37-Issue 3

Permanent URI for this collection

EuroVis 2018 - 20th EG/VGTC Conference on Visualization
Brno, Czech Republic 4-8 June 2018
Multiple Fields and Time
Hierarchical Correlation Clustering in Multiple 2D Scalar Fields
Tom Liebmann, Gunther H. Weber, and Gerik Scheuermann
Representative Consensus from Limited-Size Ensembles
Mahsa Mirzargar and Ross T. Whitaker
Time Lattice: A Data Structure for the Interactive Visual Analysis of Large Time Series
Fabio Miranda, Marcos Lage, Harish Doraiswamy, Charlie Mydlarz, Justin Salamon, Yitzchak Lockerman, Juliana Freire, and Claudio T. Silva
Key Time Steps Selection for Large-Scale Time-Varying Volume Datasets Using an Information-Theoretic Storyboard
Bo Zhou and Yi-Jen Chiang
Comparative and Collaborative
ChangeCatcher: Increasing Inter-author Awareness for Visualization Development
Mona Hosseinkhani Loorak, Melanie Tory, and Sheelagh Carpendale
Towards Easy Comparison of Local Businesses Using Online Reviews
Yong Wang, Hammad Haleem, Conglei Shi, Yanhong Wu, Xun Zhao, Siwei Fu, and Huamin Qu
Chart Constellations: Effective Chart Summarization for Collaborative and Multi-User Analyses
Shenyu Xu, Chris Bryan, Jianping Kelvin Li, Jian Zhao, and Kwan-Liu Ma
Visualizing Expanded Query Results
Michael Mazurek and Manuela Waldner
High-dimensional Data
Interactive Visual Exploration of Local Patterns in Large Scatterplot Spaces
Mohammad Chegini, Lin Shao, Robert Gregor, Dirk Joachim Lehmann, Keith Andrews, and Tobias Schreck
Fast and Accurate CNN-based Brushing in Scatterplots
Chaoran Fan and Helwig Hauser
Towards User-Centered Active Learning Algorithms
Jürgen Bernard, Matthias Zeppelzauer, Markus Lehmann, Martin Müller, and Michael Sedlmair
Visualization Design
Exploring the Visualization Design Space with Repertory Grids
Kuno Kurzhals and Daniel Weiskopf
Design Factors for Summary Visualization in Visual Analytics
Alper Sarikaya, Michael Gleicher, and Danielle Albers Szafir
Assessing Effects of Task and Data Distribution on the Effectiveness of Visual Encodings
Younghoon Kim and Jeffrey Heer
The Perception of Graph Properties in Graph Layouts
Utkarsh Soni, Yafeng Lu, Brett Hansen, Helen C. Purchase, Stephen Kobourov, and Ross Maciejewski
Medical Visualization
Explorative Blood Flow Visualization using Dynamic Line Filtering based on Surface Features
Benjamin Behrendt, Philipp Berg, Oliver Beuing, Bernhard Preim, and Sylvia Saalfeld
Visual and Quantitative Analysis of Great Arteries' Blood Flow Jets in Cardiac 4D PC-MRI Data
Benjamin Köhler, Matthias Grothoff, Matthias Gutberlet, and Bernhard Preim
Bladder Runner: Visual Analytics for the Exploration of RT-Induced Bladder Toxicity in a Cohort Study
Renata Georgia Raidou, Oscar Casares-Magaz, Aleksandr Amirkhanov, Vitali Moiseenko, Ludvig P. Muren, John P. Einck, Anna Vilanova, and Eduard Gröller
Structure and Shape
ConcaveCubes: Supporting Cluster-based Geographical Visualization in Large Data Scale
Mingzhao Li, Farhana Choudhury, Zhifeng Bao, Hanan Samet, and Timos Sellis
Hypersliceplorer: Interactive Visualization of Shapes in Multiple Dimensions
Thomas Torsney-Weir, Torsten Möller, Michael Sedlmair, and R. Mike Kirby
Exploring High-Dimensional Structure via Axis-Aligned Decomposition of Linear Projections
Jayaraman J. Thiagarajan, Shusen Liu, Karthikeyan Natesan Ramamurthy, and Peer-Timo Bremer
Embeddings
Interactive Analysis of Word Vector Embeddings
Florian Heimerl and Michael Gleicher
PixelSNE: Pixel-Aligned Stochastic Neighbor Embedding for Efficient 2D Visualization with Screen-Resolution Precision
Minjeong Kim, Minsuk Choi, Sunwoong Lee, Jian Tang, Haesun Park, and Jaegul Choo
Visualizing Multidimensional Data with Order Statistics
Mukund Raj and Ross T. Whitaker
Vector and Tensor Fields
Visualizing the Phase Space of Heterogeneous Inertial Particles in 2D Flows
Irene Baeza Rojo, Markus Gross, and Tobias Günther
Visualization of 4D Vector Field Topology
Lutz Hofmann, Bastian Rieck, and Filip Sadlo
An Approximate Parallel Vectors Operator for Multiple Vector Fields
Tim Gerrits, Christian Rössl, and Holger Theisel
Core Lines in 3D Second-Order Tensor Fields
Timo Oster, Christian Rössl, and Holger Theisel
Visual Analytics
Track Xplorer: A System for Visual Analysis of Sensor-based Motor Activity Predictions
Marco Cavallo and Çağatay Demiralp
ThreadReconstructor: Modeling Reply-Chains to Untangle Conversational Text through Visual Analytics
Mennatallah El-Assady, Rita Sevastjanova, Daniel Keim, and Christopher Collins
Biological Visualization
A General Illumination Model for Molecular Visualization
Pedro Hermosilla Casajus, Pere-Pau Vázquez, Àlvar Vinacua, and Timo Ropinski
Analyzing Residue Surface Proximity to Interpret Molecular Dynamics
Nils Lichtenberg, Raphael Menges, Vladimir Ageev, Ajay Abisheck Paul George, Pascal Heimer, Diana Imhof, and Kai Lawonn
Visual Analysis of Protein-ligand Interactions
Pere-Pau Vázquez, Pedro Hermosilla Casajus, Victor Guallar, Jorge Estrada, and Àlvar Vinacua
DimSUM: Dimension and Scale Unifying Map for Visual Abstraction of DNA Origami Structures
Haichao Miao, Elisa De Llano, Tobias Isenberg, Eduard Gröller, Ivan Barišic, and Ivan Viola
VR and Workflows
VirtualDesk: A Comfortable and Efficient Immersive Information Visualization Approach
Jorge A. Wagner Filho, Carla M.D.S. Freitas, and Luciana Nedel
Maps and Globes in Virtual Reality
Yalong Yang, Bernhard Jenny, Tim Dwyer, Kim Marriott, Haohui Chen, and Maxime Cordeil
Landscaper: A Modeling System for 3D Printing Scale Models of Landscapes
Kamyar Allahverdi, Hessam Djavaherpour, Ali Mahdavi-Amiri, and Faramarz Samavati
CFGExplorer: Designing a Visual Control Flow Analytics System around Basic Program Analysis Operations
Sabin Devkota and Katherine E. Isaacs
Applications
Illustrative Multivariate Visualization for Geological Modelling
Allan Rocha, Roberta Cabral Ramos Mota, Hamidreza Hamdi, Usman R. Alim, and Mario Costa Sousa
Hunting High and Low: Visualising Shifting Correlations in Financial Markets
Peter M. Simon and Cagatay Turkay
Baseball Timeline: Summarizing Baseball Plays Into a Static Visualization
Jorge H. Piazentin Ono, Carlos Dietrich, and Claudio T. Silva
Scalar Fields
Cosine-Weighted B-Spline Interpolation on the Face-Centered Cubic Lattice
Gergely Ferenc Rácz and Balázs Csébfalvi
Spatio-Temporal Contours from Deep Volume Raycasting
Steffen Frey
Rendering and Extracting Extremal Features in 3D Fields
Gordon L. Kindlmann, Charisee Chiw, Tri Huynh, Attila Gyulassy, John Reppy, and Peer-Timo Bremer
Trees and Graphs
SetCoLa: High-Level Constraints for Graph Layout
Jane Hoffswell, Alan Borning, and Jeffrey Heer
Multiscale Visualization and Exploration of Large Bipartite Graphs
Nicola Pezzotti, Jean-Daniel Fekete, Thomas Höllt, Boudewijn P. F. Lelieveldt, Elmar Eisemann, and Anna Vilanova
Interactive Investigation of Traffic Congestion on Fat-Tree Networks Using TREESCOPE
Harsh Bhatia, Nikhil Jain, Abhinav Bhatele, Yarden Livnat, Jens Domke, Valerio Pascucci, and Peer-Timo Bremer

BibTeX (37-Issue 3)
                
@article{
10.1111:cgf.13396,
journal = {Computer Graphics Forum}, title = {{
Hierarchical Correlation Clustering in Multiple 2D Scalar Fields}},
author = {
Liebmann, Tom
and
Weber, Gunther H.
and
Scheuermann, Gerik
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13396}
}
                
@article{
10.1111:cgf.13397,
journal = {Computer Graphics Forum}, title = {{
Representative Consensus from Limited-Size Ensembles}},
author = {
Mirzargar, Mahsa
and
Whitaker, Ross T.
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13397}
}
                
@article{
10.1111:cgf.13398,
journal = {Computer Graphics Forum}, title = {{
Time Lattice: A Data Structure for the Interactive Visual Analysis of Large Time Series}},
author = {
Miranda, Fabio
and
Lage, Marcos
and
Doraiswamy, Harish
and
Mydlarz, Charlie
and
Salamon, Justin
and
Lockerman, Yitzchak
and
Freire, Juliana
and
Silva, Claudio T.
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13398}
}
                
@article{
10.1111:cgf.13399,
journal = {Computer Graphics Forum}, title = {{
Key Time Steps Selection for Large-Scale Time-Varying Volume Datasets Using an Information-Theoretic Storyboard}},
author = {
Zhou, Bo
and
Chiang, Yi-Jen
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13399}
}
                
@article{
10.1111:cgf.13400,
journal = {Computer Graphics Forum}, title = {{
ChangeCatcher: Increasing Inter-author Awareness for Visualization Development}},
author = {
Loorak, Mona Hosseinkhani
and
Tory, Melanie
and
Carpendale, Sheelagh
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13400}
}
                
@article{
10.1111:cgf.13401,
journal = {Computer Graphics Forum}, title = {{
Towards Easy Comparison of Local Businesses Using Online Reviews}},
author = {
Wang, Yong
and
Haleem, Hammad
and
Shi, Conglei
and
Wu, Yanhong
and
Zhao, Xun
and
Fu, Siwei
and
Qu, Huamin
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13401}
}
                
@article{
10.1111:cgf.13402,
journal = {Computer Graphics Forum}, title = {{
Chart Constellations: Effective Chart Summarization for Collaborative and Multi-User Analyses}},
author = {
Xu, Shenyu
and
Bryan, Chris
and
Li, Jianping Kelvin
and
Zhao, Jian
and
Ma, Kwan-Liu
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13402}
}
                
@article{
10.1111:cgf.13403,
journal = {Computer Graphics Forum}, title = {{
Visualizing Expanded Query Results}},
author = {
Mazurek, Michael
and
Waldner, Manuela
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13403}
}
                
@article{
10.1111:cgf.13404,
journal = {Computer Graphics Forum}, title = {{
Interactive Visual Exploration of Local Patterns in Large Scatterplot Spaces}},
author = {
Chegini, Mohammad
and
Shao, Lin
and
Gregor, Robert
and
Lehmann, Dirk Joachim
and
Andrews, Keith
and
Schreck, Tobias
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13404}
}
                
@article{
10.1111:cgf.13405,
journal = {Computer Graphics Forum}, title = {{
Fast and Accurate CNN-based Brushing in Scatterplots}},
author = {
Fan, Chaoran
and
Hauser, Helwig
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13405}
}
                
@article{
10.1111:cgf.13406,
journal = {Computer Graphics Forum}, title = {{
Towards User-Centered Active Learning Algorithms}},
author = {
Bernard, Jürgen
and
Zeppelzauer, Matthias
and
Lehmann, Markus
and
Müller, Martin
and
Sedlmair, Michael
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13406}
}
                
@article{
10.1111:cgf.13407,
journal = {Computer Graphics Forum}, title = {{
Exploring the Visualization Design Space with Repertory Grids}},
author = {
Kurzhals, Kuno
and
Weiskopf, Daniel
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13407}
}
                
@article{
10.1111:cgf.13408,
journal = {Computer Graphics Forum}, title = {{
Design Factors for Summary Visualization in Visual Analytics}},
author = {
Sarikaya, Alper
and
Gleicher, Michael
and
Szafir, Danielle Albers
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13408}
}
                
@article{
10.1111:cgf.13409,
journal = {Computer Graphics Forum}, title = {{
Assessing Effects of Task and Data Distribution on the Effectiveness of Visual Encodings}},
author = {
Kim, Younghoon
and
Heer, Jeffrey
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13409}
}
                
@article{
10.1111:cgf.13410,
journal = {Computer Graphics Forum}, title = {{
The Perception of Graph Properties in Graph Layouts}},
author = {
Soni, Utkarsh
and
Lu, Yafeng
and
Hansen, Brett
and
Purchase, Helen C.
and
Kobourov, Stephen
and
Maciejewski, Ross
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13410}
}
                
@article{
10.1111:cgf.13411,
journal = {Computer Graphics Forum}, title = {{
Explorative Blood Flow Visualization using Dynamic Line Filtering based on Surface Features}},
author = {
Behrendt, Benjamin
and
Berg, Philipp
and
Beuing, Oliver
and
Preim, Bernhard
and
Saalfeld, Sylvia
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13411}
}
                
@article{
10.1111:cgf.13412,
journal = {Computer Graphics Forum}, title = {{
Visual and Quantitative Analysis of Great Arteries' Blood Flow Jets in Cardiac 4D PC-MRI Data}},
author = {
Köhler, Benjamin
and
Grothoff, Matthias
and
Gutberlet, Matthias
and
Preim, Bernhard
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13412}
}
                
@article{
10.1111:cgf.13413,
journal = {Computer Graphics Forum}, title = {{
Bladder Runner: Visual Analytics for the Exploration of RT-Induced Bladder Toxicity in a Cohort Study}},
author = {
Raidou, Renata Georgia
and
Casares-Magaz, Oscar
and
Amirkhanov, Aleksandr
and
Moiseenko, Vitali
and
Muren, Ludvig P.
and
Einck, John P.
and
Vilanova, Anna
and
Gröller, Eduard
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13413}
}
                
@article{
10.1111:cgf.13414,
journal = {Computer Graphics Forum}, title = {{
ConcaveCubes: Supporting Cluster-based Geographical Visualization in Large Data Scale}},
author = {
Li, Mingzhao
and
Choudhury, Farhana
and
Bao, Zhifeng
and
Samet, Hanan
and
Sellis, Timos
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13414}
}
                
@article{
10.1111:cgf.13415,
journal = {Computer Graphics Forum}, title = {{
Hypersliceplorer: Interactive Visualization of Shapes in Multiple Dimensions}},
author = {
Torsney-Weir, Thomas
and
Möller, Torsten
and
Sedlmair, Michael
and
Kirby, R. Mike
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13415}
}
                
@article{
10.1111:cgf.13416,
journal = {Computer Graphics Forum}, title = {{
Exploring High-Dimensional Structure via Axis-Aligned Decomposition of Linear Projections}},
author = {
Thiagarajan, Jayaraman J.
and
Liu, Shusen
and
Ramamurthy, Karthikeyan Natesan
and
Bremer, Peer-Timo
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13416}
}
                
@article{
10.1111:cgf.13417,
journal = {Computer Graphics Forum}, title = {{
Interactive Analysis of Word Vector Embeddings}},
author = {
Heimerl, Florian
and
Gleicher, Michael
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13417}
}
                
@article{
10.1111:cgf.13418,
journal = {Computer Graphics Forum}, title = {{
PixelSNE: Pixel-Aligned Stochastic Neighbor Embedding for Efficient 2D Visualization with Screen-Resolution Precision}},
author = {
Kim, Minjeong
and
Choi, Minsuk
and
Lee, Sunwoong
and
Tang, Jian
and
Park, Haesun
and
Choo, Jaegul
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13418}
}
                
@article{
10.1111:cgf.13419,
journal = {Computer Graphics Forum}, title = {{
Visualizing Multidimensional Data with Order Statistics}},
author = {
Raj, Mukund
and
Whitaker, Ross T.
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13419}
}
                
@article{
10.1111:cgf.13420,
journal = {Computer Graphics Forum}, title = {{
Visualizing the Phase Space of Heterogeneous Inertial Particles in 2D Flows}},
author = {
Rojo, Irene Baeza
and
Gross, Markus
and
Günther, Tobias
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13420}
}
                
@article{
10.1111:cgf.13421,
journal = {Computer Graphics Forum}, title = {{
Visualization of 4D Vector Field Topology}},
author = {
Hofmann, Lutz
and
Rieck, Bastian
and
Sadlo, Filip
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13421}
}
                
@article{
10.1111:cgf.13422,
journal = {Computer Graphics Forum}, title = {{
An Approximate Parallel Vectors Operator for Multiple Vector Fields}},
author = {
Gerrits, Tim
and
Rössl, Christian
and
Theisel, Holger
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13422}
}
                
@article{
10.1111:cgf.13423,
journal = {Computer Graphics Forum}, title = {{
Core Lines in 3D Second-Order Tensor Fields}},
author = {
Oster, Timo
and
Rössl, Christian
and
Theisel, Holger
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13423}
}
                
@article{
10.1111:cgf.13424,
journal = {Computer Graphics Forum}, title = {{
Track Xplorer: A System for Visual Analysis of Sensor-based Motor Activity Predictions}},
author = {
Cavallo, Marco
and
Demiralp, Çağatay
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13424}
}
                
@article{
10.1111:cgf.13425,
journal = {Computer Graphics Forum}, title = {{
ThreadReconstructor: Modeling Reply-Chains to Untangle Conversational Text through Visual Analytics}},
author = {
El-Assady, Mennatallah
and
Sevastjanova, Rita
and
Keim, Daniel
and
Collins, Christopher
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13425}
}
                
@article{
10.1111:cgf.13426,
journal = {Computer Graphics Forum}, title = {{
A General Illumination Model for Molecular Visualization}},
author = {
Casajus, Pedro Hermosilla
and
Vázquez, Pere-Pau
and
Vinacua, Àlvar
and
Ropinski, Timo
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13426}
}
                
@article{
10.1111:cgf.13427,
journal = {Computer Graphics Forum}, title = {{
Analyzing Residue Surface Proximity to Interpret Molecular Dynamics}},
author = {
Lichtenberg, Nils
and
Menges, Raphael
and
Ageev, Vladimir
and
George, Ajay Abisheck Paul
and
Heimer, Pascal
and
Imhof, Diana
and
Lawonn, Kai
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13427}
}
                
@article{
10.1111:cgf.13428,
journal = {Computer Graphics Forum}, title = {{
Visual Analysis of Protein-ligand Interactions}},
author = {
Vázquez, Pere-Pau
and
Casajus, Pedro Hermosilla
and
Guallar, Victor
and
Estrada, Jorge
and
Vinacua, Àlvar
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13428}
}
                
@article{
10.1111:cgf.13429,
journal = {Computer Graphics Forum}, title = {{
DimSUM: Dimension and Scale Unifying Map for Visual Abstraction of DNA Origami Structures}},
author = {
Miao, Haichao
and
Llano, Elisa De
and
Isenberg, Tobias
and
Gröller, Eduard
and
Barišic, Ivan
and
Viola, Ivan
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13429}
}
                
@article{
10.1111:cgf.13430,
journal = {Computer Graphics Forum}, title = {{
VirtualDesk: A Comfortable and Efficient Immersive Information Visualization Approach}},
author = {
Filho, Jorge A. Wagner
and
Freitas, Carla M.D.S.
and
Nedel, Luciana
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13430}
}
                
@article{
10.1111:cgf.13431,
journal = {Computer Graphics Forum}, title = {{
Maps and Globes in Virtual Reality}},
author = {
Yang, Yalong
and
Jenny, Bernhard
and
Dwyer, Tim
and
Marriott, Kim
and
Chen, Haohui
and
Cordeil, Maxime
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13431}
}
                
@article{
10.1111:cgf.13432,
journal = {Computer Graphics Forum}, title = {{
Landscaper: A Modeling System for 3D Printing Scale Models of Landscapes}},
author = {
Allahverdi, Kamyar
and
Djavaherpour, Hessam
and
Mahdavi-Amiri, Ali
and
Samavati, Faramarz
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13432}
}
                
@article{
10.1111:cgf.13433,
journal = {Computer Graphics Forum}, title = {{
CFGExplorer: Designing a Visual Control Flow Analytics System around Basic Program Analysis Operations}},
author = {
Devkota, Sabin
and
Isaacs, Katherine E.
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13433}
}
                
@article{
10.1111:cgf.13434,
journal = {Computer Graphics Forum}, title = {{
Illustrative Multivariate Visualization for Geological Modelling}},
author = {
Rocha, Allan
and
Mota, Roberta Cabral Ramos
and
Hamdi, Hamidreza
and
Alim, Usman R.
and
Sousa, Mario Costa
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13434}
}
                
@article{
10.1111:cgf.13435,
journal = {Computer Graphics Forum}, title = {{
Hunting High and Low: Visualising Shifting Correlations in Financial Markets}},
author = {
Simon, Peter M.
and
Turkay, Cagatay
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13435}
}
                
@article{
10.1111:cgf.13436,
journal = {Computer Graphics Forum}, title = {{
Baseball Timeline: Summarizing Baseball Plays Into a Static Visualization}},
author = {
Ono, Jorge H. Piazentin
and
Dietrich, Carlos
and
Silva, Claudio T.
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13436}
}
                
@article{
10.1111:cgf.13437,
journal = {Computer Graphics Forum}, title = {{
Cosine-Weighted B-Spline Interpolation on the Face-Centered Cubic Lattice}},
author = {
Rácz, Gergely Ferenc
and
Csébfalvi, Balázs
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13437}
}
                
@article{
10.1111:cgf.13439,
journal = {Computer Graphics Forum}, title = {{
Rendering and Extracting Extremal Features in 3D Fields}},
author = {
Kindlmann, Gordon L.
and
Chiw, Charisee
and
Huynh, Tri
and
Gyulassy, Attila
and
Reppy, John
and
Bremer, Peer-Timo
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13439}
}
                
@article{
10.1111:cgf.13438,
journal = {Computer Graphics Forum}, title = {{
Spatio-Temporal Contours from Deep Volume Raycasting}},
author = {
Frey, Steffen
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13438}
}
                
@article{
10.1111:cgf.13440,
journal = {Computer Graphics Forum}, title = {{
SetCoLa: High-Level Constraints for Graph Layout}},
author = {
Hoffswell, Jane
and
Borning, Alan
and
Heer, Jeffrey
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13440}
}
                
@article{
10.1111:cgf.13441,
journal = {Computer Graphics Forum}, title = {{
Multiscale Visualization and Exploration of Large Bipartite Graphs}},
author = {
Pezzotti, Nicola
and
Fekete, Jean-Daniel
and
Höllt, Thomas
and
Lelieveldt, Boudewijn P. F.
and
Eisemann, Elmar
and
Vilanova, Anna
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13441}
}
                
@article{
10.1111:cgf.13442,
journal = {Computer Graphics Forum}, title = {{
Interactive Investigation of Traffic Congestion on Fat-Tree Networks Using TREESCOPE}},
author = {
Bhatia, Harsh
and
Jain, Nikhil
and
Bhatele, Abhinav
and
Livnat, Yarden
and
Domke, Jens
and
Pascucci, Valerio
and
Bremer, Peer-Timo
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13442}
}

Browse

Recent Submissions

Now showing 1 - 48 of 48
  • Item
    EuroVis 2018: Frontmatter
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Heer, Jeffrey; Leitte, Heike; Ropinski, Timo; Jeffrey Heer and Heike Leitte and Timo Ropinski
  • Item
    Hierarchical Correlation Clustering in Multiple 2D Scalar Fields
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Liebmann, Tom; Weber, Gunther H.; Scheuermann, Gerik; Jeffrey Heer and Heike Leitte and Timo Ropinski
    Sets of multiple scalar fields can be used to model many types of variation in data, such as uncertainty in measurements and simulations or time-dependent behavior of scalar quantities. Many structural properties of such fields can be explained by dependencies between different points in the scalar field. Although these dependencies can be of arbitrary complexity, correlation, i.e., the linear dependency, already provides significant structural information. Existing methods for correlation analysis are usually limited to positive correlation, handle only local dependencies, or use combinatorial approximations to this continuous problem. We present a new approach for computing and visualizing correlated regions in sets of 2-dimensional scalar fields. This paper describes the following three main contributions: (i) An algorithm for hierarchical correlation clustering resulting in a dendrogram, (ii) a generalization of topological landscapes for dendrogram visualization, and (iii) a new method for incorporating negative correlation values in the clustering and visualization. All steps are designed to preserve the special properties of correlation coefficients. The results are visualized in two linked views, one showing the cluster hierarchy as 2D landscape and the other providing a spatial context in the scalar field's domain. Different coloring and texturing schemes coupled with interactive selection support an exploratory data analysis.
  • Item
    Representative Consensus from Limited-Size Ensembles
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Mirzargar, Mahsa; Whitaker, Ross T.; Jeffrey Heer and Heike Leitte and Timo Ropinski
    Characterizing the uncertainty and extracting reliable visual information from ensemble data have been persistent challenges in various disciplines, specifically in simulation sciences. Many ensemble analysis and visualization techniques take a probabilistic approach to this problem with the assumption that the ensemble size is large enough to extract reliable statistical or probabilistic summaries. However, many real-life ensembles are rather limited in size, with only a handful of members, due to various restrictions such as storage, computational power, or sampling limitations. As a result, probabilistic inference is subject to imprecision and can potentially result in untrustworthy information in the presence of a limited sample-size ensemble. In this case, a more reliable approach is to fuse the information present in an ensemble with a limited number of members with minimal assumptions. In this paper, we propose a technique to construct a representative consensus that is particularly suited for ensembles of a relatively small size. The proposed technique casts the problem as an ordering problem in which at each point in the domain, the ensemble members are ranked based on the local neighborhood. This local approach allows us to provide shape and irregularity sensitivity. The local order statistics will then be fused to construct a global consensus using a Bayesian approach to ensure spatial coherency of the local information. We demonstrate the utility of the proposed technique using a synthetic and two real-life examples.
  • Item
    Time Lattice: A Data Structure for the Interactive Visual Analysis of Large Time Series
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Miranda, Fabio; Lage, Marcos; Doraiswamy, Harish; Mydlarz, Charlie; Salamon, Justin; Lockerman, Yitzchak; Freire, Juliana; Silva, Claudio T.; Jeffrey Heer and Heike Leitte and Timo Ropinski
    Advances in technology coupled with the availability of low-cost sensors have resulted in the continuous generation of large time series from several sources. In order to visually explore and compare these time series at different scales, analysts need to execute online analytical processing (OLAP) queries that include constraints and group-by's at multiple temporal hierarchies. Effective visual analysis requires these queries to be interactive. However, while existing OLAP cube-based structures can support interactive query rates, the exponential memory requirement to materialize the data cube is often unsuitable for large data sets. Moreover, none of the recent space-efficient cube data structures allow for updates. Thus, the cube must be re-computed whenever there is new data, making them impractical in a streaming scenario. We propose Time Lattice, a memory-efficient data structure that makes use of the implicit temporal hierarchy to enable interactive OLAP queries over large time series. Time Lattice is a subset of a fully materialized cube and is designed to handle fast updates and streaming data. We perform an experimental evaluation which shows that the space efficiency of the data structure does not hamper its performance when compared to the state of the art. In collaboration with signal processing and acoustics research scientists, we use the Time Lattice data structure to design the Noise Profiler, a web-based visualization framework that supports the analysis of noise from cities. We demonstrate the utility of Noise Profiler through a set of case studies.
  • Item
    Key Time Steps Selection for Large-Scale Time-Varying Volume Datasets Using an Information-Theoretic Storyboard
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Zhou, Bo; Chiang, Yi-Jen; Jeffrey Heer and Heike Leitte and Timo Ropinski
    Key time steps selection is essential for effective and efficient scientific visualization of large-scale time-varying datasets. We present a novel approach that can decide the number of most representative time steps while selecting them to minimize the difference in the amount of information from the original data.We use linear interpolation to reconstruct the data of intermediate time steps between selected time steps.We propose an evaluation of selected time steps by computing the difference in the amount of information (called information difference) using variation of information (VI) from information theory, which compares the interpolated time steps against the original data. In the one-time preprocessing phase, a dynamic programming is applied to extract the subset of time steps that minimize the information difference. In the run-time phase, a novel chart is used to present the dynamic programming results, which serves as a storyboard of the data to guide the user to select the best time steps very efficiently. We extend our preprocessing approach to a novel out-of-core approximate algorithm to achieve optimal I/O cost, which also greatly reduces the in-core computing time and exhibits a nice trade-off between computing speed and accuracy. As shown in the experiments, our approximate method outperforms the previous globally optimal DTW approach [TLS12] on out-of-core data by significantly improving the running time while keeping similar qualities, and is our major contribution.
  • Item
    ChangeCatcher: Increasing Inter-author Awareness for Visualization Development
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Loorak, Mona Hosseinkhani; Tory, Melanie; Carpendale, Sheelagh; Jeffrey Heer and Heike Leitte and Timo Ropinski
    We introduce an approach for explicitly revealing changes between versions of a visualization workbook to support version comparison tasks. Visualization authors may need to understand version changes for a variety of reasons, analogous to document editing. An author who has been away for a while may need to catch up on the changes made by their co-author, or a person responsible for formatting compliance may need to check formatting changes that occurred since the last time they reviewed the work. We introduce ChangeCatcher, a prototype tool to help people find and understand changes in a visualization workbook, specifically, a Tableau workbook. Our design is based on interviews we conducted with experts to investigate user needs and practices around version comparison. ChangeCatcher provides an overview of changes across six categories, and employs a multi-level details-on-demand approach to progressively reveal details. Our qualitative study showed that ChangeCatcher's methods for explicitly revealing and categorizing version changes were helpful in version comparison tasks.
  • Item
    Towards Easy Comparison of Local Businesses Using Online Reviews
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Wang, Yong; Haleem, Hammad; Shi, Conglei; Wu, Yanhong; Zhao, Xun; Fu, Siwei; Qu, Huamin; Jeffrey Heer and Heike Leitte and Timo Ropinski
    With the rapid development of e-commerce, there is an increasing number of online review websites, such as Yelp, to help customers make better purchase decisions. Viewing online reviews, including the rating score and text comments by other customers, and conducting a comparison between different businesses are the key to making an optimal decision. However, due to the massive amount of online reviews, the potential difference of user rating standards, and the significant variance of review time, length, details and quality, it is difficult for customers to achieve a quick and comprehensive comparison. In this paper, we present E-Comp, a carefully-designed visual analytics system based on online reviews, to help customers compare local businesses at different levels of details. More specifically, intuitive glyphs overlaid on maps are designed for quick candidate selection. Grouped Sankey diagram visualizing the rating difference by common customers is chosen for more reliable comparison of two businesses. Augmented word cloud showing adjective-noun word pairs, combined with a temporal view, is proposed to facilitate in-depth comparison of businesses in terms of different time periods, rating scores and features. The effectiveness and usability of E-Comp are demonstrated through a case study and in-depth user interviews.
  • Item
    Chart Constellations: Effective Chart Summarization for Collaborative and Multi-User Analyses
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Xu, Shenyu; Bryan, Chris; Li, Jianping Kelvin; Zhao, Jian; Ma, Kwan-Liu; Jeffrey Heer and Heike Leitte and Timo Ropinski
    Many data problems in the real world are complex and require multiple analysts working together to uncover embedded insights by creating chart-driven data stories. How, as a subsequent analysis step, do we interpret and learn from these collections of charts? We present Chart Constellations, a system to interactively support a single analyst in the review and analysis of data stories created by other collaborative analysts. Instead of iterating through the individual charts for each data story, the analyst can project, cluster, filter, and connect results from all users in a meta-visualization approach. Constellations supports deriving summary insights about prior investigations and supports the exploration of new, unexplored regions in the dataset. To evaluate our system, we conduct a user study comparing it against data science notebooks. Results suggest that Constellations promotes the discovery of both broad and high-level insights, including theme and trend analysis, subjective evaluation, and hypothesis generation.
  • Item
    Visualizing Expanded Query Results
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Mazurek, Michael; Waldner, Manuela; Jeffrey Heer and Heike Leitte and Timo Ropinski
    When performing queries in web search engines, users often face difficulties choosing appropriate query terms. Search engines therefore usually suggest a list of expanded versions of the user query to disambiguate it or to resolve potential term mismatches. However, it has been shown that users find it difficult to choose an expanded query from such a list. In this paper, we describe the adoption of set-based text visualization techniques to visualize how query expansions enrich the result space of a given user query and how the result sets relate to each other. Our system uses a linguistic approach to expand queries and topic modeling to extract the most informative terms from the results of these queries. In a user study, we compare a common text list of query expansion suggestions to three set-based text visualization techniques adopted for visualizing expanded query results - namely, Compact Euler Diagrams, Parallel Tag Clouds, and a List View - to resolve ambiguous queries using interactive query expansion. Our results show that text visualization techniques do not increase retrieval efficiency, precision, or recall. Overall, users rate Parallel Tag Clouds visualizing key terms of the expanded query space lowest. Based on the results, we derive recommendations for visualizations of query expansion results, text visualization techniques in general, and discuss alternative use cases of set-based text visualization techniques in the context of web search.
  • Item
    Interactive Visual Exploration of Local Patterns in Large Scatterplot Spaces
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Chegini, Mohammad; Shao, Lin; Gregor, Robert; Lehmann, Dirk Joachim; Andrews, Keith; Schreck, Tobias; Jeffrey Heer and Heike Leitte and Timo Ropinski
    Analysts often use visualisation techniques like a scatterplot matrix (SPLOM) to explore multivariate datasets. The scatterplots of a SPLOM can help to identify and compare two-dimensional global patterns. However, local patterns which might only exist within subsets of records are typically much harder to identify and may go unnoticed among larger sets of plots in a SPLOM. This paper explores the notion of local patterns and presents a novel approach to visually select, search for, and compare local patterns in a multivariate dataset. Model-based and shape-based pattern descriptors are used to automatically compare local regions in scatterplots to assist in the discovery of similar local patterns. Mechanisms are provided to assess the level of similarity between local patterns and to rank similar patterns effectively. Moreover, a relevance feedback module is used to suggest potentially relevant local patterns to the user. The approach has been implemented in an interactive tool and demonstrated with two real-world datasets and use cases. It supports the discovery of potentially useful information such as clusters, functional dependencies between variables, and statistical relationships in subsets of data records and dimensions.
  • Item
    Fast and Accurate CNN-based Brushing in Scatterplots
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Fan, Chaoran; Hauser, Helwig; Jeffrey Heer and Heike Leitte and Timo Ropinski
    Brushing plays a central role in most modern visual analytics solutions and effective and efficient techniques for data selection are key to establishing a successful human-computer dialogue. With this paper, we address the need for brushing techniques that are both fast, enabling a fluid interaction in visual data exploration and analysis, and also accurate, i.e., enabling the user to effectively select specific data subsets, even when their geometric delimination is non-trivial. We present a new solution for a near-perfect sketch-based brushing technique, where we exploit a convolutional neural network (CNN) for estimating the intended data selection from a fast and simple click-and-drag interaction and from the data distribution in the visualization. Our key contributions include a drastically reduced error rate-now below 3%, i.e., less than half of the so far best accuracy- and an extension to a larger variety of selected data subsets, going beyond previous limitations due to linear estimation models.
  • Item
    Towards User-Centered Active Learning Algorithms
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Bernard, Jürgen; Zeppelzauer, Matthias; Lehmann, Markus; Müller, Martin; Sedlmair, Michael; Jeffrey Heer and Heike Leitte and Timo Ropinski
    The labeling of data sets is a time-consuming task, which is, however, an important prerequisite for machine learning and visual analytics. Visual-interactive labeling (VIAL) provides users an active role in the process of labeling, with the goal to combine the potentials of humans and machines to make labeling more efficient. Recent experiments showed that users apply different strategies when selecting instances for labeling with visual-interactive interfaces. In this paper, we contribute a systematic quantitative analysis of such user strategies. We identify computational building blocks of user strategies, formalize them, and investigate their potentials for different machine learning tasks in systematic experiments. The core insights of our experiments are as follows. First, we identified that particular user strategies can be used to considerably mitigate the bootstrap (cold start) problem in early labeling phases. Second, we observed that they have the potential to outperform existing active learning strategies in later phases. Third, we analyzed the identified core building blocks, which can serve as the basis for novel selection strategies. Overall, we observed that data-based user strategies (clusters, dense areas) work considerably well in early phases, while model-based user strategies (e.g., class separation) perform better during later phases. The insights gained from this work can be applied to develop novel active learning approaches as well as to better guide users in visual interactive labeling.
  • Item
    Exploring the Visualization Design Space with Repertory Grids
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Kurzhals, Kuno; Weiskopf, Daniel; Jeffrey Heer and Heike Leitte and Timo Ropinski
    There is an ongoing discussion in the visualization community about the relevant factors that render a visualization effective, expressive, memorable, aesthetically pleasing, etc. These factors lead to a large design space for visualizations. To explore this design space, qualitative research methods based on observations and interviews are often necessary. We describe an interview method that allows us to systematically acquire and assess important factors from subjective answers by interviewees. To this end, we adopt the repertory grid methodology in the context of visualization. It is based on the personal construct theory: each personality interprets a topic based on a set of personal, basic constructs expressed as contrasts. For the individual interpretation of visualizations, this means that these personal terms can be very different, depending on numerous influences, such as the prior experiences of the interviewed person. We present an interviewing process, visual interface, and qualitative and quantitative analysis procedures that are specifically devised to fit the needs of visualization applications. A showcase interview with 15 typical static information visualizations and 10 participants demonstrates that our approach is effective in identifying common constructs as well as individual differences. In particular, we investigate differences between expert and nonexpert interviewees. Finally, we discuss the differences to other qualitative methods and how the repertory grid can be embedded in existing theoretical frameworks of visualization research for the design process.
  • Item
    Design Factors for Summary Visualization in Visual Analytics
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Sarikaya, Alper; Gleicher, Michael; Szafir, Danielle Albers; Jeffrey Heer and Heike Leitte and Timo Ropinski
    Data summarization allows analysts to explore datasets that may be too complex or too large to visualize in detail. Designers face a number of design and implementation choices when using summarization in visual analytics systems. While these choices influence the utility of the resulting system, there are no clear guidelines for the use of these summarization techniques. In this paper, we codify summarization use in existing systems to identify key factors in the design of summary visualizations. We use quantitative content analysis to systematically survey examples of visual analytics systems and enumerate the use of these design factors in data summarization. Through this analysis, we expose the relationship between design considerations, strategies for data summarization in visualization systems, and how different summarization methods influence the analyses supported by systems. We use these results to synthesize common patterns in real-world use of summary visualizations and highlight open challenges and opportunities that these patterns offer for designing effective systems. This work provides a more principled understanding of design practices for summary visualization and offers insight into underutilized approaches.
  • Item
    Assessing Effects of Task and Data Distribution on the Effectiveness of Visual Encodings
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Kim, Younghoon; Heer, Jeffrey; Jeffrey Heer and Heike Leitte and Timo Ropinski
    In addition to the choice of visual encodings, the effectiveness of a data visualization may vary with the analytical task being performed and the distribution of data values. To better assess these effects and create refined rankings of visual encodings, we conduct an experiment measuring subject performance across task types (e.g., comparing individual versus aggregate values) and data distributions (e.g., with varied cardinalities and entropies).We compare performance across 12 encoding specifications of trivariate data involving 1 categorical and 2 quantitative fields, including the use of x, y, color, size, and spatial subdivision (i.e., faceting). Our results extend existing models of encoding effectiveness and suggest improved approaches for automated design. For example, we find that colored scatterplots (with positionally-coded quantities and color-coded categories) perform well for comparing individual points, but perform poorly for summary tasks as the number of categories increases.
  • Item
    The Perception of Graph Properties in Graph Layouts
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Soni, Utkarsh; Lu, Yafeng; Hansen, Brett; Purchase, Helen C.; Kobourov, Stephen; Maciejewski, Ross; Jeffrey Heer and Heike Leitte and Timo Ropinski
    When looking at drawings of graphs, questions about graph density, community structures, local clustering and other graph properties may be of critical importance for analysis. While graph layout algorithms have focused on minimizing edge crossing, symmetry, and other such layout properties, there is not much known about how these algorithms relate to a user's ability to perceive graph properties for a given graph layout. In this study, we apply previously established methodologies for perceptual analysis to identify which graph drawing layout will help the user best perceive a particular graph property. We conduct a large scale (n = 588) crowdsourced experiment to investigate whether the perception of two graph properties (graph density and average local clustering coefficient) can be modeled using Weber's law. We study three graph layout algorithms from three representative classes (Force Directed - FD, Circular, and Multi-Dimensional Scaling - MDS), and the results of this experiment establish the precision of judgment for these graph layouts and properties. Our findings demonstrate that the perception of graph density can be modeled with Weber's law. Furthermore, the perception of the average clustering coefficient can be modeled as an inverse of Weber's law, and the MDS layout showed a significantly different precision of judgment than the FD layout.
  • Item
    Explorative Blood Flow Visualization using Dynamic Line Filtering based on Surface Features
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Behrendt, Benjamin; Berg, Philipp; Beuing, Oliver; Preim, Bernhard; Saalfeld, Sylvia; Jeffrey Heer and Heike Leitte and Timo Ropinski
    Rupture risk assessment is a key to devise patient-specific treatment plans of cerebral aneurysms. To understand and predict the development of aneurysms and other vascular diseases over time, both hemodynamic flow patterns and their effect on the vessel surface need to be analyzed. Flow structures close to the vessel wall often correlate directly with local changes in surface parameters, such as pressure or wall shear stress. Yet, in many existing applications, the analyses of flow and surface features are either somewhat detached from one another or only globally available. Especially for the identification of specific blood flow characteristics that cause local startling parameters on the vessel surface, like elevated pressure values, an interactive analysis tool is missing. The explorative visualization of flow data is challenging due to the complexity of the underlying data. In order to find meaningful structures in the entirety of the flow, the data has to be filtered based on the respective explorative aim. In this paper, we present a combination of visualization, filtering and interaction techniques for explorative analysis of blood flow with a focus on the relation of local surface parameters and underlying flow structures. Coherent bundles of pathlines can be interactively selected based on their relation to features of the vessel wall and further refined based on their own hemodynamic features. This allows the user to interactively select and explore flow structures locally affecting a certain region on the vessel wall and therefore to understand the cause and effect relationship between these entities. Additionally, multiple selected flow structures can be compared with respect to their quantitative parameters, such as flow speed. We confirmed the usefulness of our approach by conducting an informal interview with two expert neuroradiologists and an expert in flow simulation. In addition, we recorded several insights the neuroradiologists were able to gain with the help of our tool.
  • Item
    Visual and Quantitative Analysis of Great Arteries' Blood Flow Jets in Cardiac 4D PC-MRI Data
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Köhler, Benjamin; Grothoff, Matthias; Gutberlet, Matthias; Preim, Bernhard; Jeffrey Heer and Heike Leitte and Timo Ropinski
    Flow in the great arteries (aorta, pulmonary artery) is normally laminar with a parabolic velocity profile. Eccentric flow jets are linked to various diseases like aneurysms. Cardiac 4D PC-MRI data provide spatio-temporally resolved blood flow information for the whole cardiac cycle. In this work, we establish a time-dependent visualization and quantification of flow jets. For this purpose, equidistant measuring planes are automatically placed along the vessel's centerline. The flow jet position and region with highest velocities are extracted for every plane in each time step. This is done during pre-processing and without user-defined parameters. We visualize the main flow jet as geometric tube. High-velocity areas are depicted as a net around this tube. Both geometries are time-dependent and can be animated. Quantitative values are provided during cross-sectional measuring plane-based evaluation. Moreover, we offer a plot visualization as summary of flow jet characteristics for the selected plane. Our physiologically plausible results are in accordance with medical findings. Our clinical collaborators appreciate the possibility to view the flow jet in the whole vessel at once, which normally requires repeated pathline filtering due to varying velocities along the vessel course. The overview plots are considered as valuable for documentation purposes.
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    Bladder Runner: Visual Analytics for the Exploration of RT-Induced Bladder Toxicity in a Cohort Study
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Raidou, Renata Georgia; Casares-Magaz, Oscar; Amirkhanov, Aleksandr; Moiseenko, Vitali; Muren, Ludvig P.; Einck, John P.; Vilanova, Anna; Gröller, Eduard; Jeffrey Heer and Heike Leitte and Timo Ropinski
    We present the Bladder Runner, a novel tool to enable detailed visual exploration and analysis of the impact of bladder shape variation on the accuracy of dose delivery, during the course of prostate cancer radiotherapy (RT). Our tool enables the investigation of individual patients and cohorts through the entire treatment process, and it can give indications of RT-induced complications for the patient. In prostate cancer RT treatment, despite the design of an initial plan prior to dose administration, bladder toxicity remains very common. The main reason is that the dose is delivered in multiple fractions over a period of weeks, during which, the anatomical variation of the bladder - due to differences in urinary filling - causes deviations between planned and delivered doses. Clinical researchers want to correlate bladder shape variations to dose deviations and toxicity risk through cohort studies, to understand which specific bladder shape characteristics are more prone to side effects. This is currently done with Dose-Volume Histograms (DVHs), which provide limited, qualitative insight. The effect of bladder variation on dose delivery and the resulting toxicity cannot be currently examined with the DVHs. To address this need, we designed and implemented the Bladder Runner, which incorporates visualization strategies in a highly interactive environment with multiple linked views. Individual patients can be explored and analyzed through the entire treatment period, while inter-patient and temporal exploration, analysis and comparison are also supported. We demonstrate the applicability of our presented tool with a usage scenario, employing a dataset of 29 patients followed through the course of the treatment, across 13 time points. We conducted an evaluation with three clinical researchers working on the investigation of RT-induced bladder toxicity. All participants agreed that Bladder Runner provides better understanding and new opportunities for the exploration and analysis of the involved cohort data.
  • Item
    ConcaveCubes: Supporting Cluster-based Geographical Visualization in Large Data Scale
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Li, Mingzhao; Choudhury, Farhana; Bao, Zhifeng; Samet, Hanan; Sellis, Timos; Jeffrey Heer and Heike Leitte and Timo Ropinski
    In this paper we study the problem of supporting effective and scalable visualization for the rapidly increasing volumes of urban data. From an extensive literature study, we find that the existing solutions suffer from at least one of the drawbacks below: (i) loss of interesting structures/outliers due to sampling; (ii) supporting heatmaps only, which provides limited information; and (iii) no notion of real-world geography semantics (e.g., country, state, city) is captured in the visualization result as well as the underlying index. Therefore, we propose ConcaveCubes, a cluster-based data cube to support interactive visualization of large-scale multidimensional urban data. Specifically, we devise an appropriate visualization abstraction and visualization design based on clusters. We propose a novel concave hull construction method to support boundary based cluster map visualization, where real-world geographical semantics are preserved without any information loss. Instead of calculating the clusters on demand, ConcaveCubes (re)utilizes existing calculation and visualization results to efficiently support different kinds of user interactions. We conduct extensive experiments using real-world datasets and show the efficiency and effectiveness of ConcaveCubes by comparing with the state-of-the-art cube-based solutions.
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    Hypersliceplorer: Interactive Visualization of Shapes in Multiple Dimensions
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Torsney-Weir, Thomas; Möller, Torsten; Sedlmair, Michael; Kirby, R. Mike; Jeffrey Heer and Heike Leitte and Timo Ropinski
    In this paper we present Hypersliceplorer, an algorithm for generating 2D slices of multi-dimensional shapes defined by a simplical mesh. Often, slices are generated by using a parametric form and then constraining parameters to view the slice. In our case, we developed an algorithm to slice a simplical mesh of any number of dimensions with a two-dimensional slice. In order to get a global appreciation of the multi-dimensional object, we show multiple slices by sampling a number of different slicing points and projecting the slices into a single view per dimension pair. These slices are shown in an interactive viewer which can switch between a global view (all slices) and a local view (single slice). We show how this method can be used to study regular polytopes, differences between spaces of polynomials, and multi-objective optimization surfaces.
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    Exploring High-Dimensional Structure via Axis-Aligned Decomposition of Linear Projections
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Thiagarajan, Jayaraman J.; Liu, Shusen; Ramamurthy, Karthikeyan Natesan; Bremer, Peer-Timo; Jeffrey Heer and Heike Leitte and Timo Ropinski
    Two-dimensional embeddings remain the dominant approach to visualize high dimensional data. The choice of embeddings ranges from highly non-linear ones, which can capture complex relationships but are difficult to interpret quantitatively, to axis-aligned projections, which are easy to interpret but are limited to bivariate relationships. Linear project can be considered as a compromise between complexity and interpretability, as they allow explicit axes labels, yet provide significantly more degrees of freedom compared to axis-aligned projections. Nevertheless, interpreting the axes directions, which are often linear combinations of many non-trivial components, remains difficult. To address this problem we introduce a structure aware decomposition of (multiple) linear projections into sparse sets of axis-aligned projections, which jointly capture all information of the original linear ones. In particular, we use tools from Dempster-Shafer theory to formally define how relevant a given axis-aligned project is to explain the neighborhood relations displayed in some linear projection. Furthermore, we introduce a new approach to discover a diverse set of high quality linear projections and show that in practice the information of k linear projections is often jointly encoded in ~ k axis-aligned plots. We have integrated these ideas into an interactive visualization system that allows users to jointly browse both linear projections and their axis-aligned representatives. Using a number of case studies we show how the resulting plots lead to more intuitive visualizations and new insights.
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    Interactive Analysis of Word Vector Embeddings
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Heimerl, Florian; Gleicher, Michael; Jeffrey Heer and Heike Leitte and Timo Ropinski
    Word vector embeddings are an emerging tool for natural language processing. They have proven beneficial for a wide variety of language processing tasks. Their utility stems from the ability to encode word relationships within the vector space. Applications range from components in natural language processing systems to tools for linguistic analysis in the study of language and literature. In many of these applications, interpreting embeddings and understanding the encoded grammatical and semantic relations between words is useful, but challenging. Visualization can aid in such interpretation of embeddings. In this paper, we examine the role for visualization in working with word vector embeddings. We provide a literature survey to catalogue the range of tasks where the embeddings are employed across a broad range of applications. Based on this survey, we identify key tasks and their characteristics. Then, we present visual interactive designs that address many of these tasks. The designs integrate into an exploration and analysis environment for embeddings. Finally, we provide example use cases for them and discuss domain user feedback.
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    PixelSNE: Pixel-Aligned Stochastic Neighbor Embedding for Efficient 2D Visualization with Screen-Resolution Precision
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Kim, Minjeong; Choi, Minsuk; Lee, Sunwoong; Tang, Jian; Park, Haesun; Choo, Jaegul; Jeffrey Heer and Heike Leitte and Timo Ropinski
    Embedding and visualizing large-scale high-dimensional data in a two-dimensional space is an important problem, because such visualization can reveal deep insights of complex data. However, most of the existing embedding approaches run on an excessively high precision, even when users want to obtain a brief insight from a visualization of large-scale datasets, ignoring the fact that in the end, the outputs are embedded onto a fixed-range pixel-based screen space. Motivated by this observation and directly considering the properties of screen space in an embedding algorithm, we propose Pixel-Aligned Stochastic Neighbor Embedding (PixelSNE), a highly efficient screen resolution-driven 2D embedding method which accelerates Barnes-Hut treebased t-distributed stochastic neighbor embedding (BH-SNE), which is known to be a state-of-the-art 2D embedding method. Our experimental results show a significantly faster running time for PixelSNE compared to BH-SNE for various datasets while maintaining comparable embedding quality.
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    Visualizing Multidimensional Data with Order Statistics
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Raj, Mukund; Whitaker, Ross T.; Jeffrey Heer and Heike Leitte and Timo Ropinski
    Multidimensional data sets are common in many domains, and dimensionality reduction methods that determine a lower dimensional embedding are widely used for visualizing such data sets. This paper presents a novel method to project data onto a lower dimensional space by taking into account the order statistics of the individual data points, which are quantified by their depth or centrality in the overall set. Thus, in addition to conveying relative distances in the data, the proposed method also preserves the order statistics, which are often lost or misrepresented by existing visualization methods. The proposed method entails a modification of the optimization objective of conventional multidimensional scaling (MDS) by introducing a term that penalizes discrepancies between centrality structures in the original space and the embedding. We also introduce two strategies for visualizing lower dimensional embeddings of multidimensional data that takes advantage of the coherent representation of centrality provided by the proposed projection method. We demonstrate the effectiveness of our visualization with comparisons on different kinds of multidimensional data, including categorical and multimodal, from a variety of domains such as botany and health care.
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    Visualizing the Phase Space of Heterogeneous Inertial Particles in 2D Flows
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Rojo, Irene Baeza; Gross, Markus; Günther, Tobias; Jeffrey Heer and Heike Leitte and Timo Ropinski
    In many scientific disciplines, the motion of finite-sized objects in fluid flows plays an important role, such as in brownout engineering, sediment transport, oceanology or meteorology. These finite-sized objects are called inertial particles and, in contrast to traditional tracer particles, their motion depends on their current position, their own particle velocity, the time and their size. Thus, the visualization of their motion becomes a high-dimensional problem that entails computational and perceptual challenges. So far, no visualization explored and visualized the particle trajectories under variation of all seeding parameters. In this paper, we propose three coordinated views that visualize the different aspects of the high-dimensional space in which the particles live. We visualize the evolution of particles over time, showing that particles travel different distances in the same time, depending on their size. The second view provides a clear illustration of the trajectories of different particle sizes and allows the user to easily identify differences due to particle size. Finally, we embed the trajectories in the space-velocity domain and visualize their distance to an attracting manifold using ribbons. In all views, we support interactive linking and brushing, and provide abstraction through density volumes that are shown by direct volume rendering and isosurface slabs. Using our method, users gain deeper insights into the dynamics of inertial particles in 2D fluids, including size-dependent separation, preferential clustering and attraction. We demonstrate the effectiveness of our method in multiple steady and unsteady 2D flows.
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    Visualization of 4D Vector Field Topology
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Hofmann, Lutz; Rieck, Bastian; Sadlo, Filip; Jeffrey Heer and Heike Leitte and Timo Ropinski
    In this paper, we present an approach to the topological analysis of four-dimensional vector fields. In analogy to traditional 2D and 3D vector field topology, we provide a classification and visual representation of critical points, together with a technique for extracting their invariant manifolds. For effective exploration of the resulting four-dimensional structures, we present a 4D camera that provides concise representation by exploiting projection degeneracies, and a 4D clipping approach that avoids self-intersection in the 3D projection. We exemplify the properties and the utility of our approach using specific synthetic cases.
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    An Approximate Parallel Vectors Operator for Multiple Vector Fields
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Gerrits, Tim; Rössl, Christian; Theisel, Holger; Jeffrey Heer and Heike Leitte and Timo Ropinski
    The Parallel Vectors (PV) Operator extracts the locations of points where two vector fields are parallel. In general, these features are line structures. The PV operator has been used successfully for a variety of problems, which include finding vortex-core lines or extremum lines. We present a new generic feature extraction method for multiple 3D vector fields: The Approximate Parallel Vectors (APV) Operator extracts lines where all fields are approximately parallel. The definition of the APV operator is based on the application of PV for two vector fields that are derived from the given set of fields. The APV operator enables the direct visualization of features of vector field ensembles without processing fields individually and without causing visual clutter. We give a theoretical analysis of the APV operator and demonstrate its utility for a number of ensemble data.
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    Core Lines in 3D Second-Order Tensor Fields
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Oster, Timo; Rössl, Christian; Theisel, Holger; Jeffrey Heer and Heike Leitte and Timo Ropinski
    Vortices are important features in vector fields that show a swirling behavior around a common core. The concept of a vortex core line describes the center of this swirling behavior. In this work, we examine the extension of this concept to 3D second-order tensor fields. Here, a behavior similar to vortices in vector fields can be observed for trajectories of the eigenvectors. Vortex core lines in vector fields were defined by Sujudi and Haimes to be the locations where stream lines are parallel to an eigenvector of the Jacobian. We show that a similar criterion applied to the eigenvector trajectories of a tensor field yields structurally stable lines that we call tensor core lines. We provide a formal definition of these structures and examine their mathematical properties. We also present a numerical algorithm for extracting tensor core lines in piecewise linear tensor fields. We find all intersections of tensor core lines with the faces of a dataset using a simple and robust root finding algorithm. Applying this algorithm to tensor fields obtained from structural mechanics simulations shows that it is able to effectively detect and visualize regions of rotational or hyperbolic behavior of eigenvector trajectories.
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    Track Xplorer: A System for Visual Analysis of Sensor-based Motor Activity Predictions
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Cavallo, Marco; Demiralp, Çağatay; Jeffrey Heer and Heike Leitte and Timo Ropinski
    With the rapid commoditization of wearable sensors, detecting human movements from sensor datasets has become increasingly common over a wide range of applications. To detect activities, data scientists iteratively experiment with different classifiers before deciding which model to deploy. Effective reasoning about and comparison of alternative classifiers are crucial in successful model development. This is, however, inherently difficult in developing classifiers for sensor data, where the intricacy of long temporal sequences, high prediction frequency, and imprecise labeling make standard evaluation methods relatively ineffective and even misleading. We introduce Track Xplorer, an interactive visualization system to query, analyze, and compare the predictions of sensor-data classifiers. Track Xplorer enables users to interactively explore and compare the results of different classifiers, and assess their accuracy with respect to the ground-truth labels and video. Through integration with a version control system, Track Xplorer supports tracking of models and their parameters without additional workload on model developers. Track Xplorer also contributes an extensible algebra over track representations to filter, compose, and compare classification outputs, enabling users to reason effectively about classifier performance. We apply Track Xplorer in a collaborative project to develop classifiers to detect movements from multisensor data gathered from Parkinson's disease patients. We demonstrate how Track Xplorer helps identify early on possible systemic data errors, effectively track and compare the results of different classifiers, and reason about and pinpoint the causes of misclassifications.
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    ThreadReconstructor: Modeling Reply-Chains to Untangle Conversational Text through Visual Analytics
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) El-Assady, Mennatallah; Sevastjanova, Rita; Keim, Daniel; Collins, Christopher; Jeffrey Heer and Heike Leitte and Timo Ropinski
    We present ThreadReconstructor, a visual analytics approach for detecting and analyzing the implicit conversational structure of discussions, e.g., in political debates and forums. Our work is motivated by the need to reveal and understand single threads in massive online conversations and verbatim text transcripts. We combine supervised and unsupervised machine learning models to generate a basic structure that is enriched by user-defined queries and rule-based heuristics. Depending on the data and tasks, users can modify and create various reconstruction models that are presented and compared in the visualization interface. Our tool enables the exploration of the generated threaded structures and the analysis of the untangled reply-chains, comparing different models and their agreement. To understand the inner-workings of the models, we visualize their decision spaces, including all considered candidate relations. In addition to a quantitative evaluation, we report qualitative feedback from an expert user study with four forum moderators and one machine learning expert, showing the effectiveness of our approach.
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    A General Illumination Model for Molecular Visualization
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Casajus, Pedro Hermosilla; Vázquez, Pere-Pau; Vinacua, Àlvar; Ropinski, Timo; Jeffrey Heer and Heike Leitte and Timo Ropinski
    Several visual representations have been developed over the years to visualize molecular structures, and to enable a better understanding of their underlying chemical processes. Today, the most frequently used atom-based representations are the Space-filling, the Solvent Excluded Surface, the Balls-and-Sticks, and the Licorice models. While each of these representations has its individual benefits, when applied to large-scale models spatial arrangements can be difficult to interpret when employing current visualization techniques. In the past it has been shown that global illumination techniques improve the perception of molecular visualizations; unfortunately existing approaches are tailored towards a single visual representation. We propose a general illumination model for molecular visualization that is valid for different representations. With our illumination model, it becomes possible, for the first time, to achieve consistent illumination among all atom-based molecular representations. The proposed model can be further evaluated in real-time, as it employs an analytical solution to simulate diffuse light interactions between objects. To be able to derive such a solution for the rather complicated and diverse visual representations, we propose the use of regression analysis together with adapted parameter sampling strategies as well as shape parametrization guided sampling, which are applied to the geometric building blocks of the targeted visual representations. We will discuss the proposed sampling strategies, the derived illumination model, and demonstrate its capabilities when visualizing several dynamic molecules.
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    Analyzing Residue Surface Proximity to Interpret Molecular Dynamics
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Lichtenberg, Nils; Menges, Raphael; Ageev, Vladimir; George, Ajay Abisheck Paul; Heimer, Pascal; Imhof, Diana; Lawonn, Kai; Jeffrey Heer and Heike Leitte and Timo Ropinski
    The surface of a molecule holds important information about the interaction behavior with other molecules. In dynamic folding or docking processes, residues of amino acids with different properties change their position within the molecule over time. The atoms of the residues that are accessible to the solvent can directly contribute to binding interactions, while residues buried within the molecular structure contribute to the stability of the molecule. Understanding patterns and causality of structural changes is important for experts in the pharmaceutical domain, e.g., in the process of drug design. We apply an iterative computation of the Solvent Accessible Surface in order to extract virtual layers of a molecule. The extraction allows to track the movement of residues in the body of the molecule, with respect to the distance of the residue to the surface or the core during dynamics simulations. We visualize the obtained layer information for the complete time span of the molecular dynamics simulation as a 2D-map and for individual time-steps as a 3D-representation of the molecule. The data acquisition has been implemented alongside with further analysis functionality in a prototypical application, which is available to the public domain. We underline the feasibility of our approach with a study from the pharmaceutical domain, where our approach has been used for novel insights into the folding behavior of μ-conotoxins.
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    Visual Analysis of Protein-ligand Interactions
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Vázquez, Pere-Pau; Casajus, Pedro Hermosilla; Guallar, Victor; Estrada, Jorge; Vinacua, Àlvar; Jeffrey Heer and Heike Leitte and Timo Ropinski
    The analysis of protein-ligand interactions is complex because of the many factors at play. Most current methods for visual analysis provide this information in the form of simple 2D plots, which, besides being quite space hungry, often encode a low number of different properties. In this paper we present a system for compact 2D visualization of molecular simulations. It purposely omits most spatial information and presents physical information associated to single molecular components and their pairwise interactions through a set of 2D InfoVis tools with coordinated views, suitable interaction, and focus+context techniques to analyze large amounts of data. The system provides a wide range of motifs for elements such as protein secondary structures or hydrogen bond networks, and a set of tools for their interactive inspection, both for a single simulation and for comparing two different simulations. As a result, the analysis of protein-ligand interactions of Molecular Simulation trajectories is greatly facilitated.
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    DimSUM: Dimension and Scale Unifying Map for Visual Abstraction of DNA Origami Structures
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Miao, Haichao; Llano, Elisa De; Isenberg, Tobias; Gröller, Eduard; Barišic, Ivan; Viola, Ivan; Jeffrey Heer and Heike Leitte and Timo Ropinski
    We present a novel visualization concept for DNA origami structures that integrates a multitude of representations into a Dimension and Scale Unifying Map (DimSUM). This novel abstraction map provides means to analyze, smoothly transition between, and interact with many visual representations of the DNA origami structures in an effective way that was not possible before. DNA origami structures are nanoscale objects, which are challenging to model in silico. In our holistic approach we seamlessly combine three-dimensional realistic shape models, two-dimensional diagrammatic representations, and ordered alignments in one-dimensional arrangements, with semantic transitions across many scales. To navigate through this large, two-dimensional abstraction map we highlight locations that users frequently visit for certain tasks and datasets. Particularly interesting viewpoints can be explicitly saved to optimize the workflow. We have developed DimSUM together with domain scientists specialized in DNA nanotechnology. In the paper we discuss our design decisions for both the visualization and the interaction techniques. We demonstrate two practical use cases in which our approach increases the specialists' understanding and improves their effectiveness in the analysis. Finally, we discuss the implications of our concept for the use of controlled abstraction in visualization in general.
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    VirtualDesk: A Comfortable and Efficient Immersive Information Visualization Approach
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Filho, Jorge A. Wagner; Freitas, Carla M.D.S.; Nedel, Luciana; Jeffrey Heer and Heike Leitte and Timo Ropinski
    3D representations are potentially useful under many circumstances, but suffer from long known perception and interaction challenges. Current immersive technologies, which combine stereoscopic displays and natural interaction, are being progressively seen as an opportunity to tackle this issue, but new guidelines and studies are still needed, especially regarding information visualization. Many proposed approaches are impractical for actual usage, resulting in user discomfort or requiring too much time or space. In this work, we implement and evaluate an alternative data exploration metaphor where the user remains seated and viewpoint change is only realisable through physical movements. All manipulation is done directly by natural mid-air gestures, with the data being rendered at arm's reach. The virtual reproduction of the analyst's desk aims to increase immersion and enable tangible interaction with controls and two dimensional associated information. A comparative user study was carried out against a desktop-based equivalent, exploring a set of 9 perception and interaction tasks based on previous literature and a multidimensional projection use case. We demonstrate that our prototype setup, named VirtualDesk, presents excellent results regarding user comfort and immersion, and performs equally or better in all analytical tasks, while adding minimal or no time overhead and amplifying user subjective perceptions of efficiency and engagement. Results are also contrasted to a previous experiment employing artificial flying navigation, with significant observed improvements.
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    Maps and Globes in Virtual Reality
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Yang, Yalong; Jenny, Bernhard; Dwyer, Tim; Marriott, Kim; Chen, Haohui; Cordeil, Maxime; Jeffrey Heer and Heike Leitte and Timo Ropinski
    This paper explores different ways to render world-wide geographic maps in virtual reality (VR). We compare: (a) a 3D exocentric globe, where the user's viewpoint is outside the globe; (b) a flat map (rendered to a plane in VR); (c) an egocentric 3D globe, with the viewpoint inside the globe; and (d) a curved map, created by projecting the map onto a section of a sphere which curves around the user. In all four visualisations the geographic centre can be smoothly adjusted with a standard handheld VR controller and the user, through a head-tracked headset, can physically move around the visualisation. For distance comparison exocentric globe is more accurate than egocentric globe and flat map. For area comparison more time is required with exocentric and egocentric globes than with flat and curved maps. For direction estimation, the exocentric globe is more accurate and faster than the other visual presentations. Our study participants had a weak preference for the exocentric globe. Generally the curved map had benefits over the flat map. In almost all cases the egocentric globe was found to be the least effective visualisation. Overall, our results provide support for the use of exocentric globes for geographic visualisation in mixed-reality.
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    Landscaper: A Modeling System for 3D Printing Scale Models of Landscapes
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Allahverdi, Kamyar; Djavaherpour, Hessam; Mahdavi-Amiri, Ali; Samavati, Faramarz; Jeffrey Heer and Heike Leitte and Timo Ropinski
    Landscape models of geospatial regions provide an intuitive mechanism for exploring complex geospatial information. However, the methods currently used to create these scale models require a large amount of resources, which restricts the availability of these models to a limited number of popular public places, such as museums and airports. In this paper, we have proposed a system for creating these physical models using an affordable 3D printer in order to make the creation of these models more widely accessible. Our system retrieves GIS relevant to creating a physical model of a geospatial region and then addresses the two major limitations of affordable 3D printers, namely the limited number of materials and available printing volume. This is accomplished by separating features into distinct extruded layers and splitting large models into smaller pieces, allowing us to employ different methods for the visualization of different geospatial features, like vegetation and residential areas, in a 3D printing context. We confirm the functionality of our system by printing two large physical models of relatively complex landscape regions.
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    CFGExplorer: Designing a Visual Control Flow Analytics System around Basic Program Analysis Operations
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Devkota, Sabin; Isaacs, Katherine E.; Jeffrey Heer and Heike Leitte and Timo Ropinski
    To develop new compilation and optimization techniques, computer scientists frequently consult program analysis artifacts such as control flow graphs (CFGs) and traces of executed instructions. A CFG is a directed graph representing possible execution paths in a program. CFGs are commonly visualized as node-link diagrams while traces are commonly viewed in raw text format. Visualizing and exploring CFGs and traces is challenging because of the complexity and specificity of the operations researchers perform. We present a design study where we collaborate with computer scientists researching dynamic binary analysis and compilation techniques. The research group primarily employs CFGs and traces to reason about and develop new algorithms for program optimization and parallelization. Through questionnaires, interviews, and a year-long observation, we analyzed their use of visualization, noting that the tasks they perform match common subroutines they employ in their techniques. Based on this task analysis, we designed CFGExplorer, a visual analytics system that supports computer scientists with interactions that are integrated with the program structure. We developed a domain-specific graph modification to generate graph layouts that reflect program structure. CFGExplorer incorporates structures such as functions and loops, and uses the correspondence between CFGs and traces to support navigation. We further augment the system to highlight the output of program analysis techniques, facilitating exploration at a higher level. We evaluate the tool through guided sessions and semi-structured interviews as well as deployment. Our collaborators have integrated CFGExplorer into their workflow and use it to reason about programs, develop and debug new algorithms, and share their findings.
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    Illustrative Multivariate Visualization for Geological Modelling
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Rocha, Allan; Mota, Roberta Cabral Ramos; Hamdi, Hamidreza; Alim, Usman R.; Sousa, Mario Costa; Jeffrey Heer and Heike Leitte and Timo Ropinski
    In this paper, we present a novel illustrative multivariate visualization for geological modelling to assist geologists and reservoir engineers in visualizing multivariate datasets in superimposed representations, in contrast to the single-attribute visualizations supported by commercial software. Our approach extends the use of decals from a single surface to 3D irregular grids, using the layering concept to represent multiple attributes. We also build upon prior work to augment the design and implementation of different geological attributes (namely, rock type, porosity, and permeability). More specifically, we propose a new sampling strategy to generate decals for porosity on the geological grid, a hybrid visualization for permeability which combines 2D decals and 3D ellipsoid glyphs, and a perceptually-based design that allows us to visualize additional attributes (e.g., oil saturation) while avoiding visual interference between layers. Furthermore, our visual design draws from traditional geological illustrations, facilitating the understanding and communication between interdisciplinary teams. An evaluation by domain experts highlights the potential of our approach for geological modelling and interpretation in this complex domain.
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    Hunting High and Low: Visualising Shifting Correlations in Financial Markets
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Simon, Peter M.; Turkay, Cagatay; Jeffrey Heer and Heike Leitte and Timo Ropinski
    The analysis of financial assets' correlations is fundamental to many aspects of finance theory and practice, especially modern portfolio theory and the study of risk. In order to manage investment risk, in-depth analysis of changing correlations is needed, with both high and low correlations between financial assets (and groups thereof) important to identify. In this paper, we propose a visual analytics framework for the interactive analysis of relations and structures in dynamic, high-dimensional correlation data. We conduct a series of interviews and review the financial correlation analysis literature to guide our design. Our solution combines concepts from multi-dimensional scaling, weighted complete graphs and threshold networks to present interactive, animated displays which use proximity as a visual metaphor for correlation and animation stability to encode correlation stability. We devise interaction techniques coupled with context-sensitive auxiliary views to support the analysis of subsets of correlation networks. As part of our contribution, we also present behaviour profiles to help guide future users of our approach. We evaluate our approach by checking the validity of the layouts produced, presenting a number of analysis stories, and through a user study. We observe that our solutions help unravel complex behaviours and resonate well with study participants in addressing their needs in the context of correlation analysis in finance.
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    Baseball Timeline: Summarizing Baseball Plays Into a Static Visualization
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Ono, Jorge H. Piazentin; Dietrich, Carlos; Silva, Claudio T.; Jeffrey Heer and Heike Leitte and Timo Ropinski
    In sports, Play Diagrams are the standard way to represent and convey information. They are widely used by coaches, managers, journalists and fans in general. There are situations where diagrams may be hard to understand, for example, when several actions are packed in a certain region of the field or there are just too many actions to be transformed in a clear depiction of the play. The representation of how actions develop through time, in particular, may be hardly achieved on such diagrams. The time, and the relationship among the actions of the players through time, is critical on the depiction of complex plays. In this context, we present a study on how player actions may be clearly depicted on 2D diagrams. The study is focused on Baseball plays, a sport where diagrams are heavily used to summarize the actions of the players. We propose a new and simple approach to represent spatiotemporal information in the form of a timeline. We designed our visualization with a requirement driven approach, conducting interviews and fulfilling the needs of baseball experts and expert-fans. We validate our approach by presenting a detailed analysis of baseball plays and conducting interviews with four domain experts.
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    Cosine-Weighted B-Spline Interpolation on the Face-Centered Cubic Lattice
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Rácz, Gergely Ferenc; Csébfalvi, Balázs; Jeffrey Heer and Heike Leitte and Timo Ropinski
    Cosine-Weighted B-spline (CWB) interpolation [Csé13] has been originally proposed for volumetric data sampled on the Body-Centered Cubic (BCC) lattice. The BCC lattice is well known to be optimal for sampling isotropically band-limited signals above the Nyquist limit. However, the Face-Centered Cubic (FCC) lattice has been recently proven to be optimal for low-rate sampling. The CWB interpolation is a state-of-the-art technique on the BCC lattice, which outperforms, for example, the previously proposed box-spline interpolation in terms of both efficiency and visual quality. In this paper, we show that CWB interpolation can be adapted to the FCC lattice as well, and results in similarly isotropic signal reconstructions as on the BCC lattice.
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    Rendering and Extracting Extremal Features in 3D Fields
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Kindlmann, Gordon L.; Chiw, Charisee; Huynh, Tri; Gyulassy, Attila; Reppy, John; Bremer, Peer-Timo; Jeffrey Heer and Heike Leitte and Timo Ropinski
    Visualizing and extracting three-dimensional features is important for many computational science applications, each with their own feature definitions and data types. While some are simple to state and implement (e.g. isosurfaces), others require more complicated mathematics (e.g. multiple derivatives, curvature, eigenvectors, etc.). Correctly implementing mathematical definitions is difficult, so experimenting with new features requires substantial investments. Furthermore, traditional interpolants rarely support the necessary derivatives, and approximations can reduce numerical stability. Our new approach directly translates mathematical notation into practical visualization and feature extraction, with minimal mental and implementation overhead. Using a mathematically expressive domain-specific language, Diderot, we compute direct volume renderings and particlebased feature samplings for a range of mathematical features. Non-expert users can experiment with feature definitions without any exposure to meshes, interpolants, derivative computation, etc. We demonstrate high-quality results on notoriously difficult features, such as ridges and vortex cores, using working code simple enough to be presented in its entirety.
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    Spatio-Temporal Contours from Deep Volume Raycasting
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Frey, Steffen; Jeffrey Heer and Heike Leitte and Timo Ropinski
    We visualize contours for spatio-temporal processes to indicate where and when non-continuous changes occur or spatial bounds are encountered. All time steps are comprised densely in one visualization, with contours allowing to efficiently analyze processes in the data even in case of spatial or temporal overlap. Contours are determined on the basis of deep raycasting that collects samples across time and depth along each ray. For each sample along a ray, its closest neighbors from adjacent rays are identified, considering time, depth, and value in the process. Large distances are represented as contours in image space, using color to indicate temporal occurrence. This contour representation can easily be combined with volume rendering-based techniques, providing both full spatial detail for individual time steps and an outline of the whole time series in one view. Our view-dependent technique supports efficient progressive computation, and requires no prior assumptions regarding the shape or nature of processes in the data. We discuss and demonstrate the performance and utility of our approach via a variety of data sets, comparison and combination with an alternative technique, and feedback by a domain scientist.
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    SetCoLa: High-Level Constraints for Graph Layout
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Hoffswell, Jane; Borning, Alan; Heer, Jeffrey; Jeffrey Heer and Heike Leitte and Timo Ropinski
    Constraints enable flexible graph layout by combining the ease of automatic layout with customizations for a particular domain. However, constraint-based layout often requires many individual constraints defined over specific nodes and node pairs. In addition to the effort of writing and maintaining a large number of similar constraints, such constraints are specific to the particular graph and thus cannot generalize to other graphs in the same domain. To facilitate the specification of customized and generalizable constraint layouts, we contribute SetCoLa: a domain-specific language for specifying high-level constraints relative to properties of the backing data. Users identify node sets based on data or graph properties and apply high-level constraints within each set. Applying constraints to node sets rather than individual nodes reduces specification effort and facilitates reapplication of customized layouts across distinct graphs. We demonstrate the conciseness, generalizability, and expressiveness of SetCoLa on a series of real-world examples from ecological networks, biological systems, and social networks.
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    Multiscale Visualization and Exploration of Large Bipartite Graphs
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Pezzotti, Nicola; Fekete, Jean-Daniel; Höllt, Thomas; Lelieveldt, Boudewijn P. F.; Eisemann, Elmar; Vilanova, Anna; Jeffrey Heer and Heike Leitte and Timo Ropinski
    A bipartite graph is a powerful abstraction for modeling relationships between two collections. Visualizations of bipartite graphs allow users to understand the mutual relationships between the elements in the two collections, e.g., by identifying clusters of similarly connected elements. However, commonly-used visual representations do not scale for the analysis of large bipartite graphs containing tens of millions of vertices, often resorting to an a-priori clustering of the sets. To address this issue, we present the Who's-Active-On-What-Visualization (WAOW-Vis) that allows for multiscale exploration of a bipartite socialnetwork without imposing an a-priori clustering. To this end, we propose to treat a bipartite graph as a high-dimensional space and we create the WAOW-Vis adapting the multiscale dimensionality-reduction technique HSNE. The application of HSNE for bipartite graph requires several modifications that form the contributions of this work. Given the nature of the problem, a set-based similarity is proposed. For efficient and scalable computations, we use compressed bitmaps to represent sets and we present a novel space partitioning tree to efficiently compute similarities; the Sets Intersection Tree. Finally, we validate WAOWVis on several datasets connecting Twitter-users and -streams in different domains: news, computer science and politics. We show how WAOW-Vis is particularly effective in identifying hierarchies of communities among social-media users.
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    Interactive Investigation of Traffic Congestion on Fat-Tree Networks Using TREESCOPE
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Bhatia, Harsh; Jain, Nikhil; Bhatele, Abhinav; Livnat, Yarden; Domke, Jens; Pascucci, Valerio; Bremer, Peer-Timo; Jeffrey Heer and Heike Leitte and Timo Ropinski
    Parallel simulation codes often suffer from performance bottlenecks due to network congestion, leaving millions of dollars of investments underutilized. Given a network topology, it is critical to understand how different applications, job placements, routing schemes, etc., are affected by and contribute to network congestion, especially for large and complex networks. Understanding and optimizing communication on large-scale networks is an active area of research. Domain experts often use exploratory tools to develop both intuitive and formal metrics for network health and performance. This paper presents TREESCOPE, an interactive, web-based visualization tool for exploring network traffic on large-scale fat-tree networks. TREESCOPE encodes the network topology using a tailored matrix-based representation and provides detailed visualization of all traffic in the network. We report on the design process of TREESCOPE, which has been received positively by network researchers as well as system administrators. Through case studies of real and simulated data, we demonstrate how TREESCOPE's visual design and interactive support for complex queries on network traffic can provide experts with new insights into the occurrences and causes of congestion in the network.