36-Issue 3

Permanent URI for this collection

EuroVis 2017 - 19th EG/VGTC Conference on Visualization
Barcelona, Spain 12-16 June 2017
Scalar Field Analysis
Global Feature Tracking and Similarity Estimation in Time-Dependent Scalar Fields
Himangshu Saikia and Tino Weinkauf
Nested Tracking Graphs
Jonas Lukasczyk, Gunther Weber, Ross Maciejewski, Christoph Garth, and Heike Leitte
Computing Contour Trees for 2D Piecewise Polynomial Functions
Girijanandan Nucha, Georges-Pierre Bonneau, Stefanie Hahmann, and Vijay Natarajan
Compactly Supported Biorthogonal Wavelet Bases on the Body Centered Cubic Lattice
Joshua J. Horacsek and Usman R. Alim
Evaluating Visualization
Constructing and Evaluating Visualisation Task Classifications: Process and Considerations
Natalie Kerracher and Jessie Kennedy
An Empirical Study on the Reliability of Perceiving Correlation Indices using Scatterplots
Varshita Sher, Karen G. Bemis, Ilaria Liccardi, and Min Chen
Empirically Measuring Soft Knowledge in Visualization
Natchaya Kijmongkolchai, Alfie Abdul-Rahman, and Min Chen
Visual Comparison of Eye Movement Patterns
Tanja Blascheck, Markus Schweizer, Fabian Beck, and Thomas Ertl
Biomedical Visualization
Glyph-Based Comparative Stress Tensor Visualization in Cerebral Aneurysms
Monique Meuschke, Samuel Voß, Oliver Beuing, Bernhard Preim, and Kai Lawonn
Visual Verification of Cancer Staging for Therapy Decision Support
Mario A. Cypko, Jan Wojdziak, Matthaeus Stoehr, Bettina Kirchner, Bernhard Preim, Andreas Dietz, Heinz U. Lemke, and Steffen Oeltze-Jafra
Overview + Detail Visualization for Ensembles of Diffusion Tensors
Changgong Zhang, Matthan W. A. Caan, Thomas Höllt, Elmar Eisemann, and Anna Vilanova
Visualizing the Uncertainty of Graph-based 2D Segmentation with Min-path Stability
Brian Summa, Julien Tierny, and Valerio Pascucci
Plots, Plots, Plots
Sclow Plots: Visualizing Empty Space
Joachim Giesen, Lars Kühne, and Philipp Lucas
Interactive Regression Lens for Exploring Scatter Plots
Lin Shao, Aishwarya Mahajan, Tobias Schreck, and Dirk J. Lehmann
Sliceplorer: 1D Slices for Multi-dimensional Continuous Functions
Thomas Torsney-Weir, Michael Sedlmair, and Torsten Möller
Stardust: Accessible and Transparent GPU Support for Information Visualization Rendering
Donghao Ren, Bongshin Lee, and Tobias Höllerer
Text and Time Visualization
Interactive Ambiguity Resolution of Named Entities in Fictional Literature
Florian Stoffel, Wolfgang Jentner, Michael Behrisch, Johannes Fuchs, and Daniel A. Keim
Integrating Visual Analytics Support for Grounded Theory Practice in Qualitative Text Analysis
Senthil Chandrasegaran, Sriram Karthik Badam, Lorraine Kisselburgh, Karthik Ramani, and Niklas Elmqvist
NEREx: Named-Entity Relationship Exploration in Multi-Party Conversations
Mennatallah El-Assady, Rita Sevastjanova, Bela Gipp, Daniel A. Keim, and Christopher Collins
Cycle Plot Revisited: Multivariate Outlier Detection Using a Distance-Based Abstraction
Markus Bögl, Peter Filzmoser, Theresia Gschwandtner, Tim Lammarsch, Roger A. Leite, Silvia Miksch, and Alexander Rind
Data Processing
Visual Analysis of Confocal Raman Spectroscopy Data using Cascaded Transfer Function Design
Christoph Markus Schikora, Markus Plack, Rainer Bornemann, Peter Haring Bolívar, and Andreas Kolb
Graph Visualization
Graffinity: Visualizing Connectivity in Large Graphs
Ethan Kerzner, Alexander Lex, Crystal Lynn Sigulinsky, Timothy Urness, Bryan William Jones, Robert E. Marc, and Miriah Meyer
Visualizing a Sequence of a Thousand Graphs (or Even More)
Michael Burch, Marcel Hlawatsch, and Daniel Weiskopf
Visual Exploration of Global Trade Networks with Time-Dependent and Weighted Hierarchical Edge Bundles on GPU
Johannes Hofmann, Michael Größler, Manuel Rubio-Sánchez, Peter-Paul Pichler, and Dirk J. Lehmann
Graph Layouts by t-SNE
J. F. Kruiger, Paulo E. Rauber, Rafael Messias Martins, Andreas Kerren, Stephen Kobourov, and Alexandru C. Telea
Applications and Design Studies
Comparing Personal Image Collections with PICTuReVis
Paul van der Corput and Jarke J. van Wijk
Dynamic Visual Abstraction of Soccer Movement
Dominik Sacha, Feeras Al-Masoudi, Manuel Stein, Tobias Schreck, Daniel A. Keim, Gennady Andrienko, and Halldór Janetzko
Visualization of Delay Uncertainty and its Impact on Train Trip Planning: A Design Study
Marcel Wunderlich, Kathrin Ballweg, Georg Fuchs, and Tatiana von Landesberger
Comparative Visual Analysis of Structure-Performance Relations in Complex Bulk-Heterojunction Morphologies
Amal Aboulhassan, Ronell Sicat, Daniel Baum, Olga Wodo, and Markus Hadwiger
Visual Encoding Analysis
Measuring Symmetry in Drawings of Graphs
Eric Welch and Stephen Kobourov
Reverse-Engineering Visualizations: Recovering Visual Encodings from Chart Images
Jorge Poco and Jeffrey Heer
Finding a Clear Path: Structuring Strategies for Visualization Sequences
Jessica Hullman, Robert Kosara, and Heidi Lam
Visual Narrative Flow: Exploring Factors Shaping Data Visualization Story Reading Experiences
Sean McKenna, Nathalie Henry Riche, Bongshin Lee, Jeremy Boy, and Miriah Meyer
Multi and High Dimensional Visualization
Adaptable Radial Axes Plots for Improved Multivariate Data Visualization
Manuel Rubio-Sánchez, Alberto Sanchez, and Dirk J. Lehmann
Linear Discriminative Star Coordinates for Exploring Class and Cluster Separation of High Dimensional Data
Yunhai Wang, Jingting Li, Feiping Nie, Holger Theisel, Minglun Gong, and Dirk J. Lehmann
Understanding Indirect Causal Relationships in Node-Link Graphs
Juhee Bae, Tove Helldin, and Maria Riveiro
Geo and Space Visualization
Minimum-Displacement Overlap Removal for Geo-referenced Data Visualization
Mereke van Garderen, Barbara Pampel, Arlind Nocaj, and Ulrik Brandes
Generating Tile Maps
Graham McNeill and Scott A. Hale
Illustrative Visualization of Mesoscale Ocean Eddies
Li Liu, Deborah Silver, Karen Bemis, Dujuan Kang, and Enrique Curchitser
Dynamic Scene Graph: Enabling Scaling, Positioning, and Navigation in the Universe
Emil Axelsson, Jonathas Costa, Cláudio Silva, Carter Emmart, Alexander Bock, and Anders Ynnerman
Uncertainty
Visualizing Probabilistic Multi-Phase Fluid Simulation Data using a Sampling Approach
Mathias Hummel, Lisa Jöckel, Jan Schäfer, Mark Werner Hlawitschka, and Christoph Garth
Uncertainty Footprint: Visualization of Nonuniform Behavior of Iterative Algorithms Applied to 4D Cell Tracking
Yong Wan and Charles Hansen
Interaction and Presentation
Steering the Craft: UI Elements and Visualizations for Supporting Progressive Visual Analytics
Sriram Karthik Badam, Niklas Elmqvist, and Jean-Daniel Fekete
GraSp: Combining Spatially-aware Mobile Devices and a Display Wall for Graph Visualization and Interaction
Ulrike Kister, Konstantin Klamka, Christian Tominski, and Raimund Dachselt
Internal and External Visual Cue Preferences for Visualizations in Presentations
Ha-Kyung Kong, Zhicheng Liu, and Karrie Karahalios
CoreFlow: Extracting and Visualizing Branching Patterns from Event Sequences
Zhicheng Liu, Bernard Kerr, Mira Dontcheva, Justin Grover, Matthew Hoffman, and Alan Wilson

BibTeX (36-Issue 3)
                
@article{
10.1111:cgf.13163,
journal = {Computer Graphics Forum}, title = {{
Global Feature Tracking and Similarity Estimation in Time-Dependent Scalar Fields}},
author = {
Saikia, Himangshu
and
Weinkauf, Tino
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13163}
}
                
@article{
10.1111:cgf.13164,
journal = {Computer Graphics Forum}, title = {{
Nested Tracking Graphs}},
author = {
Lukasczyk, Jonas
and
Weber, Gunther
and
Maciejewski, Ross
and
Garth, Christoph
and
Leitte, Heike
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13164}
}
                
@article{
10.1111:cgf.13165,
journal = {Computer Graphics Forum}, title = {{
Computing Contour Trees for 2D Piecewise Polynomial Functions}},
author = {
Nucha, Girijanandan
and
Bonneau, Georges-Pierre
and
Hahmann, Stefanie
and
Natarajan, Vijay
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13165}
}
                
@article{
10.1111:cgf.13166,
journal = {Computer Graphics Forum}, title = {{
Compactly Supported Biorthogonal Wavelet Bases on the Body Centered Cubic Lattice}},
author = {
Horacsek, Joshua J.
and
Alim, Usman R.
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13166}
}
                
@article{
10.1111:cgf.13168,
journal = {Computer Graphics Forum}, title = {{
An Empirical Study on the Reliability of Perceiving Correlation Indices using Scatterplots}},
author = {
Sher, Varshita
and
Bemis, Karen G.
and
Liccardi, Ilaria
and
Chen, Min
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13168}
}
                
@article{
10.1111:cgf.13167,
journal = {Computer Graphics Forum}, title = {{
Constructing and Evaluating Visualisation Task Classifications: Process and Considerations}},
author = {
Kerracher, Natalie
and
Kennedy, Jessie
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13167}
}
                
@article{
10.1111:cgf.13169,
journal = {Computer Graphics Forum}, title = {{
Empirically Measuring Soft Knowledge in Visualization}},
author = {
Kijmongkolchai, Natchaya
and
Abdul-Rahman, Alfie
and
Chen, Min
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13169}
}
                
@article{
10.1111:cgf.13170,
journal = {Computer Graphics Forum}, title = {{
Visual Comparison of Eye Movement Patterns}},
author = {
Blascheck, Tanja
and
Schweizer, Markus
and
Beck, Fabian
and
Ertl, Thomas
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13170}
}
                
@article{
10.1111:cgf.13171,
journal = {Computer Graphics Forum}, title = {{
Glyph-Based Comparative Stress Tensor Visualization in Cerebral Aneurysms}},
author = {
Meuschke, Monique
and
Voß, Samuel
and
Beuing, Oliver
and
Preim, Bernhard
and
Lawonn, Kai
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13171}
}
                
@article{
10.1111:cgf.13172,
journal = {Computer Graphics Forum}, title = {{
Visual Verification of Cancer Staging for Therapy Decision Support}},
author = {
Cypko, Mario A.
and
Wojdziak, Jan
and
Stoehr, Matthaeus
and
Kirchner, Bettina
and
Preim, Bernhard
and
Dietz, Andreas
and
Lemke, Heinz U.
and
Oeltze-Jafra, Steffen
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13172}
}
                
@article{
10.1111:cgf.13173,
journal = {Computer Graphics Forum}, title = {{
Overview + Detail Visualization for Ensembles of Diffusion Tensors}},
author = {
Zhang, Changgong
and
Caan, Matthan W. A.
and
Höllt, Thomas
and
Eisemann, Elmar
and
Vilanova, Anna
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13173}
}
                
@article{
10.1111:cgf.13175,
journal = {Computer Graphics Forum}, title = {{
Sclow Plots: Visualizing Empty Space}},
author = {
Giesen, Joachim
and
Kühne, Lars
and
Lucas, Philipp
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13175}
}
                
@article{
10.1111:cgf.13174,
journal = {Computer Graphics Forum}, title = {{
Visualizing the Uncertainty of Graph-based 2D Segmentation with Min-path Stability}},
author = {
Summa, Brian
and
Tierny, Julien
and
Pascucci, Valerio
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13174}
}
                
@article{
10.1111:cgf.13176,
journal = {Computer Graphics Forum}, title = {{
Interactive Regression Lens for Exploring Scatter Plots}},
author = {
Shao, Lin
and
Mahajan, Aishwarya
and
Schreck, Tobias
and
Lehmann, Dirk J.
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13176}
}
                
@article{
10.1111:cgf.13177,
journal = {Computer Graphics Forum}, title = {{
Sliceplorer: 1D Slices for Multi-dimensional Continuous Functions}},
author = {
Torsney-Weir, Thomas
and
Sedlmair, Michael
and
Möller, Torsten
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13177}
}
                
@article{
10.1111:cgf.13178,
journal = {Computer Graphics Forum}, title = {{
Stardust: Accessible and Transparent GPU Support for Information Visualization Rendering}},
author = {
Ren, Donghao
and
Lee, Bongshin
and
Höllerer, Tobias
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13178}
}
                
@article{
10.1111:cgf.13179,
journal = {Computer Graphics Forum}, title = {{
Interactive Ambiguity Resolution of Named Entities in Fictional Literature}},
author = {
Stoffel, Florian
and
Jentner, Wolfgang
and
Behrisch, Michael
and
Fuchs, Johannes
and
Keim, Daniel A.
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13179}
}
                
@article{
10.1111:cgf.13180,
journal = {Computer Graphics Forum}, title = {{
Integrating Visual Analytics Support for Grounded Theory Practice in Qualitative Text Analysis}},
author = {
Chandrasegaran, Senthil
and
Badam, Sriram Karthik
and
Kisselburgh, Lorraine
and
Ramani, Karthik
and
Elmqvist, Niklas
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13180}
}
                
@article{
10.1111:cgf.13181,
journal = {Computer Graphics Forum}, title = {{
NEREx: Named-Entity Relationship Exploration in Multi-Party Conversations}},
author = {
El-Assady, Mennatallah
and
Sevastjanova, Rita
and
Gipp, Bela
and
Keim, Daniel A.
and
Collins, Christopher
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13181}
}
                
@article{
10.1111:cgf.13182,
journal = {Computer Graphics Forum}, title = {{
Cycle Plot Revisited: Multivariate Outlier Detection Using a Distance-Based Abstraction}},
author = {
Bögl, Markus
and
Filzmoser, Peter
and
Gschwandtner, Theresia
and
Lammarsch, Tim
and
Leite, Roger A.
and
Miksch, Silvia
and
Rind, Alexander
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13182}
}
                
@article{
10.1111:cgf.13183,
journal = {Computer Graphics Forum}, title = {{
Visual Analysis of Confocal Raman Spectroscopy Data using Cascaded Transfer Function Design}},
author = {
Schikora, Christoph Markus
and
Plack, Markus
and
Bornemann, Rainer
and
Bolívar, Peter Haring
and
Kolb, Andreas
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13183}
}
                
@article{
10.1111:cgf.13184,
journal = {Computer Graphics Forum}, title = {{
Graffinity: Visualizing Connectivity in Large Graphs}},
author = {
Kerzner, Ethan
and
Lex, Alexander
and
Sigulinsky, Crystal Lynn
and
Urness, Timothy
and
Jones, Bryan William
and
Marc, Robert E.
and
Meyer, Miriah
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13184}
}
                
@article{
10.1111:cgf.13185,
journal = {Computer Graphics Forum}, title = {{
Visualizing a Sequence of a Thousand Graphs (or Even More)}},
author = {
Burch, Michael
and
Hlawatsch, Marcel
and
Weiskopf, Daniel
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13185}
}
                
@article{
10.1111:cgf.13186,
journal = {Computer Graphics Forum}, title = {{
Visual Exploration of Global Trade Networks with Time-Dependent and Weighted Hierarchical Edge Bundles on GPU}},
author = {
Hofmann, Johannes
and
Größler, Michael
and
Rubio-Sánchez, Manuel
and
Pichler, Peter-Paul
and
Lehmann, Dirk J.
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13186}
}
                
@article{
10.1111:cgf.13187,
journal = {Computer Graphics Forum}, title = {{
Graph Layouts by t-SNE}},
author = {
Kruiger, J. F.
and
Rauber, Paulo E.
and
Martins, Rafael Messias
and
Kerren, Andreas
and
Kobourov, Stephen
and
Telea, Alexandru C.
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13187}
}
                
@article{
10.1111:cgf.13188,
journal = {Computer Graphics Forum}, title = {{
Comparing Personal Image Collections with PICTuReVis}},
author = {
Corput, Paul van der
and
Wijk, Jarke J. van
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13188}
}
                
@article{
10.1111:cgf.13189,
journal = {Computer Graphics Forum}, title = {{
Dynamic Visual Abstraction of Soccer Movement}},
author = {
Sacha, Dominik
and
Al-Masoudi, Feeras
and
Stein, Manuel
and
Schreck, Tobias
and
Keim, Daniel A.
and
Andrienko, Gennady
and
Janetzko, Halldór
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13189}
}
                
@article{
10.1111:cgf.13190,
journal = {Computer Graphics Forum}, title = {{
Visualization of Delay Uncertainty and its Impact on Train Trip Planning: A Design Study}},
author = {
Wunderlich, Marcel
and
Ballweg, Kathrin
and
Fuchs, Georg
and
Landesberger, Tatiana von
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13190}
}
                
@article{
10.1111:cgf.13192,
journal = {Computer Graphics Forum}, title = {{
Measuring Symmetry in Drawings of Graphs}},
author = {
Welch, Eric
and
Kobourov, Stephen
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13192}
}
                
@article{
10.1111:cgf.13191,
journal = {Computer Graphics Forum}, title = {{
Comparative Visual Analysis of Structure-Performance Relations in Complex Bulk-Heterojunction Morphologies}},
author = {
Aboulhassan, Amal
and
Sicat, Ronell
and
Baum, Daniel
and
Wodo, Olga
and
Hadwiger, Markus
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13191}
}
                
@article{
10.1111:cgf.13193,
journal = {Computer Graphics Forum}, title = {{
Reverse-Engineering Visualizations: Recovering Visual Encodings from Chart Images}},
author = {
Poco, Jorge
and
Heer, Jeffrey
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13193}
}
                
@article{
10.1111:cgf.13194,
journal = {Computer Graphics Forum}, title = {{
Finding a Clear Path: Structuring Strategies for Visualization Sequences}},
author = {
Hullman, Jessica
and
Kosara, Robert
and
Lam, Heidi
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13194}
}
                
@article{
10.1111:cgf.13196,
journal = {Computer Graphics Forum}, title = {{
Adaptable Radial Axes Plots for Improved Multivariate Data Visualization}},
author = {
Rubio-Sánchez, Manuel
and
Sanchez, Alberto
and
Lehmann, Dirk J.
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13196}
}
                
@article{
10.1111:cgf.13195,
journal = {Computer Graphics Forum}, title = {{
Visual Narrative Flow: Exploring Factors Shaping Data Visualization Story Reading Experiences}},
author = {
McKenna, Sean
and
Riche, Nathalie Henry
and
Lee, Bongshin
and
Boy, Jeremy
and
Meyer, Miriah
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13195}
}
                
@article{
10.1111:cgf.13197,
journal = {Computer Graphics Forum}, title = {{
Linear Discriminative Star Coordinates for Exploring Class and Cluster Separation of High Dimensional Data}},
author = {
Wang, Yunhai
and
Li, Jingting
and
Nie, Feiping
and
Theisel, Holger
and
Gong, Minglun
and
Lehmann, Dirk J.
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13197}
}
                
@article{
10.1111:cgf.13199,
journal = {Computer Graphics Forum}, title = {{
Minimum-Displacement Overlap Removal for Geo-referenced Data Visualization}},
author = {
Garderen, Mereke van
and
Pampel, Barbara
and
Nocaj, Arlind
and
Brandes, Ulrik
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13199}
}
                
@article{
10.1111:cgf.13198,
journal = {Computer Graphics Forum}, title = {{
Understanding Indirect Causal Relationships in Node-Link Graphs}},
author = {
Bae, Juhee
and
Helldin, Tove
and
Riveiro, Maria
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13198}
}
                
@article{
10.1111:cgf.13200,
journal = {Computer Graphics Forum}, title = {{
Generating Tile Maps}},
author = {
McNeill, Graham
and
Hale, Scott A.
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13200}
}
                
@article{
10.1111:cgf.13201,
journal = {Computer Graphics Forum}, title = {{
Illustrative Visualization of Mesoscale Ocean Eddies}},
author = {
Liu, Li
and
Silver, Deborah
and
Bemis, Karen
and
Kang, Dujuan
and
Curchitser, Enrique
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13201}
}
                
@article{
10.1111:cgf.13202,
journal = {Computer Graphics Forum}, title = {{
Dynamic Scene Graph: Enabling Scaling, Positioning, and Navigation in the Universe}},
author = {
Axelsson, Emil
and
Costa, Jonathas
and
Silva, Cláudio
and
Emmart, Carter
and
Bock, Alexander
and
Ynnerman, Anders
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13202}
}
                
@article{
10.1111:cgf.13203,
journal = {Computer Graphics Forum}, title = {{
Visualizing Probabilistic Multi-Phase Fluid Simulation Data using a Sampling Approach}},
author = {
Hummel, Mathias
and
Jöckel, Lisa
and
Schäfer, Jan
and
Hlawitschka, Mark Werner
and
Garth, Christoph
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13203}
}
                
@article{
10.1111:cgf.13204,
journal = {Computer Graphics Forum}, title = {{
Uncertainty Footprint: Visualization of Nonuniform Behavior of Iterative Algorithms Applied to 4D Cell Tracking}},
author = {
Wan, Yong
and
Hansen, Charles
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13204}
}
                
@article{
10.1111:cgf.13205,
journal = {Computer Graphics Forum}, title = {{
Steering the Craft: UI Elements and Visualizations for Supporting Progressive Visual Analytics}},
author = {
Badam, Sriram Karthik
and
Elmqvist, Niklas
and
Fekete, Jean-Daniel
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13205}
}
                
@article{
10.1111:cgf.13206,
journal = {Computer Graphics Forum}, title = {{
GraSp: Combining Spatially-aware Mobile Devices and a Display Wall for Graph Visualization and Interaction}},
author = {
Kister, Ulrike
and
Klamka, Konstantin
and
Tominski, Christian
and
Dachselt, Raimund
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13206}
}
                
@article{
10.1111:cgf.13207,
journal = {Computer Graphics Forum}, title = {{
Internal and External Visual Cue Preferences for Visualizations in Presentations}},
author = {
Kong, Ha-Kyung
and
Liu, Zhicheng
and
Karahalios, Karrie
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13207}
}
                
@article{
10.1111:cgf.13208,
journal = {Computer Graphics Forum}, title = {{
CoreFlow: Extracting and Visualizing Branching Patterns from Event Sequences}},
author = {
Liu, Zhicheng
and
Kerr, Bernard
and
Dontcheva, Mira
and
Grover, Justin
and
Hoffman, Matthew
and
Wilson, Alan
}, year = {
2017},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13208}
}

Browse

Recent Submissions

Now showing 1 - 47 of 47
  • Item
    EuroVis 2017: Frontmatter
    (Eurographics Association, 2017) Heer, Jeffrey; Ropinski, Timo; van Wijk, Jarke;
  • Item
    Global Feature Tracking and Similarity Estimation in Time-Dependent Scalar Fields
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Saikia, Himangshu; Weinkauf, Tino; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    We present an algorithm for tracking regions in time-dependent scalar fields that uses global knowledge from all time steps for determining the tracks. The regions are defined using merge trees, thereby representing a hierarchical segmentation of the data in each time step. The similarity of regions of two consecutive time steps is measured using their volumetric overlap and a histogram difference. The main ingredient of our method is a directed acyclic graph that records all relevant similarity information as follows: the regions of all time steps are the nodes of the graph, the edges represent possible short feature tracks between consecutive time steps, and the edge weights are given by the similarity of the connected regions. We compute a feature track as the global solution of a shortest path problem in the graph. We use these results to steer the - to the best of our knowledge - first algorithm for spatio-temporal feature similarity estimation. Our algorithm works for 2D and 3D time-dependent scalar fields. We compare our results to previous work, showcase its robustness to noise, and exemplify its utility using several real-world data sets.
  • Item
    Nested Tracking Graphs
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Lukasczyk, Jonas; Weber, Gunther; Maciejewski, Ross; Garth, Christoph; Leitte, Heike; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    Tracking graphs are a well established tool in topological analysis to visualize the evolution of components and their properties over time, i.e., when components appear, disappear, merge, and split. However, tracking graphs are limited to a single level threshold and the graphs may vary substantially even under small changes to the threshold. To examine the evolution of features for varying levels, users have to compare multiple tracking graphs without a direct visual link between them. We propose a novel, interactive, nested graph visualization based on the fact that the tracked superlevel set components for different levels are related to each other through their nesting hierarchy. This approach allows us to set multiple tracking graphs in context to each other and enables users to effectively follow the evolution of components for different levels simultaneously. We demonstrate the effectiveness of our approach on datasets from finite pointset methods, computational fluid dynamics, and cosmology simulations.
  • Item
    Computing Contour Trees for 2D Piecewise Polynomial Functions
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Nucha, Girijanandan; Bonneau, Georges-Pierre; Hahmann, Stefanie; Natarajan, Vijay; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    Contour trees are extensively used in scalar field analysis. The contour tree is a data structure that tracks the evolution of level set topology in a scalar field. Scalar fields are typically available as samples at vertices of a mesh and are linearly interpolated within each cell of the mesh. A more suitable way of representing scalar fields, especially when a smoother function needs to be modeled, is via higher order interpolants. We propose an algorithm to compute the contour tree for such functions. The algorithm computes a local structure by connecting critical points using a numerically stable monotone path tracing procedure. Such structures are computed for each cell and are stitched together to obtain the contour tree of the function. The algorithm is scalable to higher degree interpolants whereas previous methods were restricted to quadratic or linear interpolants. The algorithm is intrinsically parallelizable and has potential applications to isosurface extraction.
  • Item
    Compactly Supported Biorthogonal Wavelet Bases on the Body Centered Cubic Lattice
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Horacsek, Joshua J.; Alim, Usman R.; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    In this work, we present a family of compact, biorthogonal wavelet filter banks that are applicable to the Body Centered Cubic (BCC) lattice. While the BCC lattice has been shown to have superior approximation properties for volumetric data when compared to the Cartesian Cubic (CC) lattice, there has been little work in the way of designing wavelet filter banks that respect the geometry of the BCC lattice. Since wavelets have applications in signal de-noising, compression, and sparse signal reconstruction, these filter banks are an important tool that addresses some of the scalability concerns presented by the BCC lattice. We use these filters in the context of volumetric data compression and reconstruction and qualitatively evaluate our results by rendering images of isosurfaces from compressed data.
  • Item
    An Empirical Study on the Reliability of Perceiving Correlation Indices using Scatterplots
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Sher, Varshita; Bemis, Karen G.; Liccardi, Ilaria; Chen, Min; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    Scatterplots have been in use for about two centuries, primarily for observing the relationship between two variables and commonly for supporting correlation analysis. In this paper, we report an empirical study that examines how humans' perception of correlation using scatterplots relates to the Pearson's product-moment correlation coefficient (PPMCC) - a commonly used statistical measure of correlation. In particular, we study human participants' estimation of correlation under different conditions, e.g., different PPMCC values, different densities of data points, different levels of symmetry of data enclosures, and different patterns of data distribution. As the participants were instructed to estimate the PPMCC of each stimulus scatterplot, the difference between the estimated and actual PPMCC is referred to as an offset. The results of the study show that varying PPMCC values, symmetry of data enclosure, or data distribution does have an impact on the average offsets, while only large variations in density cause an impact that is statistically significant. This study indicates that humans' perception of correlation using scatterplots does not correlate with computed PPMCC in a consistent manner. The magnitude of offsets may be affected not only by the difference between individuals, but also by geometric features of data enclosures. It suggests that visualizing scatterplots does not provide adequate support to the task of retrieving their corresponding PPMCC indicators, while the underlying model of humans' perception of correlation using scatterplots ought to feature other variables in addition to PPMCC. The paper also includes a theoretical discussion on the cost-benefit of using scatterplots.
  • Item
    Constructing and Evaluating Visualisation Task Classifications: Process and Considerations
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Kerracher, Natalie; Kennedy, Jessie; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    Categorising tasks is a common pursuit in the visualisation research community, with a wide variety of taxonomies, typologies, design spaces, and frameworks having been developed over the last three decades. While these classifications are universally purported to be useful in both the design and evaluation processes and in guiding future research, remarkably little attention has been paid to how these frameworks have-and can be-constructed and evaluated. In this paper we review the task classification literature and report on current practices in construction and evaluation. We consider the stages of task classification construction and identify the associated threats to validity arising at each stage and in response to the different methods employed. We provide guidance on suitable validation approaches in order to mitigate these threats. We also consider the appropriateness of evaluation strategies according to the different aspects of the classification which they evaluate. In so doing, we seek to provide guidance for developers of classifications in determining appropriate construction and evaluation strategies when developing a classification, and also for those selecting between competing classifications for use in the design and evaluation processes.
  • Item
    Empirically Measuring Soft Knowledge in Visualization
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Kijmongkolchai, Natchaya; Abdul-Rahman, Alfie; Chen, Min; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    In this paper, we present an empirical study designed to evaluate the hypothesis that humans' soft knowledge can enhance the cost-benefit ratio of a visualization process by reducing the potential distortion. In particular, we focused on the impact of three classes of soft knowledge: (i) knowledge about application contexts, (ii) knowledge about the patterns to be observed (i.e., in relation to visualization task), and (iii) knowledge about statistical measures. We mapped these classes into three control variables, and used real-world time series data to construct stimuli. The results of the study confirmed the positive contribution of each class of knowledge towards the reduction of the potential distortion, while the knowledge about the patterns prevents distortion more effectively than the other two classes.
  • Item
    Visual Comparison of Eye Movement Patterns
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Blascheck, Tanja; Schweizer, Markus; Beck, Fabian; Ertl, Thomas; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    In eye tracking research, finding eye movement patterns and similar strategies between participants' eye movements is important to understand task solving strategies and obstacles. In this application paper, we present a graph comparison method using radial graphs that show Areas of Interest (AOIs) and their transitions. An analyst investigates a single graph based on dwell times, directed transitions, and temporal AOI sequences. Two graphs can be compared directly and temporal changes may be analyzed. A list and matrix approach facilitate the analyst to contrast more than two graphs guided by visually encoded graph similarities. We evaluated our approach in case studies with three eye tracking and visualization experts. They identified temporal transition patterns of eye movements across participants, groups of participants, and outliers.
  • Item
    Glyph-Based Comparative Stress Tensor Visualization in Cerebral Aneurysms
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Meuschke, Monique; Voß, Samuel; Beuing, Oliver; Preim, Bernhard; Lawonn, Kai; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    We present the first visualization tool that enables a comparative depiction of structural stress tensor data for vessel walls of cerebral aneurysms. Such aneurysms bear the risk of rupture, whereas their treatment also carries considerable risks for the patient. Medical researchers emphasize the importance of analyzing the interaction of morphological and hemodynamic information for the patient-specific rupture risk evaluation and treatment analysis. Tensor data such as the stress inside the aneurysm walls characterizes the interplay between the morphology and blood flow and seems to be an important rupture-prone criterion. We use different glyph-based techniques to depict local stress tensors simultaneously and compare their applicability to cerebral aneurysms in a user study. We thus offer medical researchers an effective visual exploration tool to assess the aneurysm rupture risk.We developed a GPU-based implementation of our techniques with a flexible interactive data exploration mechanism. Our depictions are designed in collaboration with domain experts, and we provide details about the evaluation.
  • Item
    Visual Verification of Cancer Staging for Therapy Decision Support
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Cypko, Mario A.; Wojdziak, Jan; Stoehr, Matthaeus; Kirchner, Bettina; Preim, Bernhard; Dietz, Andreas; Lemke, Heinz U.; Oeltze-Jafra, Steffen; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    It is generally accepted practice that each cancer patient case should be discussed in a clinical expert meeting, the so-called tumor board. A central role in finding the best therapy options for patients with solid tumors plays the Tumor, lymph Node, and Metastasis staging (TNM staging). Correctness of TNM staging has a significant impact on the therapy choice and hence on the patient's post-therapeutic quality of life or even survival. If inconsistencies in the TNM staging occur, possible explanations and solutions must be found based on the complex patient records, which takes the costly time of (multiple) physicians. We propose a more efficient visual analysis component, which supports a physician in verifying the given TNM staging before forwarding it to the tumor board. Our component comprises a Bayesian network model of the TNM staging process. Using information from the patient records and Bayesian inference, the models computes a patient-specific TNM staging, which is then explored and compared to the given staging by means of a graph-based visualization. Our component is implemented in a research prototype that supports an understanding of the model computations, allows for a fast identification of important influencing factors, and facilitates a quick detection of differences between two TNM stagings. We evaluated our component with five physicians, each studying 20 cases of laryngeal cancer.
  • Item
    Overview + Detail Visualization for Ensembles of Diffusion Tensors
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Zhang, Changgong; Caan, Matthan W. A.; Höllt, Thomas; Eisemann, Elmar; Vilanova, Anna; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    A Diffusion Tensor Imaging (DTI) group study consists of a collection of volumetric diffusion tensor datasets (i.e., an ensemble) acquired from a group of subjects. The multivariate nature of the diffusion tensor imposes challenges on the analysis and the visualization. These challenges are commonly tackled by reducing the diffusion tensors to scalar-valued quantities that can be analyzed with common statistical tools. However, reducing tensors to scalars poses the risk of losing intrinsic information about the tensor. Visualization of tensor ensemble data without loss of information is still a largely unsolved problem. In this work, we propose an overview + detail visualization to facilitate the tensor ensemble exploration. We define an ensemble representative tensor and variations in terms of the three intrinsic tensor properties (i.e., scale, shape, and orientation) separately. The ensemble summary information is visually encoded into the newly designed aggregate tensor glyph which, in a spatial layout, functions as the overview. The aggregate tensor glyph guides the analyst to interesting areas that would need further detailed inspection. The detail views reveal the original information that is lost during aggregation. It helps the analyst to further understand the sources of variation and formulate hypotheses. To illustrate the applicability of our prototype, we compare with most relevant previous work through a user study and we present a case study on the analysis of a brain diffusion tensor dataset ensemble from healthy volunteers.
  • Item
    Sclow Plots: Visualizing Empty Space
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Giesen, Joachim; Kühne, Lars; Lucas, Philipp; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    Scatter plots are mostly used for correlation analysis, but are also a useful tool for understanding the distribution of highdimensional point cloud data. An important characteristic of such distributions are clusters, and scatter plots have been used successfully to identify clusters in data. Another characteristic of point cloud data that has received less attention so far are regions that contain no or only very few data points. We show that augmenting scatter plots by projections of flow lines along the gradient vector field of the distance function to the point cloud reveals such empty regions or voids. The augmented scatter plots, that we call sclow plots, enable a much better understanding of the geometry underlying the point cloud than traditional scatter plots, and by that support tasks like dimension inference, detecting outliers, or identifying data points at the interface between clusters. We demonstrate the feasibility of our approach on synthetic and real world data sets.
  • Item
    Visualizing the Uncertainty of Graph-based 2D Segmentation with Min-path Stability
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Summa, Brian; Tierny, Julien; Pascucci, Valerio; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    This paper presents a novel approach to visualize the uncertainty in graph-based segmentations of scalar data. Segmentation of 2D scalar data has wide application in a variety of scientific and medical domains. Typically, a segmentation is presented as a single unambiguous boundary although the solution is often uncertain due to noise or blur in the underlying data as well as imprecision in user input. Our approach provides insight into this uncertainty by computing the ''min-path stability'', a scalar measure analyzing the stability of the segmentation given a set of input constraints. Our approach is efficient, easy to compute, and can be generally applied to either graph cuts or live-wire (even partial) segmentations. In addition to its general applicability, our new approach to graph cuts uncertainty visualization improves on the time complexity of the current state-ofthe- art with an additional fast approximate solution. We also introduce a novel query enabled by our approach which provides users with alternate segmentations by efficiently extracting local minima of the segmentation optimization. Finally, we evaluate our approach and demonstrate its utility on data from scientific and medical applications.
  • Item
    Interactive Regression Lens for Exploring Scatter Plots
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Shao, Lin; Mahajan, Aishwarya; Schreck, Tobias; Lehmann, Dirk J.; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    Data analysis often involves finding models that can explain patterns in data, and reduce possibly large data sets to more compact model-based representations. In Statistics, many methods are available to compute model information. Among others, regression models are widely used to explain data. However, regression analysis typically searches for the best model based on the global distribution of data. On the other hand, a data set may be partitioned into subsets, each requiring individual models. While automatic data subsetting methods exist, these often require parameters or domain knowledge to work with. We propose a system for visual-interactive regression analysis for scatter plot data, supporting both global and local regression modeling. We introduce a novel regression lens concept, allowing a user to interactively select a portion of data, on which regression analysis is run in interactive time. The lens gives encompassing visual feedback on the quality of candidate models as it is interactively navigated across the input data. While our regression lens can be used for fully interactive modeling, we also provide user guidance suggesting appropriate models and data subsets, by means of regression quality scores. We show, by means of use cases, that our regression lens is an effective tool for user-driven regression modeling and supports model understanding.
  • Item
    Sliceplorer: 1D Slices for Multi-dimensional Continuous Functions
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Torsney-Weir, Thomas; Sedlmair, Michael; Möller, Torsten; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    Multi-dimensional continuous functions are commonly visualized with 2D slices or topological views. Here, we explore 1D slices as an alternative approach to show such functions. Our goal with 1D slices is to combine the benefits of topological views, that is, screen space efficiency, with those of slices, that is a close resemblance of the underlying function. We compare 1D slices to 2D slices and topological views, first, by looking at their performance with respect to common function analysis tasks. We also demonstrate 3 usage scenarios: the 2D sinc function, neural network regression, and optimization traces. Based on this evaluation, we characterize the advantages and drawbacks of each of these approaches, and show how interaction can be used to overcome some of the shortcomings.
  • Item
    Stardust: Accessible and Transparent GPU Support for Information Visualization Rendering
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Ren, Donghao; Lee, Bongshin; Höllerer, Tobias; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    Web-based visualization libraries are in wide use, but performance bottlenecks occur when rendering, and especially animating, a large number of graphical marks. While GPU-based rendering can drastically improve performance, that paradigm has a steep learning curve, usually requiring expertise in the computer graphics pipeline and shader programming. In addition, the recent growth of virtual and augmented reality poses a challenge for supporting multiple display environments beyond regular canvases, such as a Head Mounted Display (HMD) and Cave Automatic Virtual Environment (CAVE). In this paper, we introduce a new web-based visualization library called Stardust, which provides a familiar API while leveraging GPU's processing power. Stardust also enables developers to create both 2D and 3D visualizations for diverse display environments using a uniform API. To demonstrate Stardust's expressiveness and portability, we present five example visualizations and a coding playground for four display environments. We also evaluate its performance by comparing it against the standard HTML5 Canvas, D3, and Vega.
  • Item
    Interactive Ambiguity Resolution of Named Entities in Fictional Literature
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Stoffel, Florian; Jentner, Wolfgang; Behrisch, Michael; Fuchs, Johannes; Keim, Daniel A.; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    Named entity recognition (NER) denotes the task to detect entities and their corresponding classes, such as person or location, in unstructured text data. For most applications, state of the art NER software is producing reasonable results. However, as a consequence of the methodological limitations and the well-known pitfalls when analyzing natural language data, the NER results are likely to contain ambiguities. In this paper, we present an interactive NER ambiguity resolution technique, which enables users to create (post-processing) rules for named entity recognition data based on the content and entity context of the analyzed documents. We specifically address the problem that in use-cases where ambiguities are problematic, such as the attribution of fictional characters with traits, it is often unfeasible to train models on custom data to improve state of the art NER software. We derive an iterative process model for improving NER results, show an interactive NER ambiguity resolution prototype, illustrate our approach with contemporary literature, and discuss our work and future research.
  • Item
    Integrating Visual Analytics Support for Grounded Theory Practice in Qualitative Text Analysis
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Chandrasegaran, Senthil; Badam, Sriram Karthik; Kisselburgh, Lorraine; Ramani, Karthik; Elmqvist, Niklas; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    We present an argument for using visual analytics to aid Grounded Theory methodologies in qualitative data analysis. Grounded theory methods involve the inductive analysis of data to generate novel insights and theoretical constructs. Making sense of unstructured text data is uniquely suited for visual analytics. Using natural language processing techniques such as parts-ofspeech tagging, retrieving information content, and topic modeling, different parts of the data can be structured and semantically associated, and interactively explored, thereby providing conceptual depth to the guided discovery process. We review grounded theory methods and identify processes that can be enhanced through visual analytic techniques. Next, we develop an interface for qualitative text analysis, and evaluate our design with qualitative research practitioners who analyze texts with and without visual analytics support. The results of our study suggest how visual analytics can be incorporated into qualitative data analysis tools, and the analytic and interpretive benefits that can result.
  • Item
    NEREx: Named-Entity Relationship Exploration in Multi-Party Conversations
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) El-Assady, Mennatallah; Sevastjanova, Rita; Gipp, Bela; Keim, Daniel A.; Collins, Christopher; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    Abstract We present NEREx, an interactive visual analytics approach for the exploratory analysis of verbatim conversational transcripts. By revealing different perspectives on multi-party conversations, NEREx gives an entry point for the analysis through high-level overviews and provides mechanisms to form and verify hypotheses through linked detail-views. Using a tailored named-entity extraction, we abstract important entities into ten categories and extract their relations with a distance-restricted entity-relationship model. This model complies with the often ungrammatical structure of verbatim transcripts, relating two entities if they are present in the same sentence within a small distance window. Our tool enables the exploratory analysis of multi-party conversations using several linked views that reveal thematic and temporal structures in the text. In addition to distant-reading, we integrated close-reading views for a text-level investigation process. Beyond the exploratory and temporal analysis of conversations, NEREx helps users generate and validate hypotheses and perform comparative analyses of multiple conversations. We demonstrate the applicability of our approach on real-world data from the 2016 U.S. Presidential Debates through a qualitative study with three domain experts from political science.
  • Item
    Cycle Plot Revisited: Multivariate Outlier Detection Using a Distance-Based Abstraction
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Bögl, Markus; Filzmoser, Peter; Gschwandtner, Theresia; Lammarsch, Tim; Leite, Roger A.; Miksch, Silvia; Rind, Alexander; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    The cycle plot is an established and effective visualization technique for identifying and comprehending patterns in periodic time series, like trends and seasonal cycles. It also allows to visually identify and contextualize extreme values and outliers from a different perspective. Unfortunately, it is limited to univariate data. For multivariate time series, patterns that exist across several dimensions are much harder or impossible to explore. We propose a modified cycle plot using a distance-based abstraction (Mahalanobis distance) to reduce multiple dimensions to one overview dimension and retain a representation similar to the original. Utilizing this distance-based cycle plot in an interactive exploration environment, we enhance the Visual Analytics capacity of cycle plots for multivariate outlier detection. To enable interactive exploration and interpretation of outliers, we employ coordinated multiple views that juxtapose a distance-based cycle plot with Cleveland's original cycle plots of the underlying dimensions. With our approach it is possible to judge the outlyingness regarding the seasonal cycle in multivariate periodic time series.
  • Item
    Visual Analysis of Confocal Raman Spectroscopy Data using Cascaded Transfer Function Design
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Schikora, Christoph Markus; Plack, Markus; Bornemann, Rainer; Bolívar, Peter Haring; Kolb, Andreas; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    2D Confocal Raman Microscopy (CRM) data consist of high dimensional per-pixel spectral data of 1000 bands and allows for complex spectral and spatial-spectral analysis tasks, i.e., in material discrimination, material thickness, and spatial material distributions. Currently, simple integral methods are commonly applied as visual analysis solutions to CRM data which exhibit restricted discrimination power in various regards. In this paper we present a novel approach for the visual analysis of 2D multispectral CRM data using multi-variate visualization techniques. Due to the large amount of data and the demand of an explorative approach without a-priori restriction, our system allows for arbitrary interactive (de)selection of varaibles w/o limitation and an unrestricted online definition/construction of new, combined properties. Our approach integrates CRM specific quantitative measures and handles material-related features for mixed materials in a quantitative manner. Technically, we realize the online definition/construction of new, combined properties as semi-automatic, cascaded, 1D and 2D multidimensional transfer functions (MD-TFs). By interactively incorporating new (raw or derived) properties, the dimensionality of the MD-TF space grows during the exploration procedure and is virtually unlimited. The final visualization is achieved by an enhanced color mixing step which improves saturation and contrast.
  • Item
    Graffinity: Visualizing Connectivity in Large Graphs
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Kerzner, Ethan; Lex, Alexander; Sigulinsky, Crystal Lynn; Urness, Timothy; Jones, Bryan William; Marc, Robert E.; Meyer, Miriah; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    Multivariate graphs are prolific across many fields, including transportation and neuroscience. A key task in graph analysis is the exploration of connectivity, to, for example, analyze how signals flow through neurons, or to explore how well different cities are connected by flights. While standard node-link diagrams are helpful in judging connectivity, they do not scale to large networks. Adjacency matrices also do not scale to large networks and are only suitable to judge connectivity of adjacent nodes. A key approach to realize scalable graph visualization are queries: instead of displaying the whole network, only a relevant subset is shown. Query-based techniques for analyzing connectivity in graphs, however, can also easily suffer from cluttering if the query result is big enough. To remedy this, we introduce techniques that provide an overview of the connectivity and reveal details on demand.We have two main contributions: (1) two novel visualization techniques that work in concert for summarizing graph connectivity; and (2) Graffinity, an open-source implementation of these visualizations supplemented by detail views to enable a complete analysis workflow. Graffinity was designed in a close collaboration with neuroscientists and is optimized for connectomics data analysis, yet the technique is applicable across domains. We validate the connectivity overview and our open-source tool with illustrative examples using flight and connectomics data.
  • Item
    Visualizing a Sequence of a Thousand Graphs (or Even More)
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Burch, Michael; Hlawatsch, Marcel; Weiskopf, Daniel; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    The visualization of dynamic graphs demands visually encoding at least three major data dimensions: vertices, edges, and time steps. Many of the state-of-the-art techniques can show an overview of vertices and edges but lack a data-scalable visual representation of the time aspect. In this paper, we address the problem of displaying dynamic graphs with a thousand or more time steps. Our proposed interleaved parallel edge splatting technique uses a time-to-space mapping and shows the complete dynamic graph in a static visualization. It provides an overview of all data dimensions, allowing for visually detecting timevarying data patterns; hence, it serves as a starting point for further data exploration. By applying clustering and ordering techniques on the vertices, edge splatting on the links, and a dense time-to-space mapping, our approach becomes visually scalable in all three dynamic graph data dimensions. We illustrate the usefulness of our technique by applying it to call graphs and US domestic flight data with several hundred vertices, several thousand edges, and more than a thousand time steps.
  • Item
    Visual Exploration of Global Trade Networks with Time-Dependent and Weighted Hierarchical Edge Bundles on GPU
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Hofmann, Johannes; Größler, Michael; Rubio-Sánchez, Manuel; Pichler, Peter-Paul; Lehmann, Dirk J.; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    The UN Comtrade database is the world's largest repository of bilateral trade data. Their complexity poses a challenge to visualization systems, leading to issues such as scalability and visual clutter. Thus, we propose a radial layout-based visual exploration system to enable the user to smoothly explore the change over time and to explore different commodity classes at once by using a novel edge bundling concept. We evaluated our system with the aid of a group of domain experts.
  • Item
    Graph Layouts by t-SNE
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Kruiger, J. F.; Rauber, Paulo E.; Martins, Rafael Messias; Kerren, Andreas; Kobourov, Stephen; Telea, Alexandru C.; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    We propose a new graph layout method based on a modification of the t-distributed Stochastic Neighbor Embedding (t-SNE) dimensionality reduction technique. Although t-SNE is one of the best techniques for visualizing high-dimensional data as 2D scatterplots, t-SNE has not been used in the context of classical graph layout. We propose a new graph layout method, tsNET, based on representing a graph with a distance matrix, which together with a modified t-SNE cost function results in desirable layouts. We evaluate our method by a formal comparison with state-of-the-art methods, both visually and via established quality metrics on a comprehensive benchmark, containing real-world and synthetic graphs. As evidenced by the quality metrics and visual inspection, tsNET produces excellent layouts.
  • Item
    Comparing Personal Image Collections with PICTuReVis
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Corput, Paul van der; Wijk, Jarke J. van; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    Digital image collections contain a wealth of information, which for instance can be used to trace illegal activities and investigate criminal networks. We present a method that enables analysts to reveal relations among people, based on the patterns in their collections. Similar temporal and spatial patterns can be found using a parameterized algorithm, visualization is used to choose the right parameters and to inspect the patterns found. The visualization shows relations between image properties: the person it belongs to, the concepts in the image, its time stamp and location. We demonstrate the method with image collections of 10;000 people containing 460;000 images in total.
  • Item
    Dynamic Visual Abstraction of Soccer Movement
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Sacha, Dominik; Al-Masoudi, Feeras; Stein, Manuel; Schreck, Tobias; Keim, Daniel A.; Andrienko, Gennady; Janetzko, Halldór; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    Trajectory-based visualization of coordinated movement data within a bounded area, such as player and ball movement within a soccer pitch, can easily result in visual crossings, overplotting, and clutter. Trajectory abstraction can help to cope with these issues, but it is a challenging problem to select the right level of abstraction (LoA) for a given data set and analysis task. We present a novel dynamic approach that combines trajectory simplification and clustering techniques with the goal to support interpretation and understanding of movement patterns. Our technique provides smooth transitions between different abstraction types that can be computed dynamically and on-the-fly. This enables the analyst to effectively navigate and explore the space of possible abstractions in large trajectory data sets. Additionally, we provide a proof of concept for supporting the analyst in determining the LoA semi-automatically with a recommender system. Our approach is illustrated and evaluated by case studies, quantitative measures, and expert feedback. We further demonstrate that it allows analysts to solve a variety of analysis tasks in the domain of soccer.
  • Item
    Visualization of Delay Uncertainty and its Impact on Train Trip Planning: A Design Study
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Wunderlich, Marcel; Ballweg, Kathrin; Fuchs, Georg; Landesberger, Tatiana von; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    Uncertainty about possible train delays has an impact on train trips, as the exact arrival time is unknown during trip planning. Delays can lead to missing a connecting train at the transfer station, or to coming too late to an appointment at the destination. Facing this uncertainty, the traveler may wish to use an earlier train or a different connection arriving well before the appointment. Currently, train trip planning is based on scheduled times of connections between two stations. Information about approximate delays is only available shortly before train departure. Although several visualization approaches can show temporal uncertainty, we are not aware of any visual design specifically supporting trip planning, which can show delay uncertainty and its impact on the connections. We propose and evaluate a visual design which extends train trip planning with delay uncertainty. It shows the scheduled train connections together with their expected train delays as well as their impacts on both the arrival time, and the potential of missing a transfer. The visualization also includes information about alternative connections in case of these critical transfers. In this way the user is able to judge which train connection is suitable for a trip. We conducted a user study with 76 participants to evaluate our design. We compared it to two alternative presentations that are prominent in Germany. The study showed that our design performs comparably well for tasks concerning train schedules. The additional uncertainty display as well as the visualization of alternative connections was appreciated and well understood. The participants were able to estimate when they would likely arrive at their destination despite possible train delays while they were unable to estimate this with existing presentations. The users would prefer to use the new design for their trip planning.
  • Item
    Measuring Symmetry in Drawings of Graphs
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Welch, Eric; Kobourov, Stephen; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    Layout symmetry is an important and desired feature in graph drawing. While there is a substantial body of work in computer vision around the detection and measurement of symmetry in images, there has been little effort to define and validate meaningful measures of the symmetry of graph drawings. In this paper, we evaluate two algorithms that have been proposed for measuring graph drawing symmetry, comparing their judgments to those of human subjects, and investigating the use of stress as an alternative measure of symmetry. We discuss advantages and disadvantages of these measures, possible ways to improve them, and implications for the design of algorithms that optimize the symmetry in the layout.
  • Item
    Comparative Visual Analysis of Structure-Performance Relations in Complex Bulk-Heterojunction Morphologies
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Aboulhassan, Amal; Sicat, Ronell; Baum, Daniel; Wodo, Olga; Hadwiger, Markus; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    The structure of Bulk-Heterojunction (BHJ) materials, the main component of organic photovoltaic solar cells, is very complex, and the relationship between structure and performance is still largely an open question. Overall, there is a wide spectrum of fabrication configurations resulting in different BHJ morphologies and correspondingly different performances. Current stateof- the-art methods for assessing the performance of BHJ morphologies are either based on global quantification of morphological features or simply on visual inspection of the morphology based on experimental imaging. This makes finding optimal BHJ structures very challenging. Moreover, finding the optimal fabrication parameters to get an optimal structure is still an open question. In this paper, we propose a visual analysis framework to help answer these questions through comparative visualization and parameter space exploration for local morphology features. With our approach, we enable scientists to explore multivariate correlations between local features and performance indicators of BHJ morphologies. Our framework is built on shape-based clustering of local cubical regions of the morphology that we call patches. This enables correlating the features of clusters with intuition-based performance indicators computed from geometrical and topological features of charge paths.
  • Item
    Reverse-Engineering Visualizations: Recovering Visual Encodings from Chart Images
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Poco, Jorge; Heer, Jeffrey; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    We investigate how to automatically recover visual encodings from a chart image, primarily using inferred text elements. We contribute an end-to-end pipeline which takes a bitmap image as input and returns a visual encoding specification as output. We present a text analysis pipeline which detects text elements in a chart, classifies their role (e.g., chart title, x-axis label, y-axis title, etc.), and recovers the text content using optical character recognition. We also train a Convolutional Neural Network for mark type classification. Using the identified text elements and graphical mark type, we can then infer the encoding specification of an input chart image. We evaluate our techniques on three chart corpora: a set of automatically labeled charts generated using Vega, charts from the Quartz news website, and charts extracted from academic papers. We demonstrate accurate automatic inference of text elements, mark types, and chart specifications across a variety of input chart types.
  • Item
    Finding a Clear Path: Structuring Strategies for Visualization Sequences
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Hullman, Jessica; Kosara, Robert; Lam, Heidi; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    Little is known about how people structure sets of visualizations to support sequential viewing. We contribute findings from several studies examining visualization sequencing and reception. In our first study, people made decisions between various possible structures as they ordered a set of related visualizations (consisting of either bar charts or thematic maps) into what they considered the clearest sequence for showing the data.We find that most people structure visualization sequences hierarchically: they create high level groupings based on shared data properties like time period, measure, level of aggregation, and spatial region, then order the views within these groupings. We also observe a tendency for certain types of similarities between views, like a common spatial region or aggregation level, to be seen as more appropriate categories for organizing views in a sequence than others, like a common time period or measure. In a second study, we find that viewers' perceptions of the quality and intention of different sequences are largely consistent with the perceptions of the users who created them. The understanding of sequence preferences and perceptions that emerges from our studies has implications for the development of visualization authoring tools and sequence recommendations for guided analysis.
  • Item
    Adaptable Radial Axes Plots for Improved Multivariate Data Visualization
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Rubio-Sánchez, Manuel; Sanchez, Alberto; Lehmann, Dirk J.; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    Radial axes plots are multivariate visualization techniques that extend scatterplots in order to represent high-dimensional data as points on an observable display. Well-known methods include star coordinates or principal component biplots, which represent data attributes as vectors that de ne axes, and produce linear dimensionality reduction mappings. In this paper we propose a hybrid approach that bridges the gap between star coordinates and principal component biplots, which we denominate adaptable radial axes plots . It is based on solving convex optimization problems where users can: (a) update the axis vectors interactively, as in star coordinates, while producing mappings that enable to estimate attribute values optimally through labeled axes, similarly to principal component biplots; (b) use different norms in order to explore additional nonlinear mappings of the data; and (c) include weights and constraints in the optimization problems for sorting the data along one axis. The result is a exible technique that complements, extends, and enhances current radial methods for data analysis.
  • Item
    Visual Narrative Flow: Exploring Factors Shaping Data Visualization Story Reading Experiences
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) McKenna, Sean; Riche, Nathalie Henry; Lee, Bongshin; Boy, Jeremy; Meyer, Miriah; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    Many factors can shape the flow of visual data-driven stories, and thereby the way readers experience those stories. Through the analysis of 80 existing stories found on popular websites, we systematically investigate and identify seven characteristics of these stories, which we name ''flow-factors,'' and we illustrate how they feed into the broader concept of ''visual narrative flow.'' These flow-factors are navigation input, level of control, navigation progress, story layout, role of visualization, story progression, and navigation feedback. We also describe a series of studies we conducted, which shed initial light on how different visual narrative flows impact the reading experience. We report on two exploratory studies, in which we gathered reactions and preferences of readers for stepper- vs. scroller-driven flows. We then report on a crowdsourced study with 240 participants, in which we explore the effect of the combination of different flow-factors on readers' engagement. Our results indicate that visuals and navigation feedback (e.g., static vs. animated transitions) have an impact on readers' engagement, while level of control (e.g., discrete vs. continuous) may not.
  • Item
    Linear Discriminative Star Coordinates for Exploring Class and Cluster Separation of High Dimensional Data
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Wang, Yunhai; Li, Jingting; Nie, Feiping; Theisel, Holger; Gong, Minglun; Lehmann, Dirk J.; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    One main task for domain experts in analysing their nD data is to detect and interpret class/cluster separations and outliers. In fact, an important question is, which features/dimensions separate classes best or allow a cluster-based data classification. Common approaches rely on projections from nD to 2D, which comes with some challenges, such as: The space of projection contains an infinite number of items. How to find the right one? The projection approaches suffers from distortions and misleading effects. How to rely to the projected class/cluster separation? The projections involve the complete set of dimensions/ features. How to identify irrelevant dimensions? Thus, to address these challenges, we introduce a visual analytics concept for the feature selection based on linear discriminative star coordinates (DSC), which generate optimal cluster separating views in a linear sense for both labeled and unlabeled data. This way the user is able to explore how each dimension contributes to clustering. To support to explore relations between clusters and data dimensions, we provide a set of cluster-aware interactions allowing to smartly iterate through subspaces of both records and features in a guided manner. We demonstrate our features selection approach for optimal cluster/class separation analysis with a couple of experiments on real-life benchmark high-dimensional data sets.
  • Item
    Minimum-Displacement Overlap Removal for Geo-referenced Data Visualization
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Garderen, Mereke van; Pampel, Barbara; Nocaj, Arlind; Brandes, Ulrik; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    Given a set of rectangles embedded in the plane, we consider the problem of adjusting the layout to remove all overlap while preserving the orthogonal order of the rectangles. The objective is to minimize the displacement of the rectangles. We call this problem MINIMUM-DISPLACEMENT OVERLAP REMOVAL (MDOR). Our interest in this problem is motivated by the application of displaying metadata of archaeological sites. Because most existing overlap removal algorithms are not designed to minimize displacement while preserving orthogonal order, we present and compare several approaches which are tailored to our particular usecase. We introduce a new overlap removal heuristic which we call REARRANGE. Although conceptually simple, it is very effective in removing the overlap while keeping the displacement small. Furthermore, we propose an additional procedure to repair the orthogonal order after every iteration, with which we extend both our new heuristic and PRISM, a widely used overlap removal algorithm. We compare the performance of both approaches with and without this order repair method. The experimental results indicate that REARRANGE is very effective for heterogeneous input data where the overlap is concentrated in few dense regions.
  • Item
    Understanding Indirect Causal Relationships in Node-Link Graphs
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Bae, Juhee; Helldin, Tove; Riveiro, Maria; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    To find correlations and cause and effect relationships in multivariate data sets is central in many data analysis problems. A common way of representing causal relations among variables is to use node-link diagrams, where nodes depict variables and edges show relationships between them. When performing a causal analysis, analysts may be biased by the position of collected evidences, especially when they are at the top of a list. This is of crucial importance since finding a root cause or a derived effect, and searching for causal chains of inferences are essential analytic tasks when investigating causal relationships. In this paper, we examine whether sequential ordering influences understanding of indirect causal relationships and whether it improves readability of multi-attribute causal diagrams. Moreover, we see how people reason to identify a root cause or a derived effect. The results of our design study show that sequential ordering does not play a crucial role when analyzing causal relationships, but many connections from/to a variable and higher strength/certainty values may influence the process of finding a root cause and a derived effect.
  • Item
    Generating Tile Maps
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) McNeill, Graham; Hale, Scott A.; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    Tile maps are an important tool in thematic cartography with distinct qualities (and limitations) that distinguish them from better-known techniques such as choropleths, cartograms and symbol maps. Specifically, tile maps display geographic regions as a grid of identical tiles so large regions do not dominate the viewer's attention and small regions are easily seen. Furthermore, complex data such as time series can be shown on each tile in a consistent format, and the grid layout facilitates comparisons across tiles. Whilst a small number of handcrafted tile maps have become popular, the time-consuming process of creating new tile maps limits their wider use. To address this issue, we present an algorithm that generates a tile map of the specified type (e.g. square, hexagon, triangle) from raw shape data. Since the 'best' tile map depends on the specific geography visualized and the task to be performed, the algorithm generates and ranks multiple tile maps and allows the user to choose the most appropriate. The approach is demonstrated on a range of examples using a prototype browser-based application.
  • Item
    Illustrative Visualization of Mesoscale Ocean Eddies
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Liu, Li; Silver, Deborah; Bemis, Karen; Kang, Dujuan; Curchitser, Enrique; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    Feature-based time-varying volume visualization is combined with illustrative visualization to tell the story of how mesoscale ocean eddies form in the Gulf Stream and transport heat and nutrients across the ocean basin. The internal structure of these three-dimensional eddies and the kinematics with which they move are critical to a full understanding of ocean eddies. In this work, we apply a feature-based method to track instances of ocean eddies through the time steps of a high-resolution multidecadal regional ocean model and generate a series of eddy paths which reflect the life cycle of individual eddy instances. Based on the computed metadata, several important geometric and physical properties of eddy are computed. Illustrative visualization techniques, including visual effectiveness enhancement, focus+context, and smart visibility, are combined with the extracted volume features to explore eddy characteristics at different levels. An evaluation by domain experts indicates that combining our feature-based techniques with illustrative visualization techniques provides an insight into the role eddies play in ocean circulation. The domain experts expressed a preference for our methods over existing tools.
  • Item
    Dynamic Scene Graph: Enabling Scaling, Positioning, and Navigation in the Universe
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Axelsson, Emil; Costa, Jonathas; Silva, Cláudio; Emmart, Carter; Bock, Alexander; Ynnerman, Anders; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    In this work, we address the challenge of seamlessly visualizing astronomical data exhibiting huge scale differences in distance, size, and resolution. One of the difficulties is accurate, fast, and dynamic positioning and navigation to enable scaling over orders of magnitude, far beyond the precision of floating point arithmetic. To this end we propose a method that utilizes a dynamically assigned frame of reference to provide the highest possible numerical precision for all salient objects in a scene graph. This makes it possible to smoothly navigate and interactively render, for example, surface structures on Mars and the MilkyWay simultaneously. Our work is based on an analysis of tracking and quantification of the propagation of precision errors through the computer graphics pipeline using interval arithmetic. Furthermore, we identify sources of precision degradation, leading to incorrect object positions in screen-space and z-fighting. Our proposed method operates without near and far planes while maintaining high depth precision through the use of floating point depth buffers. By providing interoperability with order-independent transparency algorithms, direct volume rendering, and stereoscopy, our approach is well suited for scientific visualization. We provide the mathematical background, a thorough description of the method, and a reference implementation.
  • Item
    Visualizing Probabilistic Multi-Phase Fluid Simulation Data using a Sampling Approach
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Hummel, Mathias; Jöckel, Lisa; Schäfer, Jan; Hlawitschka, Mark Werner; Garth, Christoph; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    Eulerian Method of Moment (MoM) solvers are gaining popularity for multi-phase CFD simulation involving bubbles or droplets in process engineering. Because the actual positions of bubbles are uncertain, the spatial distribution of bubbles is described by scalar fields of moments, which can be interpreted as probability density functions. Visualizing these simulation results and comparing them to physical experiments is challenging, because neither the shape nor the distribution of bubbles described by the moments lend themselves to visual interpretation. In this work, we describe a visualization approach that provides explicit instances of the bubble distribution and produces bubble geometry based on local flow properties. To facilitate animation, the instancing of the bubble distribution provides coherence over time by advancing bubbles between time steps and updating the distribution. Our approach provides an intuitive visualization and enables direct visual comparison of simulation results to physical experiments.
  • Item
    Uncertainty Footprint: Visualization of Nonuniform Behavior of Iterative Algorithms Applied to 4D Cell Tracking
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Wan, Yong; Hansen, Charles; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    Research on microscopy data from developing biological samples usually requires tracking individual cells over time. When cells are three-dimensionally and densely packed in a time-dependent scan of volumes, tracking results can become unreliable and uncertain. Not only are cell segmentation results often inaccurate to start with, but it also lacks a simple method to evaluate the tracking outcome. Previous cell tracking methods have been validated against benchmark data from real scans or artificial data, whose ground truth results are established by manual work or simulation. However, the wide variety of real-world data makes an exhaustive validation impossible. Established cell tracking tools often fail on new data, whose issues are also difficult to diagnose with only manual examinations. Therefore, data-independent tracking evaluation methods are desired for an explosion of microscopy data with increasing scale and resolution. In this paper, we propose the uncertainty footprint, an uncertainty quantification and visualization technique that examines nonuniformity at local convergence for an iterative evaluation process on a spatial domain supported by partially overlapping bases. We demonstrate that the patterns revealed by the uncertainty footprint indicate data processing quality in two algorithms from a typical cell tracking workflow - cell identification and association. A detailed analysis of the patterns further allows us to diagnose issues and design methods for improvements. A 4D cell tracking workflow equipped with the uncertainty footprint is capable of self diagnosis and correction for a higher accuracy than previous methods whose evaluation is limited by manual examinations.
  • Item
    Steering the Craft: UI Elements and Visualizations for Supporting Progressive Visual Analytics
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Badam, Sriram Karthik; Elmqvist, Niklas; Fekete, Jean-Daniel; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    Progressive visual analytics (PVA) has emerged in recent years to manage the latency of data analysis systems. When analysis is performed progressively, rough estimates of the results are generated quickly and are then improved over time. Analysts can therefore monitor the progression of the results, steer the analysis algorithms, and make early decisions if the estimates provide a convincing picture. In this article, we describe interface design guidelines for helping users understand progressively updating results and make early decisions based on progressive estimates. To illustrate our ideas, we present a prototype PVA tool called INSIGHTSFEED for exploring Twitter data at scale. As validation, we investigate the tradeoffs of our tool when exploring a Twitter dataset in a user study. We report the usage patterns in making early decisions using the user interface, guiding computational methods, and exploring different subsets of the dataset, compared to sequential analysis without progression.
  • Item
    GraSp: Combining Spatially-aware Mobile Devices and a Display Wall for Graph Visualization and Interaction
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Kister, Ulrike; Klamka, Konstantin; Tominski, Christian; Dachselt, Raimund; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    Going beyond established desktop interfaces, researchers have begun re-thinking visualization approaches to make use of alternative display environments and more natural interaction modalities. In this paper, we investigate how spatially-aware mobile displays and a large display wall can be coupled to support graph visualization and interaction. For that purpose, we distribute typical visualization views of classic node-link and matrix representations between displays. The focus of our work lies in novel interaction techniques that enable users to work with personal mobile devices in combination with the wall. We devised and implemented a comprehensive interaction repertoire that supports basic and advanced graph exploration and manipulation tasks, including selection, details-on-demand, focus transitions, interactive lenses, and data editing. A qualitative study has been conducted to identify strengths and weaknesses of our techniques. Feedback showed that combining mobile devices and a wall-sized display is useful for diverse graph-related tasks. We also gained valuable insights regarding the distribution of visualization views and interactive tools among the combined displays.
  • Item
    Internal and External Visual Cue Preferences for Visualizations in Presentations
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Kong, Ha-Kyung; Liu, Zhicheng; Karahalios, Karrie; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    Presenters, such as analysts briefing to an executive committee, often use visualizations to convey information. In these cases, providing clear visual guidance is important to communicate key concepts without confusion. This paper explores visual cues that guide attention to a particular area of a visualization. We developed a visual cue taxonomy distinguishing internal from external cues, designed a web tool based on the taxonomy, and conducted a user study with 24 participants to understand user preferences in choosing visual cues. Participants perceived internal cues (e.g., transparency, brightness, and magnification) as the most useful visual cues and often combined them with other internal or external cues to emphasize areas of focus for their audience. Interviews also revealed that the choice of visual cues depends on not only the chart type, but also the presentation setting, the audience, and the function cues are serving. Considering the complexity of choosing visual cues, we provide design implications for improving the organization, consistency, and integration of visual cues within existing workflows.
  • Item
    CoreFlow: Extracting and Visualizing Branching Patterns from Event Sequences
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Liu, Zhicheng; Kerr, Bernard; Dontcheva, Mira; Grover, Justin; Hoffman, Matthew; Wilson, Alan; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    Event sequence datasets with high event cardinality and long sequences are difficult to visualize and analyze. In particular, it is hard to generate a high level visual summary of paths and volume of flow. Existing approaches of mining and visualizing frequent sequential patterns look promising, but have limitations in terms of scalability, interpretability and utility. We propose CoreFlow, a technique that automatically extracts and visualizes branching patterns in event sequences. CoreFlow constructs a tree by recursively applying a three-step procedure: rank events, divide sequences into groups, and trim sequences by the chosen event. The resulting tree contains key events as nodes, and links represent aggregated flows between key events. Based on CoreFlow, we have developed an interactive system for event sequence analysis. Our approach can compute branching patterns for millions of events in a few seconds, with improved interpretability of extracted patterns compared to previous work. We also present case studies of using the system in three different domains and discuss success and failure cases of applying CoreFlow to real-world analytic problems. These case studies call forth future research on metrics and models to evaluate the quality of visual summaries of event sequences.