Features in Trajectory Visualizations

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Willems, Niels

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Wetering, Huub van de

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Wijk, Jarke J. van

An Evaluation of Visualization Techniques to Illustrate Statistical Deformation Models

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Caban, Jesus J.

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Rheingans, Penny

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Yoo, T.

Complete Tensor Field Topology on 2D Triangulated Manifolds embedded in 3D

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Auer, Cornelia

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Hotz, Ingrid

Stable Morse Decompositions for Piecewise Constant Vector Fields on Surfaces

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Szymczak, Andrzej

Topological Features in 2D Symmetric Higher-Order Tensor Fields

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Schultz, Thomas

Visual Boosting in Pixel-based Visualizations

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Oelke, Daniela

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Janetzko, Halldor

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Simon, Svenja

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Neuhaus, Klaus

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Keim, Daniel A.

Dynamic Insets for Context-Aware Graph Navigation

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Ghani, Sohaib

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Riche, N. Henry

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Elmqvist, Niklas

Visualization of Time-Series Data in Parameter Space for Understanding Facial Dynamics

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Tam, Gary K. L.

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Fang, H.

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Aubrey, A. J.

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Grant, P. W.

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Rosin, P. L.

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Marshall, D.

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Chen, M.

The Undistort Lens

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Brosz, John

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Carpendale, Sheelagh

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Nacenta, Miguel A.

Assisted Descriptor Selection Based on Visual Comparative Data Analysis

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Bremm, Sebastian

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Landesberger, Tatiana von

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Bernard, Jürgen

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Schreck, Tobias

Uncertainty-Aware Exploration of Continuous Parameter Spaces Using Multivariate Prediction

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Berger, Wolfgang

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Piringer, H.

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Filzmoser, P.

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Gröller, Eduard

Probabilistic Marching Cubes

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Pöthkow, Kai

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Weber, Britta

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Hege, Hans-Christian

Structural Decomposition Trees

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Engel, Daniel

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Rosenbaum, R.

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Hamann, B.

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Hagen, Hans

Depth of Field Effects for Interactive Direct Volume Rendering

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Schott, Mathias

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Grosset, A. V. Pascal

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Martin, Tobias

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Pegoraro, Vincent

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Smith, Sean T.

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Hansen, Charles D.

Fast Extraction of High-quality Crease Surfaces for Visual Analysis

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Barakat, Samer

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Andrysco, N.

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Tricoche, Xavier

Visualizing the Positional and Geometrical Variability of Isosurfaces in Uncertain Scalar Fields

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Pfaffelmoser, Tobias

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Reitinger, Matthias

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Westermann, Rüdiger

Flowstrates: An Approach for Visual Exploration of Temporal Origin-Destination Data

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Boyandin, Ilya

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Bertini, Enrico

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Bak, Peter

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Lalanne, Denis

Temporal Visualization of Boundary-based Geo-information Using Radial Projection

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Drocourt, Y.

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Borgo, Rita

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Scharrer, K.

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Murray, T.

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Bevan, S. I.

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Chen, M.

WaveMap: Interactively Discovering Features From Protein Flexibility Matrices Using Wavelet-based Visual Analytics

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Barlowe, Scott

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Liu, Yujie

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Yang, Jing

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Livesay, Dennis R.

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Jacobs, Donald J.

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Mottonen, James

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Verma, Deeptak

Pathway Preserving Representation of Metabolic Networks

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Lambert, Antoine

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Dubois, J.

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Bourqui, Romain

Visualising Errors in Animal Pedigree Genotype Data

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Graham, Martin

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Kennedy, Jessie

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Paterson, Trevor

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Law, Andy

Visualization and Analysis of Eddies in a Global Ocean Simulation

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Williams, S.

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Hecht, M.

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Petersen, M.

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Strelitz, R.

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Maltrud, M.

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Ahrens, J.

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Hlawitschka, M.

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Hamann, B.

Anatomy-Guided Multi-Level Exploration of Blood Flow in Cerebral Aneurysms

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Neugebauer, Mathias

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Janiga, Gabor

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Beuing, Oliver

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Skalej, Martin

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Preim, Bernhard

A Shader Framework for Rapid Prototyping of GPU-Based Volume Rendering

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Rieder, Christian

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Palmer, Stephan

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Link, Florian

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Hahn, Horst K.

Prostate Cancer Visualization from MR Imagery and MR Spectroscopy

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Marino, Joseph

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Kaufman, Arie

Visualizing the Evolution of Community Structures in Dynamic Social Networks

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Reda, Khairi

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Tantipathananandh, Chayant

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Johnson, Andrew

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Leigh, Jason

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Berger-Wolf, Tanya

ImPrEd: An Improved Force-Directed Algorithm that Prevents Nodes from Crossing Edges

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Simonetto, Paolo

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Archambault, Daniel

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Auber, David

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Bourqui, Romain

Visual Recommendations for Network Navigation

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Crnovrsanin, Tarik

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Liao, Isaac

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Wuy, Yingcai

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Ma, Kwan-Liu

A Gradient-Based Comparison Measure for Visual analysis of Multifield Data

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Nagaraj, Suthambhara

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Natarajan, Vijay

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Nanjundiah, Ravi S.

Piecewise Laplacian-based Projection for Interactive Data Exploration and Organization

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Paulovich, Fernando V.

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Eler, D. M.

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Poco, J.

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Botha, Charl P.

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Minghim, R.

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Nonato, L. G.

A Framework for Exploring Multidimensional Data with 3D Projections

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Poco, Jorge

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Etemadpour, Ronak

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Paulovich, F. V.

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Long, T. V.

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Rosenthal, P.

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Oliveira, M. C. F.

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Linsen, Lars

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Minghim, R.

Visualizing High-Dimensional Structures by Dimension Ordering and Filtering using Subspace Analysis

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Ferdosi, Bilkis J.

Tablorer - An Interactive Tree Visualization System for Tablet PCs

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Shin, HyunJu

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Park, GwangHyun

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Han, JungHyun

Comparison of Multiple Weighted Hierarchies: Visual Analytics for Microbe Community Profiling

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Dinkla, Kasper

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Westenberg, M. A.

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Timmerman, H. M.

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Hijum, S.A.F.T. van

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Wijk, J. J. van

Automatic Registration of Multi-Projector Domes Using a Single Uncalibrated Camera

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Sajadi, Behzad

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Majumder, Aditi

In-situ Sampling of a Large-Scale Particle Simulation for Interactive Visualization and Analysis

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Woodring, Jonathan

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Ahrens, J.

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Figg, J.

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Wendelberger, J.

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Habib, S.

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Heitmann, K.

Browse

Now showing 1 - 54 of 54

Curve Density Estimates
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Lampe, Ove Daae; Hauser, Helwig; H. Hauser, H. Pfister, and J. J. van Wijk
In this work, we present a technique based on kernel density estimation for rendering smooth curves. With this approach, we produce uncluttered and expressive pictures, revealing frequency information about one, or, multiple curves, independent of the level of detail in the data, the zoom level, and the screen resolution. With this technique the visual representation scales seamlessly from an exact line drawing, (for low-frequency/low-complexity curves) to a probability density estimate for more intricate situations. This scale-independence facilitates displays based on non-linear time, enabling high-resolution accuracy of recent values, accompanied by long historical series for context. We demonstrate the functionality of this approach in the context of prediction scenarios and in the context of streaming data.
Progressive Splatting of Continuous Scatterplots and Parallel Coordinates
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Heinrich, Julian; Bachthaler, S.; Weiskopf, Daniel; H. Hauser, H. Pfister, and J. J. van Wijk
Continuous scatterplots and parallel coordinates are used to visualize multivariate data defined on a continuous domain. With the existing techniques, rendering such plots becomes prohibitively slow, especially for large scientific datasets. This paper presents a scalable and progressive rendering algorithm for continuous data plots that allows exploratory analysis of large datasets at interactive framerates. The algorithm employs splatting to produce a series of plots that are combined using alpha blending to achieve a progressively improving image. For each individual frame, splats are obtained by transforming Gaussian density kernels from the 3-D domain of the input dataset to the respective data domain. A closed-form analytic description of the resulting splat footprints is derived to allow pre-computation of splat textures for efficient GPU rendering. The plotting method is versatile because it supports arbitrary reconstruction or interpolation schemes for the input data and the splatting technique is scalable because it chooses splat samples independently from the size of the input dataset. Finally, the effectiveness of the method is compared to existing techniques regarding rendering performance and quality.
Visual Coherence for Large-Scale Line-Plot Visualizations
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Muigg, Philipp; Hadwiger, Markus; Doleisch, Helmut; Gröller, Eduard; H. Hauser, H. Pfister, and J. J. van Wijk
Displaying a large number of lines within a limited amount of screen space is a task that is common to many different classes of visualization techniques such as time-series visualizations, parallel coordinates, link-node diagrams, and phase-space diagrams. This paper addresses the challenging problems of cluttering and overdraw inherent to such visualizations. We generate a 2x2 tensor field during line rasterization that encodes the distribution of line orientations through each image pixel. Anisotropic diffusion of a noise texture is then used to generate a dense, coherent visualization of line orientation. In order to represent features of different scales, we employ a multi-resolution representation of the tensor field. The resulting technique can easily be applied to a wide variety of line-based visualizations. We demonstrate this for parallel coordinates, a time-series visualization, and a phase-space diagram. Furthermore, we demonstrate how to integrate a focus+context approach by incorporating a second tensor field. Our approach achieves interactive rendering performance for large data sets containing millions of data items, due to its image-based nature and ease of implementation on GPUs. Simulation results from computational fluid dynamics are used to evaluate the performance and usefulness of the proposed method.
Topology-based Visualization of Transformation Pathways in Complex Chemical Systems
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Beketayev, Kenes; Weber, G. H.; Haranczyk, M.; Bremer, P.-T.; Hlawitschka, M.; Hamann, B.; H. Hauser, H. Pfister, and J. J. van Wijk
Studying transformation in a chemical system by considering its energy as a function of coordinates of the system's components provides insight and changes our understanding of this process. Currently, a lack of effective visualization techniques for high-dimensional energy functions limits chemists to plot energy with respect to one or two coordinates at a time. In some complex systems, developing a comprehensive understanding requires new visualization techniques that show relationships between all coordinates at the same time. We propose a new visualization technique that combines concepts from topological analysis, multi-dimensional scaling, and graph layout to enable the analysis of energy functions for a wide range of molecular structures. We demonstrate our technique by studying the energy function of a dimer of formic and acetic acids and a LTA zeolite structure, in which we consider diffusion of methane.
Interactive Exploration of Protein Cavities
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Krone, M.; Falk, M.; Rehm, S.; Pleiss, J.; Ertl, T.; H. Hauser, H. Pfister, and J. J. van Wijk
We present a novel application for the interactive exploration of cavities within proteins in dynamic data sets. Inside a protein, cavities can often be found close to the active center. Therefore, when analyzing a molecular dynamics simulation trajectory it is of great interest to find these cavities and determine if such a cavity opens up to the environment, making the binding site accessible to the surrounding substrate. Our user-driven approach enables expert users to select a certain cavity and track its evolution over time. The user is supported by different visualizations of the extracted cavity to facilitate the analysis. The boundary of the protein and its cavities is obtained by means of volume ray casting, where the volume is computed in real-time for each frame, therefore allowing the examination of time-dependent data sets. A fast, partial segmentation of the volume is applied to obtain the selected cavity and trace it over time. Domain experts found our method useful when they applied it exemplarily on two trajectories of lipases from Rhizomucor miehei and Candida antarctica. In both data sets cavities near the active center were easily identified and tracked over time until they reached the surface and formed an open substrate channel.
Illustrative Molecular Visualization with Continuous Abstraction
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Zwan, Matthew van der; Lueks, Wouter; Bekker, Henk; Isenberg, Tobias; H. Hauser, H. Pfister, and J. J. van Wijk
Molecular systems may be visualized with various degrees of structural abstraction, support of spatial perception, and 'illustrativeness.' In this work we propose and realize methods to create seamless transformations that allow us to affect and change each of these three parameters individually. The resulting transitions give viewers a dedicated control of abstraction in illustrative molecular visualization and, consequently, allow them to seamlessly explore the resulting abstraction space for obtaining a fundamental understanding of molecular systems.We show example visualizations created with our approach and report informal feedback on our technique from domain experts.
Visual Exploration of Time-Series Data with Shape Space Projections
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Ward, Matthew O.; Guo, Zhenyu; H. Hauser, H. Pfister, and J. J. van Wijk
Time-series data is a common target for visual analytics, as they appear in a wide range of application domains. Typical tasks in analyzing time-series data include identifying cyclic behavior, outliers, trends, and periods of time that share distinctive shape characteristics. Many methods for visualizing time series data exist, generally mapping the data values to positions or colors. While each can be used to perform a subset of the above tasks, none to date is a complete solution. In this paper we present a novel approach to time-series data visualization, namely creating multivariate data records out of short subsequences of the data and then using multivariate visualization methods to display and explore the data in the resulting shape space. We borrow ideas from text analysis, where the use of N-grams is a common approach to decomposing and processing unstructured text. By mapping each temporal N-gram to a glyph, and then positioning the glyphs via PCA (basically a projection in shape space), many different kinds of patterns in the sequence can be readily identified. Interactive selection via brushing, in conjunction with linking to other visualizations, provides a wide range of tools for exploring the data. We validate the usefulness of this approach with examples from several application domains and tasks, comparing our methods with traditional time-series visualizations.
A Visual Analytics Approach for Peak-Preserving Prediction of Large Seasonal Time Series
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Hao, M. C.; Janetzko, H.; Mittelstädt, S.; Hill, W.; Dayal, U.; Keim, D. A.; Marwah, M.; Sharma, R. K.; H. Hauser, H. Pfister, and J. J. van Wijk
Time series prediction methods are used on a daily basis by analysts for making important decisions. Most of these methods use some variant of moving averages to reduce the number of data points before prediction. However, to reach a good prediction in certain applications (e.g., power consumption time series in data centers) it is important to preserve peaks and their patterns. In this paper, we introduce automated peak-preserving smoothing and prediction algorithms, enabling a reliable long term prediction for seasonal data, and combine them with an advanced visual interface: (1) using high resolution cell-based time series to explore seasonal patterns, (2) adding new visual interaction techniques (multi-scaling, slider, and brushing & linking) to incorporate human expert knowledge, and (3) providing both new visual accuracy color indicators for validating the predicted results and certainty bands communicating the uncertainty of the prediction. We have integrated these techniques into a wellfitted solution to support the prediction process, and applied and evaluated the approach to predict both power consumption and server utilization in data centers with 70-80% accuracy.
Interactive Visual Analysis of Temporal Cluster Structures
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Turkay, Cagatay; Parulek, J.; Reuter, N.; Hauser, Helwig; H. Hauser, H. Pfister, and J. J. van Wijk
Cluster analysis is a useful method which reveals underlying structures and relations of items after grouping them into clusters. In the case of temporal data, clusters are defined over time intervals where they usually exhibit structural changes. Conventional cluster analysis does not provide sufficient methods to analyze these structural changes, which are, however, crucial in the interpretation and evaluation of temporal clusters. In this paper, we present two novel and interactive visualization techniques that enable users to explore and interpret the structural changes of temporal clusters. We introduce the temporal cluster view, which visualizes the structural quality of a number of temporal clusters, and temporal signatures, which represents the structure of clusters over time. We discuss how these views are utilized to understand the temporal evolution of clusters. We evaluate the proposed techniques in the cluster analysis of mixed lipid bilayers.
PaperVis: Literature Review Made Easy
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Chou, Jia -Kai; Yang, C. -K.; H. Hauser, H. Pfister, and J. J. van Wijk
Reviewing literatures for a certain research field is always important for academics. One could use Google-like information seeking tools, but oftentimes he/she would end up obtaining too many possibly related papers, as well as the papers in the associated citation network. During such a process, a user may easily get lost after following a few links for searching or cross-referencing. It is also difficult for the user to identify relevant/important papers from the resulting huge collection of papers. Our work, called PaperVis, endeavors to provide a user-friendly interface to help users quickly grasp the intrinsic complex citation-reference structures among a specific group of papers. We modify the existing Radial Space Filling (RSF) and Bullseye View techniques to arrange involved papers as a node-link graph that better depicts the relationships among them while saving the screen space at the same time. PaperVis applies visual cues to present node attributes and their transitions among interactions, and it categorizes papers into semantically meaningful hierarchies to facilitate ensuing literature exploration. We conduct experiments on the InfoVis 2004 Contest Dataset to demonstrate the effectiveness of PaperVis.
Efficient Parallel Vectors Feature Extraction from Higher-Order Data
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Pagot, Christian; Osmari, D.; Sadlo, F.; Weiskopf, Daniel; Ertl, Thomas; Comba, J.; H. Hauser, H. Pfister, and J. J. van Wijk
The parallel vectors (PV) operator is a feature extraction approach for defining line-type features such as creases (ridges and valleys) in scalar fields, as well as separation, attachment, and vortex core lines in vector fields. In this work, we extend PV feature extraction to higher-order data represented by piecewise analytical functions defined over grid cells. The extraction uses PV in two distinct stages. First, seed points on the feature lines are placed by evaluating the inclusion form of the PV criterion with reduced affine arithmetic. Second, a feature flow field is derived from the higher-order PV expression where the features can be extracted as streamlines starting at the seeds. Our approach allows for guaranteed bounds regarding accuracy with respect to existence, position, and topology of the features obtained. The method is suitable for parallel implementation and we present results obtained with our GPU-based prototype. We apply our method to higher-order data obtained from discontinuous Galerkin fluid simulations.
Semantic-Preserving Word Clouds by Seam Carving
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Wu, Yingcai; Provan, Thomas; Wei, Furu; Liu, Shixia; Ma, Kwan-Liu; H. Hauser, H. Pfister, and J. J. van Wijk
Word clouds are proliferating on the Internet and have received much attention in visual analytics. Although word clouds can help users understand the major content of a document collection quickly, their ability to visually compare documents is limited. This paper introduces a new method to create semantic-preserving word clouds by leveraging tailored seam carving, a well-established content-aware image resizing operator. The method can optimize a word cloud layout by removing a left-to-right or top-to-bottom seam iteratively and gracefully from the layout. Each seam is a connected path of low energy regions determined by a Gaussian-based energy function. With seam carving, we can pack the word cloud compactly and effectively, while preserving its overall semantic structure. Furthermore, we design a set of interactive visualization techniques for the created word clouds to facilitate visual text analysis and comparison. Case studies are conducted to demonstrate the effectiveness and usefulness of our techniques.
Exploring Collections of Tagged Text for Literary Scholarship
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Correll, Michael; Witmore, M.; Gleicher, M.; H. Hauser, H. Pfister, and J. J. van Wijk
Modern literary scholars must combine access to vast collections of text with the traditional close analysis of their field. In this paper, we discuss the design and development of tools to support this work. Based on analysis of the needs of literary scholars, we constructed a suite of visualization tools for the analysis of large collections of tagged text (i.e. text where one or more words have been annotated as belonging to a specific category). These tools unite the aspects of the scholars' work: large scale overview tools help to identify corpus-wide statistical patterns while fine scale analysis tools assist in finding specific details that support these observations. We designed visual tools that support and integrate these levels of analysis. The result is the first tool suite that can support the multilevel text analysis performed by scholars, combining standard visual elements with novel methods for selecting individual texts and identifying represenative passages in them.
Lagrangian Coherent Structures with Guaranteed Material Separation
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Germer, Tobias; Otto, Mathias; Peikert, R.; Theisel, H.; H. Hauser, H. Pfister, and J. J. van Wijk
Given an unsteady flow field, one common way to compute Lagrangian Coherent Structures (LCS) is to extract extremal structures of the Finite Time Lyapunov Exponent (FTLE). Experience has shown that the resulting structures are often close to material structures (i.e., material lines or material surfaces). Moreover, it has been proven that for an integration time converging to infinity, they converge to exact material structures. However, due to the finite integration time in FTLE, they are generally not exact material structures. In this paper we introduce a modification of the FTLE method which is guaranteed to produce separating material structures as features of a scalar field. We achieve this by incorporating the complete available integration time both in forward and backward direction, and by choosing an appropriate definition for separating structures. We apply our method to two test data sets and show the differences to classical FTLE.
A User Study of Visualization Effectiveness Using EEG and Cognitive Load
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Anderson, Erik W.; Potter, K. C.; Matzen, L. E.; Shepherd, J. F.; Preston, G. A.; Silva, C. T.; H. Hauser, H. Pfister, and J. J. van Wijk
Effectively evaluating visualization techniques is a difficult task often assessed through feedback from user studies and expert evaluations. This work presents an alternative approach to visualization evaluation in which brain activity is passively recorded using electroencephalography (EEG). These measurements are used to compare different visualization techniques in terms of the burden they place on a viewer's cognitive resources. In this paper, EEG signals and response times are recorded while users interpret different representations of data distributions. This information is processed to provide insight into the cognitive load imposed on the viewer. This paper describes the design of the user study performed, the extraction of cognitive load measures from EEG data, and how those measures are used to quantitatively evaluate the effectiveness of visualizations.
Energy-scale Aware Feature Extraction for Flow Visualization
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Pobitzer, A.; Tutkun, M.; Andreassen, Ø.; Fuchs, R.; Peikert, R.; Hauser, H.; H. Hauser, H. Pfister, and J. J. van Wijk
In the visualization of flow simulation data, feature detectors often tend to result in overly rich response, making some sort of filtering or simplification necessary to convey meaningful images. In this paper we present an approach that builds upon a decomposition of the flow field according to dynamical importance of different scales of motion energy. Focusing on the high-energy scales leads to a reduction of the flow field while retaining the underlying physical process. The presented method acknowledges the intrinsic structures of the flow according to its energy and therefore allows to focus on the energetically most interesting aspects of the flow. Our analysis shows that this approach can be used for methods based on both local feature extraction and particle integration and we provide a discussion of the error caused by the approximation. Finally, we illustrate the use of the proposed approach for both a local and a global feature detector and in the context of numerical flow simulations.
Visual Reconstructability as a Quality Metric for Flow Visualization
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Jänicke, Heike; Weidner, Thomas; Chung, David; Laramee, Robert S.; Townsend, Peter; Chen, Min; H. Hauser, H. Pfister, and J. J. van Wijk
We present a novel approach for the evaluation of 2D flow visualizations based on the visual reconstructability of the input vector fields. According to this metric, a visualization has high quality if the underlying data can be reliably reconstructed from the image. This approach provides visualization creators with a cost-effective means to assess the quality of visualization results objectively. We present a vision-based reconstruction system for the three most commonly-used visual representations of vector fields, namely streamlines, arrow glyphs, and line integral convolution. To demonstrate the use of visual reconstructability as a quality metric, we consider a selection of vector fields obtained from numerical simulations, containing typical flow features. We apply the three types of visualization to each dataset, and compare the visualization results based on their visual reconstructability of the original vector field.
Perceptual Evaluation of Ghosted View Techniques for the Exploration of Vascular Structures and Embedded Flow
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Baer, Alexandra; Gasteiger, Rocco; Cunningham, Douglas; Preim, Bernhard; H. Hauser, H. Pfister, and J. J. van Wijk
This paper presents three controlled perceptual studies investigating the visualization of the cerebral aneurysm anatomy with embedded flow visualization. We evaluate and compare the common semitransparent visualization technique with a ghosted view and a ghosted view with depth enhancement technique. We analyze the techniques' ability to facilitate and support the shape and spatial representation of the aneurysm models as well as evaluating the smart visibility characteristics. The techniques are evaluated with respect to the participants accuracy, response time and their personal preferences. We used as stimuli 3D aneurysm models of five clinical datasets. There was overwhelming preference for the two ghosted view techniques over the semitransparent technique. Since smart visibility techniques are rarely evaluated, this paper may serve as orientation for further studies.
Evaluation of the Visibility of Vessel Movement Features in Trajectory Visualizations
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Willems, Niels; Wetering, Huub van de; Wijk, Jarke J. van; H. Hauser, H. Pfister, and J. J. van Wijk
There are many visualizations that show the trajectory of a moving object to obtain insights in its behavior. In this user study, we test the performance of three of these visualizations with respect to three movement features that occur in vessel behavior. Our goal is to compare the recently presented vessel density by Willems et al. [WvdWvW09] with well-known trajectory visualizations such as an animation of moving dots and the space-time cube. We test these visualizations with common maritime analysis tasks by investigating the ability of users to find stopping objects, fast moving objects, and estimate the busiest routes in vessel trajectories. We test the robustness of the visualizations towards scalability and the influence of complex trajectories using small-scale synthetic data sets. The performance is measured in terms of correctness and response time. The user test shows that each visualization type excels for correctness for a specific movement feature. Vessel density performs best for finding stopping objects, but does not perform significantly less than the remaining visualizations for the other features. Therefore, vessel density is a nice extension in the toolkit for analyzing trajectories of moving objects, in particular for vessel movements, since stops can be visualized better, and the performance for comparing lanes and finding fast movers is at a similar level as established trajectory visualizations.
An Evaluation of Visualization Techniques to Illustrate Statistical Deformation Models
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Caban, Jesus J.; Rheingans, Penny; Yoo, T.; H. Hauser, H. Pfister, and J. J. van Wijk
As collections of 2D/3D images continue to grow, interest in effective ways to visualize and explore the statistical morphological properties of a group of images has surged. Recently, deformation models have emerged as simple methods to capture the variability and statistical properties of a collection of images. Such models have proven to be effective in tasks such as image classification, generation, registration, segmentation, and analysis of modes of variation. A crucial element missing from most statistical models has been an effective way to summarize and visualize the statistical morphological properties of a group of images. This paper evaluates different visualization techniques that can be extended and used to illustrate the information captured by such statistical models. First, four illustration techniques are described as methods to summarize the statistical morphological properties as captured by deformation models. Second, results of a user study conducted to compare the effectiveness of each visualization technique are presented. After comparing the performance of 40 subjects, we found that statistical annotation techniques present significant benefits when analyzing the structural properties of a group of images.
Complete Tensor Field Topology on 2D Triangulated Manifolds embedded in 3D
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Auer, Cornelia; Hotz, Ingrid; H. Hauser, H. Pfister, and J. J. van Wijk
This paper is concerned with the extraction of the surface topology of tensor fields on 2D triangulated manifolds embedded in 3D. In scientific visualization topology is a meaningful instrument to get a hold on the structure of a given dataset. Due to the discontinuity of tensor fields on a piecewise planar domain, standard topology extraction methods result in an incomplete topological skeleton. In particular with regard to the high computational costs of the extraction this is not satisfactory. This paper provides a method for topology extraction of tensor fields that leads to complete results. The core idea is to include the locations of discontinuity into the topological analysis. For this purpose the model of continuous transition bridges is introduced, which allows to capture the entire topology on the discontinuous field. The proposed method is applied to piecewise linear three-dimensional tensor fields defined on the vertices of the triangulation and for piecewise constant two or three-dimensional tensor fields given per triangle, e.g. rate of strain tensors of piecewise linear flow fields.
Stable Morse Decompositions for Piecewise Constant Vector Fields on Surfaces
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Szymczak, Andrzej; H. Hauser, H. Pfister, and J. J. van Wijk
Numerical simulations and experimental observations are inherently imprecise. Therefore, most vector fields of interest in scientific visualization are known only up to an error. In such cases, some topological features, especially those not stable enough, may be artifacts of the imprecision of the input. This paper introduces a technique to compute topological features of user-prescribed stability with respect to perturbation of the input vector field. In order to make our approach simple and efficient, we develop our algorithms for the case of piecewise constant (PC) vector fields. Our approach is based on a super-transition graph, a common graph representation of all PC vector fields whose vector value in a mesh triangle is contained in a convex set of vectors associated with that triangle. The graph is used to compute a Morse decomposition that is coarse enough to be correct for all vector fields satisfying the constraint. Apart from computing stable Morse decompositions, our technique can also be used to estimate the stability of Morse sets with respect to perturbation of the vector field or to compute topological features of continuous vector fields using the PC framework.
Topological Features in 2D Symmetric Higher-Order Tensor Fields
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Schultz, Thomas; H. Hauser, H. Pfister, and J. J. van Wijk
The topological structure of scalar, vector, and second-order tensor fields provides an important mathematical basis for data analysis and visualization. In this paper, we extend this framework towards higher-order tensors. First, we establish formal uniqueness properties for a geometrically constrained tensor decomposition. This allows us to define and visualize topological structures in symmetric tensor fields of orders three and four. We clarify that in 2D, degeneracies occur at isolated points, regardless of tensor order. However, for orders higher than two, they are no longer equivalent to isotropic tensors, and their fractional Poincaré index prevents us from deriving continuous vector fields from the tensor decomposition. Instead, sorting the terms by magnitude leads to a new type of feature, lines along which the resulting vector fields are discontinuous. We propose algorithms to extract these features and present results on higher-order derivatives and higher-order structure tensors.
Visual Boosting in Pixel-based Visualizations
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Oelke, Daniela; Janetzko, Halldor; Simon, Svenja; Neuhaus, Klaus; Keim, Daniel A.; H. Hauser, H. Pfister, and J. J. van Wijk
Pixel-based visualizations have become popular, because they are capable of displaying large amounts of data and at the same time provide many details. However, pixel-based visualizations are only effective if the data set is not sparse and the data distribution not random. Single pixels - no matter if they are in an empty area or in the middle of a large area of differently colored pixels - are perceptually difficult to discern and may therefore easily be missed. Furthermore, trends and interesting passages may be camouflaged in the sea of details. In this paper we compare different approaches for visual boosting in pixel-based visualizations. Several boosting techniques such as halos, background coloring, distortion, and hatching are discussed and assessed with respect to their effectiveness in boosting single pixels, trends, and interesting passages. Application examples from three different domains (document analysis, genome analysis, and geospatial analysis) show the general applicability of the techniques and the derived guidelines.
Dynamic Insets for Context-Aware Graph Navigation
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Ghani, Sohaib; Riche, N. Henry; Elmqvist, Niklas; H. Hauser, H. Pfister, and J. J. van Wijk
Maintaining both overview and detail while navigating in graphs, such as road networks, airline route maps, or social networks, is difficult, especially when targets of interest are located far apart. We present a navigation technique called Dynamic Insets that provides context awareness for graph navigation. Dynamic insets utilize the topological structure of the network to draw a visual inset for off-screen nodes that shows a portion of the surrounding area for links leaving the edge of the screen. We implement dynamic insets for general graph navigation as well as geographical maps. We also present results from a set of user studies that show that our technique is more efficient than most of the existing techniques for graph navigation in different networks.
Visualization of Time-Series Data in Parameter Space for Understanding Facial Dynamics
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Tam, Gary K. L.; Fang, H.; Aubrey, A. J.; Grant, P. W.; Rosin, P. L.; Marshall, D.; Chen, M.; H. Hauser, H. Pfister, and J. J. van Wijk
Over the past decade, computer scientists and psychologists have made great efforts to collect and analyze facial dynamics data that exhibit different expressions and emotions. Such data is commonly captured as videos and are transformed into feature-based time-series prior to any analysis. However, the analytical tasks, such as expression classification, have been hindered by the lack of understanding of the complex data space and the associated algorithm space. Conventional graph-based time-series visualization is also found inadequate to support such tasks. In this work, we adopt a visual analytics approach by visualizing the correlation between the algorithm space and our goal classifying facial dynamics. We transform multiple feature-based time-series for each expression in measurement space to a multi-dimensional representation in parameter space. This enables us to utilize parallel coordinates visualization to gain an understanding of the algorithm space, providing a fast and cost-effective means to support the design of analytical algorithms.
The Undistort Lens
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Brosz, John; Carpendale, Sheelagh; Nacenta, Miguel A.; H. Hauser, H. Pfister, and J. J. van Wijk
Detail-in-context lens techniques can be useful for exploring visualizations of data spaces that are too large or have too much detail to fit in regular displays. For example, by bending the space in the right way we can bring together details from two separate areas for easy comparison while roughly keeping the context that situates each area within the global space. While these techniques can be powerful tools, they also introduce distortions that need to be understood, and often the tools have to be disabled in order to have access to the undistorted data. We introduce the undistort lens, a complement to existing distortion-based techniques that provides a local and separate presentation of the original geometry without affecting any distortion-based lenses currently used in the presentation. The undistort lens is designed to allow interactive access to the underlying undistorted data within the context of the distorted space, and to enable a better understanding of the distortions. The paper describes the implementation of a generic back-mapping mechanism that enables the implementation of undistort lenses for arbitrary distortion based techniques, including those presented in the lens literature. We also provide a series of use-case scenarios that demonstrate the situations in which the technique can complement existing lenses.
Assisted Descriptor Selection Based on Visual Comparative Data Analysis
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Bremm, Sebastian; Landesberger, Tatiana von; Bernard, Jürgen; Schreck, Tobias; H. Hauser, H. Pfister, and J. J. van Wijk
Exploration and selection of data descriptors representing objects using a set of features are important components in many data analysis tasks. Usually, for a given dataset, an optimal data description does not exist, as the suitable data representation is strongly use case dependent. Many solutions for selecting a suitable data description have been proposed. In most instances, they require data labels and often are black box approaches. Non-expert users have difficulties to comprehend the coherency of input, parameters, and output of these algorithms. Alternative approaches, interactive systems for visual feature selection, overburden the user with an overwhelming set of options and data views. Therefore, it is essential to offer the users a guidance in this analytical process. In this paper, we present a novel system for data description selection, which facilitates the user's access to the data analysis process. As finding of suitable data description consists of several steps, we support the user with guidance. Our system combines automatic data analysis with interactive visualizations. By this, the system provides a recommendation for suitable data descriptor selections. It supports the comparison of data descriptors with differing dimensionality for unlabeled data. We propose specialized scores and interactive views for descriptor comparison. The visualization techniques are scatterplot-based and grid-based. For the latter case, we apply Self-Organizing Maps as adaptive grids which are well suited for large multi-dimensional data sets. As an example, we demonstrate the usability of our system on a real-world biochemical application.
Uncertainty-Aware Exploration of Continuous Parameter Spaces Using Multivariate Prediction
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Berger, Wolfgang; Piringer, H.; Filzmoser, P.; Gröller, Eduard; H. Hauser, H. Pfister, and J. J. van Wijk
Systems projecting a continuous n-dimensional parameter space to a continuous m-dimensional target space play an important role in science and engineering. If evaluating the system is expensive, however, an analysis is often limited to a small number of sample points. The main contribution of this paper is an interactive approach to enable a continuous analysis of a sampled parameter space with respect to multiple target values. We employ methods from statistical learning to predict results in real-time at any user-defined point and its neighborhood. In particular, we describe techniques to guide the user to potentially interesting parameter regions, and we visualize the inherent uncertainty of predictions in 2D scatterplots and parallel coordinates. An evaluation describes a realworld scenario in the application context of car engine design and reports feedback of domain experts. The results indicate that our approach is suitable to accelerate a local sensitivity analysis of multiple target dimensions, and to determine a sufficient local sampling density for interesting parameter regions.
Probabilistic Marching Cubes
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Pöthkow, Kai; Weber, Britta; Hege, Hans-Christian; H. Hauser, H. Pfister, and J. J. van Wijk
In this paper we revisit the computation and visualization of equivalents to isocontours in uncertain scalar fields. We model uncertainty by discrete random fields and, in contrast to previous methods, also take arbitrary spatial correlations into account. Starting with joint distributions of the random variables associated to the sample locations, we compute level crossing probabilities for cells of the sample grid. This corresponds to computing the probabilities that the well-known symmetry-reduced marching cubes cases occur in random field realizations. For Gaussian random fields, only marginal density functions that correspond to the vertices of the considered cell need to be integrated. We compute the integrals for each cell in the sample grid using a Monte Carlo method. The probabilistic ansatz does not suffer from degenerate cases that usually require case distinctions and solutions of ill-conditioned problems. Applications in 2D and 3D, both to synthetic and real data from ensemble simulations in climate research, illustrate the influence of spatial correlations on the spatial distribution of uncertain isocontours.
Structural Decomposition Trees
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Engel, Daniel; Rosenbaum, R.; Hamann, B.; Hagen, Hans; H. Hauser, H. Pfister, and J. J. van Wijk
Researchers and analysts in modern industrial and academic environments are faced with a daunting amount of multi-dimensional data. While there has been significant development in the areas of data mining and knowledge discovery, there is still the need for improved visualizations and generic solutions. The state-of-the-art in visual analytics and exploratory data visualization is to incorporate more profound analysis methods while focusing on fast interactive abilities. The common trend in these scenarios is to either visualize an abstraction of the data set or to better utilize screen-space. This paper presents a novel technique that combines clustering, dimension reduction and multi-dimensional data representation to form a multivariate data visualization that incorporates both detail and overview. This amalgamation counters the individual drawbacks of common projection and multi-dimensional data visualization techniques, namely ambiguity and clutter. A specific clustering criterion is used to decompose a multi-dimensional data set into a hierarchical tree structure. This decomposition is embedded in a novel Dimensional Anchor visualization through the use of a weighted linear dimension reduction technique. The resulting Structural Decomposition Tree (SDT) provides not only an insight of the data set's inherent structure, but also conveys detailed coordinate value information. Further, fast and intuitive interaction techniques are explored in order to guide the user in highlighting, brushing, and filtering of the data.
Depth of Field Effects for Interactive Direct Volume Rendering
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Schott, Mathias; Grosset, A. V. Pascal; Martin, Tobias; Pegoraro, Vincent; Smith, Sean T.; Hansen, Charles D.; H. Hauser, H. Pfister, and J. J. van Wijk
In this paper, a method for interactive direct volume rendering is proposed for computing depth of field effects, which previously were shown to aid observers in depth and size perception of synthetically generated images. The presented technique extends those benefits to volume rendering visualizations of 3D scalar fields from CT/MRI scanners or numerical simulations. It is based on incremental filtering and as such does not depend on any precomputation, thus allowing interactive explorations of volumetric data sets via on-the-fly editing of the shading model parameters or (multi-dimensional) transfer functions.
Fast Extraction of High-quality Crease Surfaces for Visual Analysis
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Barakat, Samer; Andrysco, N.; Tricoche, Xavier; H. Hauser, H. Pfister, and J. J. van Wijk
We present a novel algorithm for the efficient extraction and visualization of high-quality ridge and valley surfaces from numerical datasets. Despite their rapidly increasing popularity in visualization, these so-called crease surfaces remain challenging to compute owing to their strongly nonlinear and non-orientable nature, and their complex boundaries. In this context, existing meshing techniques require an extremely dense sampling that is computationally prohibitive. Our proposed solution intertwines sampling and meshing steps to yield an accurate approximation of the underlying surfaces while ensuring the geometric quality of the resulting mesh. Using the computation power of the GPU, we propose a fast, parallel method for sampling. Additionally, we present a new front propagation meshing strategy that leverages CPU multiprocessing. Results are shown for synthetic, medical and fluid dynamics datasets.
Visualizing the Positional and Geometrical Variability of Isosurfaces in Uncertain Scalar Fields
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Pfaffelmoser, Tobias; Reitinger, Matthias; Westermann, Rüdiger; H. Hauser, H. Pfister, and J. J. van Wijk
We present a novel approach for visualizing the positional and geometrical variability of isosurfaces in uncertain 3D scalar fields. Our approach extends recent work by Pöthkow and Hege [PH10] in that it accounts for correlations in the data to determine more reliable isosurface crossing probabilities. We introduce an incremental updatescheme that allows integrating the probability computation into front-to-back volume ray-casting efficiently. Our method accounts for homogeneous and anisotropic correlations, and it determines for each sampling interval along a ray the probability of crossing an isosurface for the first time. To visualize the positional and geometrical uncertainty even under viewing directions parallel to the surface normal, we propose a new color mapping scheme based on the approximate spatial deviation of possible surface points from the mean surface. The additional use of saturation enables to distinguish between areas of high and low statistical dependence. Experimental results confirm the effectiveness of our approach for the visualization of uncertainty related to position and shape of convex and concave isosurface structures.
Flowstrates: An Approach for Visual Exploration of Temporal Origin-Destination Data
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Boyandin, Ilya; Bertini, Enrico; Bak, Peter; Lalanne, Denis; H. Hauser, H. Pfister, and J. J. van Wijk
Many origin-destination datasets have become available in the recent years, e.g. flows of people, animals, money, material, or network traffic between pairs of locations, but appropriate techniques for their exploration still have to be developed. Especially, supporting the analysis of datasets with a temporal dimension remains a significant challenge. Many techniques for the exploration of spatio-temporal data have been developed, but they prove to be only of limited use when applied to temporal origin-destination datasets.We present Flowstrates, a new interactive visualization approach in which the origins and the destinations of the flows are displayed in two separate maps, and the changes over time of the flow magnitudes are represented in a separate heatmap view in the middle. This allows the users to perform spatial visual queries, focusing on different regions of interest for the origins and destinations, and to analyze the changes over time provided with the means of flow ordering, filtering and aggregation in the heatmap. In this paper, we discuss the challenges associated with the visualization of temporal origin-destination data, introduce our solution, and present several usage scenarios showing how the tool we have developed supports them.
Temporal Visualization of Boundary-based Geo-information Using Radial Projection
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Drocourt, Y.; Borgo, Rita; Scharrer, K.; Murray, T.; Bevan, S. I.; Chen, M.; H. Hauser, H. Pfister, and J. J. van Wijk
This work is concerned with a design study by an interdisciplinary team on visualizing a 10-year record of seasonal and inter-annual changes in frontal position (advance/retreat) of nearly 200 marine terminating glaciers in Greenland. Whilst the spatiotemporal nature of the raw data presents a challenge to develop a compact and intuitive visual design, the focus on coastal boundaries provides an opportunity for dimensional reduction. In this paper, we report the user-centered design process carried out by the team, and present several visual encoding schemes that have met the requirements including compactness, intuitiveness, and ability to depict temporal changes and spatial relations. In particular, we designed a family of radial visualization, where radial lines correspond to different coastal locations, and nested rings represent the evolution of the temporal dimension from inner to outer circles. We developed an algorithm for mapping glacier terminus positions from Cartesian coordinates to angular coordinates. Instead of a naive uniform mapping, the algorithm maintains consistent spatial perception of the visually-sensitive geographical references between their Cartesian and angular coordinates, and distributes other termini positions between primary locations based on coastal distance. This work has provided a useful solution to address the problem of inaccuracy in change evaluation based on pixel-based visualization [BPC*10].
WaveMap: Interactively Discovering Features From Protein Flexibility Matrices Using Wavelet-based Visual Analytics
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Barlowe, Scott; Liu, Yujie; Yang, Jing; Livesay, Dennis R.; Jacobs, Donald J.; Mottonen, James; Verma, Deeptak; H. Hauser, H. Pfister, and J. J. van Wijk
The knowledge gained from biology datasets can streamline and speed-up pharmaceutical development. However, computational models generate so much information regarding protein behavior that large-scale analysis by traditional methods is almost impossible. The volume of data produced makes the transition from data to knowledge difficult and hinders biomedical advances. In this work, we present a novel visual analytics approach named WaveMap for exploring data generated by a protein flexibility model. WaveMap integrates wavelet analysis, visualizations, and interactions to facilitate the browsing, feature identification, and comparison of protein attributes represented by two-dimensional plots. We have implemented a fully working prototype of WaveMap and illustrate its usefulness through expert evaluation and an example scenario.
Pathway Preserving Representation of Metabolic Networks
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Lambert, Antoine; Dubois, J.; Bourqui, Romain; H. Hauser, H. Pfister, and J. J. van Wijk
Improvements in biological data acquisition and genomes sequencing now allow to reconstruct entire metabolic networks of many living organisms. The size and complexity of these networks prohibit manual drawing and thereby urge the need of dedicated visualization techniques. An efficient representation of such a network should preserve the topological information of metabolic pathways while respecting biological drawing conventions. These constraints complicate the automatic generation of such visualization as it raises graph drawing issues. In this paper we propose a method to lay out the entire metabolic network while preserving the pathway information as much as possible. That method is flexible as it enables the user to define whether or not node duplication should be performed, to preserve or not the network topology. Our technique combines partitioning, node placement and edge bundling to provide a pseudo-orthogonal visualization of the metabolic network. To ease pathway information retrieval, we also provide complementary interaction tools that emphasize relevant pathways in the entire metabolic context.
Visualising Errors in Animal Pedigree Genotype Data
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Graham, Martin; Kennedy, Jessie; Paterson, Trevor; Law, Andy; H. Hauser, H. Pfister, and J. J. van Wijk
Genetic analysis of a breeding animal population involves determining the inheritance pattern of genotypes for multiple genetic markers across the individuals in the population pedigree structure. However, experimental pedigree genotype data invariably contains errors in both the pedigree structure and in the associated individual genotypes, introducing inconsistencies into the dataset, rendering them useless for further analysis. The resolution of these errors requires consideration of genotype inheritance patterns in the context of the pedigree structure. Existing pedigree visualisations are typically more suited to human pedigrees and are less suitable for large complex animal pedigrees which may exhibit cross generational inbreeding. Similarly, table-based viewers of genotype marker data can highlight where errors become apparent but lack the functionality and interactive visual feedback to allow users to locate the origin of errors within the pedigree. In this paper, we detail a design study steered by biologists who work with pedigree data, and describe successive iterations through approaches and prototypes for viewing genotyping errors in the context of a displayed pedigree. We describe how each approach performs with real pedigree genotype data and why even-tually we deemed them unsuitable. Finally, a novel prototype visualisation for pedigrees, which we term the 'sandwich view', is detailed and we demonstrate how the approach effectively communicates errors in the pedigree context, supporting the biologist in the error identification task.
Visualization and Analysis of Eddies in a Global Ocean Simulation
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Williams, S.; Hecht, M.; Petersen, M.; Strelitz, R.; Maltrud, M.; Ahrens, J.; Hlawitschka, M.; Hamann, B.; H. Hauser, H. Pfister, and J. J. van Wijk
We present analysis and visualization of flow data from a high-resolution simulation of the dynamical behavior of the global ocean. Of particular scientific interest are coherent vortical features called mesoscale eddies. We first extract high-vorticity features using a metric from the oceanography community called the Okubo-Weiss parameter. We then use a new circularity criterion to differentiate eddies from other non-eddy features like meanders in strong background currents. From these data, we generate visualizations showing the three-dimensional structure and distribution of ocean eddies. Additionally, the characteristics of each eddy are recorded to form an eddy census that can be used to investigate correlations among variables such as eddy thickness, depth, and location. From these analyses, we gain insight into the role eddies play in large-scale ocean circulation.
Anatomy-Guided Multi-Level Exploration of Blood Flow in Cerebral Aneurysms
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Neugebauer, Mathias; Janiga, Gabor; Beuing, Oliver; Skalej, Martin; Preim, Bernhard; H. Hauser, H. Pfister, and J. J. van Wijk
For cerebral aneurysms, the ostium, the area of inflow, is an important anatomic landmark, since it separates the pathological vessel deformation from the healthy parent vessel. A better understanding of the inflow characteristics, the flow inside the aneurysm and the overall change of pre- and post-aneurysm flow in the parent vessel provide insights for medical research and the development of new risk-reduced treatment options. We present an approach for a qualitative, visual flow exploration that incorporates the ostium and derived anatomical landmarks. It is divided into three scopes: a global scope for exploration of the in- and outflow, an ostium scope that provides characteristics of the flow profile close to the ostium and a local scope for a detailed exploration of the flow in the parent vessel and the aneurysm. The approach was applied to five representative datasets, including measured and simulated blood flow. Informal interviews with two board-certified radiologists confirmed the usefulness of the provided exploration tools and delivered input for the integration of the ostium-based flow analysis into the overall exploration workflow.
A Shader Framework for Rapid Prototyping of GPU-Based Volume Rendering
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Rieder, Christian; Palmer, Stephan; Link, Florian; Hahn, Horst K.; H. Hauser, H. Pfister, and J. J. van Wijk
In this paper, we present a rapid prototyping framework for GPU-based volume rendering. Therefore, we propose a dynamic shader pipeline based on the SuperShader concept and illustrate the design decisions. Also, important requirements for the development of our system are presented. In our approach, we break down the rendering shader into areas containing code for different computations, which are defined as freely combinable, modularized shader blocks. Hence, high-level changes of the rendering configuration result in the implicit modification of the underlying shader pipeline. Furthermore, the prototyping system allows inserting custom shader code between shader blocks of the pipeline at run-time. A suitable user interface is available within the prototyping environment to allow intuitive modification of the shader pipeline. Thus, appropriate solutions for visualization problems can be interactively developed. We demonstrate the usage and the usefulness of our framework with implementations of dynamic rendering effects for medical applications.
Prostate Cancer Visualization from MR Imagery and MR Spectroscopy
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Marino, Joseph; Kaufman, Arie; H. Hauser, H. Pfister, and J. J. van Wijk
Prostate cancer is one of the most prevalent cancers among males, and the use of magnetic resonance imaging (MRI) has been suggested for its detection. A framework is presented for scoring and visualizing various MR data in an efficient and intuitive manner. A classification method is introduced where a cumulative score volume is created which takes into account each of three acquisition types. This score volume is integrated into a volume rendering framework which allows the user to view the prostate gland, the multi-modal score values, and the sur- rounding anatomy. A visibility persistence mode is introduced to automatically avoid full occlusion of a selected score and indicate overlaps. The use of GPU-accelerated multi-modal single-pass ray casting provides an inter- active experience. User driven importance rendering allows the user to gain insight into the data and can assist in localization of the disease and treatment planning. We evaluate our results against pathology and radiologists' determinations.
Visualizing the Evolution of Community Structures in Dynamic Social Networks
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Reda, Khairi; Tantipathananandh, Chayant; Johnson, Andrew; Leigh, Jason; Berger-Wolf, Tanya; H. Hauser, H. Pfister, and J. J. van Wijk
Social network analysis is the study of patterns of interaction between social entities. The field is attracting increasing attention from diverse disciplines including sociology, epidemiology, and behavioral ecology. An important sociological phenomenon that draws the attention of analysts is the emergence of communities, which tend to form, evolve, and dissolve gradually over a period of time. Understanding this evolution is crucial to sociologists and domain scientists, and often leads to a better appreciation of the social system under study. Therefore, it is imperative that social network visualization tools support this task. While graph-based representations are well suited for investigating structural properties of networks at a single point in time, they appear to be significantly less useful when used to analyze gradual structural changes over a period of time. In this paper, we present an interactive visualization methodology for dynamic social networks. Our technique focuses on revealing the community structure implied by the evolving interaction patterns between individuals. We apply our visualization to analyze the community structure in the US House of Representatives. We also report on a user study conducted with the participation of behavioral ecologists working with social network datasets that depict interactions between wild animals. Findings from the user study confirm that the visualization was helpful in providing answers to sociological questions as well as eliciting new observations on the social organization of the population under study.
ImPrEd: An Improved Force-Directed Algorithm that Prevents Nodes from Crossing Edges
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Simonetto, Paolo; Archambault, Daniel; Auber, David; Bourqui, Romain; H. Hauser, H. Pfister, and J. J. van Wijk
PrEd [Ber00] is a force-directed algorithm that improves the existing layout of a graph while preserving its edge crossing properties. The algorithm has a number of applications including: improving the layouts of planar graph drawing algorithms, interacting with a graph layout, and drawing Euler-like diagrams. The algorithm ensures that nodes do not cross edges during its execution. However, PrEd can be computationally expensive and overlyrestrictive in terms of node movement. In this paper, we introduce ImPrEd: an improved version of PrEd that overcomes some of its limitations and widens its range of applicability. ImPrEd also adds features such as flexible or crossable edges, allowing for greater control over the output. Flexible edges, in particular, can improve the distribution of graph elements and the angular resolution of the input graph. They can also be used to generate Euler diagrams with smooth boundaries. As flexible edges increase data set size, we experience an execution/drawing quality trade off. However, when flexible edges are not used, ImPrEd proves to be consistently faster than PrEd.
Visual Recommendations for Network Navigation
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Crnovrsanin, Tarik; Liao, Isaac; Wuy, Yingcai; Ma, Kwan-Liu; H. Hauser, H. Pfister, and J. J. van Wijk
Understanding large, complex networks is important for many critical tasks, including decision making, process optimization, and threat detection. Existing network analysis tools often lack intuitive interfaces to support the exploration of large scale data. We present a visual recommendation system to help guide users during navigation of network data. Collaborative filtering, similarity metrics, and relative importance are used to generate recommendations of potentially significant nodes for users to explore. In addition, graph layout and node visibility are adjusted in real-time to accommodate recommendation display and to reduce visual clutter. Case studies are presented to show how our design can improve network exploration.
A Gradient-Based Comparison Measure for Visual analysis of Multifield Data
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Nagaraj, Suthambhara; Natarajan, Vijay; Nanjundiah, Ravi S.; H. Hauser, H. Pfister, and J. J. van Wijk
We introduce a multifield comparison measure for scalar fields that helps in studying relations between them. The comparison measure is insensitive to noise in the scalar fields and to noise in their gradients. Further, it can be computed robustly and efficiently. Results from the visual analysis of various data sets from climate science and combustion applications demonstrate the effective use of the measure.
Piecewise Laplacian-based Projection for Interactive Data Exploration and Organization
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Paulovich, Fernando V.; Eler, D. M.; Poco, J.; Botha, Charl P.; Minghim, R.; Nonato, L. G.; H. Hauser, H. Pfister, and J. J. van Wijk
Multidimensional projection has emerged as an important visualization tool in applications involving the visual analysis of high-dimensional data. However, high precision projection methods are either computationally expensive or not flexible enough to enable feedback from user interaction into the projection process. A built-in mechanism that dynamically adapts the projection based on direct user intervention would make the technique more useful for a larger range of applications and data sets. In this paper we propose the Piecewise Laplacian-based Projection (PLP), a novel multidimensional projection technique, that, due to the local nature of its formulation, enables a versatile mechanism to interact with projected data and to allow interactive changes to alter the projection map dynamically, a capability unique of this technique. We exploit the flexibility provided by PLP in two interactive projection-based applications, one designed to organize pictures visually and another to build music playlists. These applications illustrate the usefulness of PLP in handling high-dimensional data in a flexible and highly visual way. We also compare PLP with the currently most promising projections in terms of precision and speed, showing that it performs very well also according to these quality criteria.
A Framework for Exploring Multidimensional Data with 3D Projections
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Poco, Jorge; Etemadpour, Ronak; Paulovich, F. V.; Long, T. V.; Rosenthal, P.; Oliveira, M. C. F.; Linsen, Lars; Minghim, R.; H. Hauser, H. Pfister, and J. J. van Wijk
Visualization of high-dimensional data requires a mapping to a visual space. Whenever the goal is to preserve similarity relations a frequent strategy is to use 2D projections, which afford intuitive interactive exploration, e.g., by users locating and selecting groups and gradually drilling down to individual objects. In this paper, we propose a framework for projecting high-dimensional data to 3D visual spaces, based on a generalization of the Least- Square Projection (LSP). We compare projections to 2D and 3D visual spaces both quantitatively and through a user study considering certain exploration tasks. The quantitative analysis confirms that 3D projections outperform 2D projections in terms of precision. The user study indicates that certain tasks can be more reliably and confidently answered with 3D projections. Nonetheless, as 3D projections are displayed on 2D screens, interaction is more difficult. Therefore, we incorporate suitable interaction functionalities into a framework that supports 3D transformations, predefined optimal 2D views, coordinated 2D and 3D views, and hierarchical 3D cluster definition and exploration. For visually encoding data clusters in a 3D setup, we employ color coding of projected data points as well as four types of surface renderings. A second user study evaluates the suitability of these visual encodings. Several examples illustrate the framework's applicability for both visual exploration of multidimensional abstract (non-spatial) data as well as the feature space of multi-variate spatial data.
Visualizing High-Dimensional Structures by Dimension Ordering and Filtering using Subspace Analysis
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Ferdosi, Bilkis J.; H. Hauser, H. Pfister, and J. J. van Wijk
High-dimensional data visualization is receiving increasing interest because of the growing abundance of highdimensional datasets. To understand such datasets, visualization of the structures present in the data, such as clusters, can be an invaluable tool. Structures may be present in the full high-dimensional space, as well as in its subspaces. Two widely used methods to visualize high-dimensional data are the scatter plot matrix (SPM) and the parallel coordinate plot (PCP). SPM allows a quick overview of the structures present in pairwise combinations of dimensions. On the other hand, PCP has the potential to visualize not only bi-dimensional structures but also higher dimensional ones. A problem with SPM is that it suffers from crowding and clutter which makes interpretation hard. Approaches to reduce clutter are available in the literature, based on changing the order of the dimensions. However, usually this reordering has a high computational complexity. For effective visualization of high-dimensional structures, also PCP requires a proper ordering of the dimensions. In this paper, we propose methods for reordering dimensions in PCP in such a way that high-dimensional structures (if present) become easier to perceive. We also present a method for dimension reordering in SPM which yields results that are comparable to those of existing approaches, but at a much lower computational cost. Our approach is based on finding relevant subspaces for clustering using a quality criterion and cluster information. The quality computation and cluster detection are done in image space, using connected morphological operators. We demonstrate the potential of our approach for synthetic and astronomical datasets, and show that our method compares favorably with a number of existing approaches.
Tablorer - An Interactive Tree Visualization System for Tablet PCs
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Shin, HyunJu; Park, GwangHyun; Han, JungHyun; H. Hauser, H. Pfister, and J. J. van Wijk
A variety of mobile devices are available today, but there is no dominant tree visualization system in the devices. This paper proposes Tablorer, a novel interactive tree visualization system for medium-sized mobile devices, especially for tablet PCs. The system shows the hierarchical information with a compact way using an expandable table format. For efficient navigation, the system provides an integrated view of context and focus information. The experimental results show that Tablorer can reduce the search time by about 22%.
Comparison of Multiple Weighted Hierarchies: Visual Analytics for Microbe Community Profiling
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Dinkla, Kasper; Westenberg, M. A.; Timmerman, H. M.; Hijum, S.A.F.T. van; Wijk, J. J. van; H. Hauser, H. Pfister, and J. J. van Wijk
We propose visual analytics techniques to support concurrent comparison of hundreds of cumulatively weighted instances of a single hierarchy. This includes a node-link representation of the hierarchy where nodes depict the weights of all instances with high-density heat maps that are grouped and aligned to ease cross-referencing. Hierarchy exploration is facilitated by smoothly animated expansion and collapse of its branches. Detailed infor- mation about hierarchy structure, weights, and meta-data is provided by secondary linked visualizations. These techniques have been implemented in a prototype tool, in which the computational analysis concerns have been strictly separated from the visualization concerns. The analysis algorithms are extensible via a script engine. We discuss the effectiveness of our techniques for the visual analytic process of microbe community profiling experts.
Automatic Registration of Multi-Projector Domes Using a Single Uncalibrated Camera
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Sajadi, Behzad; Majumder, Aditi; H. Hauser, H. Pfister, and J. J. van Wijk
In this paper we present a novel technique for easily calibrating multiple casually aligned projectors on spherical domes using a single uncalibrated camera. Using the prior knowledge of the display surface being a dome, we can estimate the camera intrinsic and extrinsic parameters and the projector to display surface correspondences automatically using a set of images. These images include the image of the dome itself and a projected pattern from each projector. Using these correspondences we can register images from the multiple projectors on the dome. Further, we can register displays which are not entirely visible in a single camera view using multiple pan and tilted views of an uncalibrated camera making our method suitable for displays of different size and resolution. We can register images from any arbitrary viewpoint making it appropriate for a single head-tracked user in a 3D visualization system. Also, we can use several cartographic mapping techniques to register images in a manner that is appropriate for multi-user visualization. Domes are known to produce a tremendous sense of immersion and presence in visualization systems. Yet, till date, there exists no easy way to register multiple projectors on a dome to create a high-resolution realistic visualizations. To the best of our knowledge, this is the first method that can achieve accurate geometric registration of multiple projectors on a dome simply and automatically using a single uncalibrated camera.
In-situ Sampling of a Large-Scale Particle Simulation for Interactive Visualization and Analysis
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Woodring, Jonathan; Ahrens, J.; Figg, J.; Wendelberger, J.; Habib, S.; Heitmann, K.; H. Hauser, H. Pfister, and J. J. van Wijk
We describe a simulation-time random sampling of a large-scale particle simulation, the RoadRunner Universe MC3 cosmological simulation, for interactive post-analysis and visualization. Simulation data generation rates will continue to be far greater than storage bandwidth rates by many orders of magnitude. This implies that only a very small fraction of data generated by a simulation can ever be stored and subsequently post-analyzed. The limiting factors in this situation are similar to the problem in many population surveys: there aren't enough human resources to query a large population. To cope with the lack of resources, statistical sampling techniques are used to create a representative data set of a large population. Following this analogy, we propose to store a simulationtime random sampling of the particle data for post-analysis, with level-of-detail organization, to cope with the bottlenecks. A sample is stored directly from the simulation in a level-of-detail format for post-visualization and analysis, which amortizes the cost of post-processing and reduces workflow time. Additionally by sampling during the simulation, we are able to analyze the entire particle population to record full population statistics and quantify sample error.

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