39-Issue 3

Permanent URI for this collection

EuroVis 2020 - 22nd EG/VGTC Conference on Visualization
Norrköping, Sweden, May 25-29, 2020 (Virtual)
Volumes
CPU Ray Tracing of Tree-Based Adaptive Mesh Refinement Data
Feng Wang, Nathan Marshak, Will Usher, Carsten Burstedde, Aaron Knoll, Timo Heister, and Chris R. Johnson
Knowledge-Assisted Comparative Assessment of Breast Cancer using Dynamic Contrast-Enhanced Magnetic Resonance Imaging
Kai Nie, Pascal Baltzer, Bernhard Preim, and Gabriel Mistelbauer
Hairy Slices II: Depth Cues for Visualizing 3D Streamlines Through Cutting Planes
Andrew H. Stevens, Colin Ware, Thomas Butkiewicz, David Rogers, and Greg Abram
Representative Isovalue Detection and Isosurface Segmentation Using Novel Isosurface Measures
Cuilan Wang
Visualization Applications and Machine Learning
DRLViz: Understanding Decisions and Memory in Deep Reinforcement Learning
Theo Jaunet, Romain Vuillemot, and Christian Wolf
MotionGlyphs: Visual Abstraction of Spatio-Temporal Networks in Collective Animal Behavior
Eren Cakmak, Hanna Schäfer, Juri Buchmüller, Johannes Fuchs, Tobias Schreck, Alex Jordan, and Daniel A. Keim
Reading Traces: Scalable Exploration in Elastic Visualizations of Cultural Heritage Data
Mark-Jan Bludau, Viktoria Brüggemann, Anna Busch, and Marian Dörk
Bombalytics: Visualization of Competition and Collaboration Strategies of Players in a Bomb Laying Game
Shivam Agarwal, Günter Wallner, and Fabian Beck
Applications
VA-TRAC: Geospatial Trajectory Analysis for Monitoring, Identification, and Verification in Fishing Vessel Operations
Syver Storm-Furru and Stefan Bruckner
Orchard: Exploring Multivariate Heterogeneous Networks on Mobile Phones
Philipp Eichmann, Darren Edge, Nathan Evans, Bongshin Lee, Matthew Brehmer, and Christopher White
Ocupado: Visualizing Location-Based Counts Over Time Across Buildings
Michael Oppermann and Tamara Munzner
A Visual Analytics Approach to Facilitate Crime Hotspot Analysis
José F. de Queiroz Neto, Emanuele Santos, Creto Augusto Vidal, and David S. Ebert
Machine Learning
QUESTO: Interactive Construction of Objective Functions for Classification Tasks
Subhajit Das, Shenyu Xu, Michael Gleicher, Remco Chang, and Alex Endert
PEAX: Interactive Visual Pattern Search in Sequential Data Using Unsupervised Deep Representation Learning [Best Paper Award]
Fritz Lekschas, Brant Peterson, Daniel Haehn, Eric Ma, Nils Gehlenborg, and Hanspeter Pfister
Boxer: Interactive Comparison of Classifier Results
Michael Gleicher, Aditya Barve, Xinyi Yu, and Florian Heimerl
Classifier-Guided Visual Correction of Noisy Labels for Image Classification Tasks
Alex Bäuerle, Heiko Neumann, and Timo Ropinski
User-Centered Visual Design and Interaction
Understanding the Design Space and Authoring Paradigms for Animated Data Graphics
John R. Thompson, Zhicheng Liu, Wilmot Li, and John Stasko
VisuaLint: Sketchy In Situ Annotations of Chart Construction Errors
Aspen K. Hopkins, Michael Correll, and Arvind Satyanarayan
Many At Once: Capturing Intentions to Create And Use Many Views At Once In Large Display Environments
Jillian Aurisano, Abhinav Kumar, Abeer Alsaiari, Barbara Di Eugenio, and Andrew E. Johnson
Dimension Reduction and Projections
Quantitative Evaluation of Time-Dependent Multidimensional Projection Techniques
Eduardo Faccin Vernier, Rafael Garcia, Iron Prando da Silva, João L. D. Comba, and Alexandru C. Telea
Phase Space Projection of Dynamical Systems [Honorable Mentions]
Nemanja Bartolovic, Markus Gross, and Tobias Günther
Interaction and Storytelling
Short-Contact Touch-Manipulation of Scatterplot Matrices on Wall Displays
Patrick Riehmann, Gabriela Molina León, Joshua Reibert, Florian Echtler, and Bernd Froehlich
Structure and Empathy in Visual Data Storytelling: Evaluating their Influence on Attitude
Johannes Liem, Charles Perin, and Jo Wood
Co-creating Visualizations: A First Evaluation with Social Science Researchers
Gabriela Molina León and Andreas Breiter
Topology
Extraction of Distinguished Hyperbolic Trajectories for 2D Time-Dependent Vector Field Topology
Lutz Hofmann and Filip Sadlo
Fiber Surfaces for many Variables
Christian Blecha, Felix Raith, Arne Jonas Präger, Thomas Nagel, Olaf Kolditz, Jobst Maßmann, Niklas Röber, Michael Böttinger, and Gerik Scheuermann
Visual Analysis of the Finite-Time Lyapunov Exponent
Antoni Sagristà, Stefan Jordan, and Filip Sadlo
Fuzzy Contour Trees: Alignment and Joint Layout of Multiple Contour Trees
Anna-Pia Lohfink, Florian Wetzels, Jonas Lukasczyk, Gunther H. Weber, and Christoph Garth
Networks and Sets
Metro Maps on Octilinear Grid Graphs
Hannah Bast, Patrick Brosi, and Sabine Storandt
Augmenting Node-Link Diagrams with Topographic Attribute Maps
Reinhold Preiner, Johanna Schmidt, Katharina Krösl, Tobias Schreck, and Gabriel Mistelbauer
Set Streams: Visual Exploration of Dynamic Overlapping Sets
Shivam Agarwal and Fabian Beck
Quantitative Comparison of Time-Dependent Treemaps
Eduardo Vernier, Max Sondag, João Comba, Bettina Speckmann, Alexandru Telea, and Kevin Verbeek
Vectors and Tensors
PAVED: Pareto Front Visualization for Engineering Design
Lena Cibulski, Hubert Mitterhofer, Thorsten May, and Jörn Kohlhammer
A Globally Conforming Lattice Structure for 2D Stress Tensor Visualization
Junpeng Wang, Jun Wu, and Rüdiger Westermann
Feature Driven Combination of Animated Vector Field Visualizations
María Jesús Lobo, Alexandru Telea, and Christophe Hurter
Space and Time
LOCALIS: Locally-adaptive Line Simplification for GPU-based Geographic Vector Data Visualization [Honorable Mentions]
Alireza Amiraghdam, Alexandra Diehl, and Renato Pajarola
Data Comets: Designing a Visualization Tool for Analyzing Autonomous Aerial Vehicle Logs with Grounded Evaluation
David Saffo, Aristotelis Leventidis, Twinkle Jain, Michelle A. Borkin, and Cody Dunne
GTMapLens: Interactive Lens for Geo-Text Data Browsing on Map
Chao Ma, Ye Zhao, Shamal AL-Dohuki, Jing Yang, Xinyue Ye, Farah Kamw, and Md Amiruzzaman
Visual Analytics for Problem Solving
WarehouseVis: A Visual Analytics Approach to Facilitating Warehouse Location Selection for Business Districts
Quan Li, Qiangqiang Liu, Chunfeng Tang, Zhiwei Li, Shuaichao Wei, Xianrui Peng, Minghua Zheng, Tianjian Chen, and Qiang Yang
Resolving Conflicting Insights in Asynchronous Collaborative Visual Analysis
Jianping Kelvin Li, Shenyu Xu, Yecong (Chris) Ye, and Kwan-Liu Ma
SeqDynamics: Visual Analytics for Evaluating Online Problem-solving Dynamics
Meng Xia, Min Xu, Chuan-en Lin, Ta Ying Cheng, Huamin Qu, and Xiaojuan Ma
SEEVis: A Smart Emergency Evacuation Plan Visualization System with Data-Driven Shot Designs
Quan Li, Yingjie J. Liu, Li Chen, Xingchao C. Yang, Yi Peng, Xiaoru R. Yuan, and Maddegedara Lalith Lakshman Wijerathne
Multivariate Data Visualization
Evaluating Reordering Strategies for Cluster Identification in Parallel Coordinates
Michael Blumenschein, Xuan Zhang, David Pomerenke, Daniel A. Keim, and Johannes Fuchs
Sunspot Plots: Model-based Structure Enhancement for Dense Scatter Plots
Thomas Trautner, Fabian Bolte, Sergej Stoppel, and Stefan Bruckner
v-plots: Designing Hybrid Charts for the Comparative Analysis of Data Distributions
Michael Blumenschein, Luka J. Debbeler, Nadine C. Lages, Britta Renner, Daniel A. Keim, and Mennatallah El-Assady
Graphs and Charts
Sublinear Time Force Computation for Big Complex Network Visualization
Amyra Meidiana, Seok-Hee Hong, Marnijati Torkel, Shijun Cai, and Peter Eades
Infomages: Embedding Data into Thematic Images [Honorable Mentions]
Darius Coelho and Klaus Mueller
Canis: A High-Level Language for Data-Driven Chart Animations
Tong Ge, Yue Zhao, Bongshin Lee, Donghao Ren, Baoquan Chen, and Yunhai Wang

BibTeX (39-Issue 3)
                
@article{
10.1111:cgf.13958,
journal = {Computer Graphics Forum}, title = {{
CPU Ray Tracing of Tree-Based Adaptive Mesh Refinement Data}},
author = {
Wang, Feng
and
Marshak, Nathan
and
Usher, Will
and
Burstedde, Carsten
and
Knoll, Aaron
and
Heister, Timo
and
Johnson, Chris R.
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13958}
}
                
@article{
10.1111:cgf.13959,
journal = {Computer Graphics Forum}, title = {{
Knowledge-Assisted Comparative Assessment of Breast Cancer using Dynamic Contrast-Enhanced Magnetic Resonance Imaging}},
author = {
Nie, Kai
and
Baltzer, Pascal
and
Preim, Bernhard
and
Mistelbauer, Gabriel
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13959}
}
                
@article{
10.1111:cgf.13960,
journal = {Computer Graphics Forum}, title = {{
Hairy Slices II: Depth Cues for Visualizing 3D Streamlines Through Cutting Planes}},
author = {
Stevens, Andrew H.
and
Ware, Colin
and
Butkiewicz, Thomas
and
Rogers, David
and
Abram, Greg
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13960}
}
                
@article{
10.1111:cgf.13961,
journal = {Computer Graphics Forum}, title = {{
Representative Isovalue Detection and Isosurface Segmentation Using Novel Isosurface Measures}},
author = {
Wang, Cuilan
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13961}
}
                
@article{
10.1111:cgf.13963,
journal = {Computer Graphics Forum}, title = {{
MotionGlyphs: Visual Abstraction of Spatio-Temporal Networks in Collective Animal Behavior}},
author = {
Cakmak, Eren
and
Schäfer, Hanna
and
Buchmüller, Juri
and
Fuchs, Johannes
and
Schreck, Tobias
and
Jordan, Alex
and
Keim, Daniel A.
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13963}
}
                
@article{
10.1111:cgf.13962,
journal = {Computer Graphics Forum}, title = {{
DRLViz: Understanding Decisions and Memory in Deep Reinforcement Learning}},
author = {
Jaunet, Theo
and
Vuillemot, Romain
and
Wolf, Christian
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13962}
}
                
@article{
10.1111:cgf.13964,
journal = {Computer Graphics Forum}, title = {{
Reading Traces: Scalable Exploration in Elastic Visualizations of Cultural Heritage Data}},
author = {
Bludau, Mark-Jan
and
Brüggemann, Viktoria
and
Busch, Anna
and
Dörk, Marian
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13964}
}
                
@article{
10.1111:cgf.13965,
journal = {Computer Graphics Forum}, title = {{
Bombalytics: Visualization of Competition and Collaboration Strategies of Players in a Bomb Laying Game}},
author = {
Agarwal, Shivam
and
Wallner, Günter
and
Beck, Fabian
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13965}
}
                
@article{
10.1111:cgf.13966,
journal = {Computer Graphics Forum}, title = {{
VA-TRAC: Geospatial Trajectory Analysis for Monitoring, Identification, and Verification in Fishing Vessel Operations}},
author = {
Storm-Furru, Syver
and
Bruckner, Stefan
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13966}
}
                
@article{
10.1111:cgf.13967,
journal = {Computer Graphics Forum}, title = {{
Orchard: Exploring Multivariate Heterogeneous Networks on Mobile Phones}},
author = {
Eichmann, Philipp
and
Edge, Darren
and
Evans, Nathan
and
Lee, Bongshin
and
Brehmer, Matthew
and
White, Christopher
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13967}
}
                
@article{
10.1111:cgf.13968,
journal = {Computer Graphics Forum}, title = {{
Ocupado: Visualizing Location-Based Counts Over Time Across Buildings}},
author = {
Oppermann, Michael
and
Munzner, Tamara
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13968}
}
                
@article{
10.1111:cgf.13969,
journal = {Computer Graphics Forum}, title = {{
A Visual Analytics Approach to Facilitate Crime Hotspot Analysis}},
author = {
Neto, José F. de Queiroz
and
Santos, Emanuele
and
Vidal, Creto Augusto
and
Ebert, David S.
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13969}
}
                
@article{
10.1111:cgf.13970,
journal = {Computer Graphics Forum}, title = {{
QUESTO: Interactive Construction of Objective Functions for Classification Tasks}},
author = {
Das, Subhajit
and
Xu, Shenyu
and
Gleicher, Michael
and
Chang, Remco
and
Endert, Alex
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13970}
}
                
@article{
10.1111:cgf.13971,
journal = {Computer Graphics Forum}, title = {{
PEAX: Interactive Visual Pattern Search in Sequential Data Using Unsupervised Deep Representation Learning}},
author = {
Lekschas, Fritz
and
Peterson, Brant
and
Haehn, Daniel
and
Ma, Eric
and
Gehlenborg, Nils
and
Pfister, Hanspeter
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13971}
}
                
@article{
10.1111:cgf.13972,
journal = {Computer Graphics Forum}, title = {{
Boxer: Interactive Comparison of Classifier Results}},
author = {
Gleicher, Michael
and
Barve, Aditya
and
Yu, Xinyi
and
Heimerl, Florian
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13972}
}
                
@article{
10.1111:cgf.13973,
journal = {Computer Graphics Forum}, title = {{
Classifier-Guided Visual Correction of Noisy Labels for Image Classification Tasks}},
author = {
Bäuerle, Alex
and
Neumann, Heiko
and
Ropinski, Timo
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13973}
}
                
@article{
10.1111:cgf.13975,
journal = {Computer Graphics Forum}, title = {{
VisuaLint: Sketchy In Situ Annotations of Chart Construction Errors}},
author = {
Hopkins, Aspen K.
and
Correll, Michael
and
Satyanarayan, Arvind
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13975}
}
                
@article{
10.1111:cgf.13974,
journal = {Computer Graphics Forum}, title = {{
Understanding the Design Space and Authoring Paradigms for Animated Data Graphics}},
author = {
Thompson, John R.
and
Liu, Zhicheng
and
Li, Wilmot
and
Stasko, John
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13974}
}
                
@article{
10.1111:cgf.13977,
journal = {Computer Graphics Forum}, title = {{
Quantitative Evaluation of Time-Dependent Multidimensional Projection Techniques}},
author = {
Vernier, Eduardo Faccin
and
Garcia, Rafael
and
Silva, Iron Prando da
and
Comba, João L. D.
and
Telea, Alexandru C.
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13977}
}
                
@article{
10.1111:cgf.13976,
journal = {Computer Graphics Forum}, title = {{
Many At Once: Capturing Intentions to Create And Use Many Views At Once In Large Display Environments}},
author = {
Aurisano, Jillian
and
Kumar, Abhinav
and
Alsaiari, Abeer
and
Eugenio, Barbara Di
and
Johnson, Andrew E.
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13976}
}
                
@article{
10.1111:cgf.13978,
journal = {Computer Graphics Forum}, title = {{
Phase Space Projection of Dynamical Systems}},
author = {
Bartolovic, Nemanja
and
Gross, Markus
and
Günther, Tobias
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13978}
}
                
@article{
10.1111:cgf.13980,
journal = {Computer Graphics Forum}, title = {{
Structure and Empathy in Visual Data Storytelling: Evaluating their Influence on Attitude}},
author = {
Liem, Johannes
and
Perin, Charles
and
Wood, Jo
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13980}
}
                
@article{
10.1111:cgf.13979,
journal = {Computer Graphics Forum}, title = {{
Short-Contact Touch-Manipulation of Scatterplot Matrices on Wall Displays}},
author = {
Riehmann, Patrick
and
Molina León, Gabriela
and
Reibert, Joshua
and
Echtler, Florian
and
Froehlich, Bernd
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13979}
}
                
@article{
10.1111:cgf.13981,
journal = {Computer Graphics Forum}, title = {{
Co-creating Visualizations: A First Evaluation with Social Science Researchers}},
author = {
Molina León, Gabriela
and
Breiter, Andreas
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13981}
}
                
@article{
10.1111:cgf.13982,
journal = {Computer Graphics Forum}, title = {{
Extraction of Distinguished Hyperbolic Trajectories for 2D Time-Dependent Vector Field Topology}},
author = {
Hofmann, Lutz
and
Sadlo, Filip
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13982}
}
                
@article{
10.1111:cgf.13983,
journal = {Computer Graphics Forum}, title = {{
Fiber Surfaces for many Variables}},
author = {
Blecha, Christian
and
Raith, Felix
and
Präger, Arne Jonas
and
Nagel, Thomas
and
Kolditz, Olaf
and
Maßmann, Jobst
and
Röber, Niklas
and
Böttinger, Michael
and
Scheuermann, Gerik
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13983}
}
                
@article{
10.1111:cgf.13984,
journal = {Computer Graphics Forum}, title = {{
Visual Analysis of the Finite-Time Lyapunov Exponent}},
author = {
Sagristà, Antoni
and
Jordan, Stefan
and
Sadlo, Filip
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13984}
}
                
@article{
10.1111:cgf.13985,
journal = {Computer Graphics Forum}, title = {{
Fuzzy Contour Trees: Alignment and Joint Layout of Multiple Contour Trees}},
author = {
Lohfink, Anna-Pia
and
Wetzels, Florian
and
Lukasczyk, Jonas
and
Weber, Gunther H.
and
Garth, Christoph
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13985}
}
                
@article{
10.1111:cgf.13986,
journal = {Computer Graphics Forum}, title = {{
Metro Maps on Octilinear Grid Graphs}},
author = {
Bast, Hannah
and
Brosi, Patrick
and
Storandt, Sabine
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13986}
}
                
@article{
10.1111:cgf.13987,
journal = {Computer Graphics Forum}, title = {{
Augmenting Node-Link Diagrams with Topographic Attribute Maps}},
author = {
Preiner, Reinhold
and
Schmidt, Johanna
and
Krösl, Katharina
and
Schreck, Tobias
and
Mistelbauer, Gabriel
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13987}
}
                
@article{
10.1111:cgf.13988,
journal = {Computer Graphics Forum}, title = {{
Set Streams: Visual Exploration of Dynamic Overlapping Sets}},
author = {
Agarwal, Shivam
and
Beck, Fabian
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13988}
}
                
@article{
10.1111:cgf.13989,
journal = {Computer Graphics Forum}, title = {{
Quantitative Comparison of Time-Dependent Treemaps}},
author = {
Vernier, Eduardo
and
Sondag, Max
and
Comba, João
and
Speckmann, Bettina
and
Telea, Alexandru
and
Verbeek, Kevin
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13989}
}
                
@article{
10.1111:cgf.13990,
journal = {Computer Graphics Forum}, title = {{
PAVED: Pareto Front Visualization for Engineering Design}},
author = {
Cibulski, Lena
and
Mitterhofer, Hubert
and
May, Thorsten
and
Kohlhammer, Jörn
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13990}
}
                
@article{
10.1111:cgf.13991,
journal = {Computer Graphics Forum}, title = {{
A Globally Conforming Lattice Structure for 2D Stress Tensor Visualization}},
author = {
Wang, Junpeng
and
Wu, Jun
and
Westermann, Rüdiger
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13991}
}
                
@article{
10.1111:cgf.13992,
journal = {Computer Graphics Forum}, title = {{
Feature Driven Combination of Animated Vector Field Visualizations}},
author = {
Lobo, María Jesús
and
Telea, Alexandru
and
Hurter, Christophe
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13992}
}
                
@article{
10.1111:cgf.13993,
journal = {Computer Graphics Forum}, title = {{
LOCALIS: Locally-adaptive Line Simplification for GPU-based Geographic Vector Data Visualization}},
author = {
Amiraghdam, Alireza
and
Diehl, Alexandra
and
Pajarola, Renato
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13993}
}
                
@article{
10.1111:cgf.13995,
journal = {Computer Graphics Forum}, title = {{
GTMapLens: Interactive Lens for Geo-Text Data Browsing on Map}},
author = {
Ma, Chao
and
Zhao, Ye
and
AL-Dohuki, Shamal
and
Yang, Jing
and
Ye, Xinyue
and
Kamw, Farah
and
Amiruzzaman, Md
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13995}
}
                
@article{
10.1111:cgf.13994,
journal = {Computer Graphics Forum}, title = {{
Data Comets: Designing a Visualization Tool for Analyzing Autonomous Aerial Vehicle Logs with Grounded Evaluation}},
author = {
Saffo, David
and
Leventidis, Aristotelis
and
Jain, Twinkle
and
Borkin, Michelle A.
and
Dunne, Cody
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13994}
}
                
@article{
10.1111:cgf.13997,
journal = {Computer Graphics Forum}, title = {{
Resolving Conflicting Insights in Asynchronous Collaborative Visual Analysis}},
author = {
Li, Jianping Kelvin
and
Xu, Shenyu
and
Ye, Yecong (Chris)
and
Ma, Kwan-Liu
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13997}
}
                
@article{
10.1111:cgf.13996,
journal = {Computer Graphics Forum}, title = {{
WarehouseVis: A Visual Analytics Approach to Facilitating Warehouse Location Selection for Business Districts}},
author = {
Li, Quan
and
Liu, Qiangqiang
and
Tang, Chunfeng
and
Li, Zhiwei
and
Wei, Shuaichao
and
Peng, Xianrui
and
Zheng, Minghua
and
Chen, Tianjian
and
Yang, Qiang
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13996}
}
                
@article{
10.1111:cgf.13998,
journal = {Computer Graphics Forum}, title = {{
SeqDynamics: Visual Analytics for Evaluating Online Problem-solving Dynamics}},
author = {
Xia, Meng
and
Xu, Min
and
Lin, Chuan-en
and
Cheng, Ta Ying
and
Qu, Huamin
and
Ma, Xiaojuan
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13998}
}
                
@article{
10.1111:cgf.13999,
journal = {Computer Graphics Forum}, title = {{
SEEVis: A Smart Emergency Evacuation Plan Visualization System with Data-Driven Shot Designs}},
author = {
Li, Quan
and
Liu, Yingjie J.
and
Chen, Li
and
Yang, Xingchao C.
and
Peng, Yi
and
Yuan, Xiaoru R.
and
Wijerathne, Maddegedara Lalith Lakshman
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13999}
}
                
@article{
10.1111:cgf.14000,
journal = {Computer Graphics Forum}, title = {{
Evaluating Reordering Strategies for Cluster Identification in Parallel Coordinates}},
author = {
Blumenschein, Michael
and
Zhang, Xuan
and
Pomerenke, David
and
Keim, Daniel A.
and
Fuchs, Johannes
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.14000}
}
                
@article{
10.1111:cgf.14001,
journal = {Computer Graphics Forum}, title = {{
Sunspot Plots: Model-based Structure Enhancement for Dense Scatter Plots}},
author = {
Trautner, Thomas
and
Bolte, Fabian
and
Stoppel, Sergej
and
Bruckner, Stefan
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.14001}
}
                
@article{
10.1111:cgf.14002,
journal = {Computer Graphics Forum}, title = {{
v-plots: Designing Hybrid Charts for the Comparative Analysis of Data Distributions}},
author = {
Blumenschein, Michael
and
Debbeler, Luka J.
and
Lages, Nadine C.
and
Renner, Britta
and
Keim, Daniel A.
and
El-Assady, Mennatallah
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.14002}
}
                
@article{
10.1111:cgf.14003,
journal = {Computer Graphics Forum}, title = {{
Sublinear Time Force Computation for Big Complex Network Visualization}},
author = {
Meidiana, Amyra
and
Hong, Seok-Hee
and
Torkel, Marnijati
and
Cai, Shijun
and
Eades, Peter
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.14003}
}
                
@article{
10.1111:cgf.14004,
journal = {Computer Graphics Forum}, title = {{
Infomages: Embedding Data into Thematic Images}},
author = {
Coelho, Darius
and
Mueller, Klaus
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.14004}
}
                
@article{
10.1111:cgf.14005,
journal = {Computer Graphics Forum}, title = {{
Canis: A High-Level Language for Data-Driven Chart Animations}},
author = {
Ge, Tong
and
Zhao, Yue
and
Lee, Bongshin
and
Ren, Donghao
and
Chen, Baoquan
and
Wang, Yunhai
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.14005}
}

Browse

Recent Submissions

Now showing 1 - 49 of 49
  • Item
    EuroVis 2020 CGF 39-3: Frontmatter
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Gleicher, Michael; Viola, Ivan; Landesberger von Antburg, Tatiana; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
  • Item
    CPU Ray Tracing of Tree-Based Adaptive Mesh Refinement Data
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Wang, Feng; Marshak, Nathan; Usher, Will; Burstedde, Carsten; Knoll, Aaron; Heister, Timo; Johnson, Chris R.; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Adaptive mesh refinement (AMR) techniques allow for representing a simulation's computation domain in an adaptive fashion. Although these techniques have found widespread adoption in high-performance computing simulations, visualizing their data output interactively and without cracks or artifacts remains challenging. In this paper, we present an efficient solution for direct volume rendering and hybrid implicit isosurface ray tracing of tree-based AMR (TB-AMR) data. We propose a novel reconstruction strategy, Generalized Trilinear Interpolation (GTI), to interpolate across AMR level boundaries without cracks or discontinuities in the surface normal. We employ a general sparse octree structure supporting a wide range of AMR data, and use it to accelerate volume rendering, hybrid implicit isosurface rendering and value queries. We demonstrate that our approach achieves artifact-free isosurface and volume rendering and provides higher quality output images compared to existing methods at interactive rendering rates.
  • Item
    Knowledge-Assisted Comparative Assessment of Breast Cancer using Dynamic Contrast-Enhanced Magnetic Resonance Imaging
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Nie, Kai; Baltzer, Pascal; Preim, Bernhard; Mistelbauer, Gabriel; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Breast perfusion data are dynamic medical image data that depict perfusion characteristics of the investigated tissue. These data consist of a series of static datasets that are acquired at different time points and aggregated into time intensity curves (TICs) for each voxel. The characteristics of these TICs provide important information about a lesion's composition, but their analysis is time-consuming due to their large number. Subsequently, these TICs are used to classify a lesion as benign or malignant. This lesion scoring is commonly done manually by physicians and may therefore be subject to bias. We propose an approach that addresses both of these problems by combining an automated lesion classification with a visual confirmatory analysis, especially for uncertain cases. Firstly, we cluster the TICs of a lesion using ordering points to identify the clustering structure (OPTICS) and then visualize these clusters. Together with their relative size, they are added to a library. We then model fuzzy inference rules by using the lesion's TIC clusters as antecedents and its score as consequent. Using a fuzzy scoring system, we can suggest a score for a new lesion. Secondly, to allow physicians to confirm the suggestion in uncertain cases, we display the TIC clusters together with their spatial distribution and allow them to compare two lesions side by side. With our knowledge-assisted comparative visual analysis, physicians can explore and classify breast lesions. The true positive prediction accuracy of our scoring system achieved 71.4% in one-fold cross-validation using 14 lesions.
  • Item
    Hairy Slices II: Depth Cues for Visualizing 3D Streamlines Through Cutting Planes
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Stevens, Andrew H.; Ware, Colin; Butkiewicz, Thomas; Rogers, David; Abram, Greg; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Visualizing 3D vector fields is challenging because of occlusion problems and the difficulty of providing depth cues that adequately support the perception of direction of flow lines in 3D space. One of the depth cues that has proven most valuable for the perception of other kinds of 3D data, notably 3D networks and 3D point clouds, is structure-from-motion (also called the Kinetic Depth Effect); another powerful depth cue is stereoscopic viewing. We carried out an experiment of the perception of direction for short streamlines passing through a cutting plane. The conditions included viewing with and without structurefrom- motion and with and without stereoscopic depth. Conditions also include comparing streamtubes to lines. The results show that for this particular task, stereo provided an effective depth cue, but structure-from-motion did not. Ringed streamtubes and streamcones provided good 3D direction information, even without stereoscopic viewing. We conclude with guidelines for viewing slices through vector fields.
  • Item
    Representative Isovalue Detection and Isosurface Segmentation Using Novel Isosurface Measures
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Wang, Cuilan; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Interval volume is the volume of the region between two isosurfaces. This paper proposes a novel measure, called VOA measure, that is computed based on interval volume and isosurface area. This measure represents the rate of change of distance between isosurfaces with respect to isovalue. It can be used to detect representative isovalues of the dataset since two isosurfaces near material boundaries tend to be much closer to each other than two isosurfaces in material interiors, assuming they have the same isovalue difference. For the same isosurface, some portion of it may pass through the boundary of two materials and some portion of it may pass through the interior of a material. To separate the portions of an isosurface that represent different features of the dataset, another novel isosurface measure is introduced. This measure is calculated based on the Euclidean distance of individual sample points on two isosurfaces. The effectiveness of the two new measures in detecting significant isovalues and segmenting isosurfaces are demonstrated in the paper.
  • Item
    MotionGlyphs: Visual Abstraction of Spatio-Temporal Networks in Collective Animal Behavior
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Cakmak, Eren; Schäfer, Hanna; Buchmüller, Juri; Fuchs, Johannes; Schreck, Tobias; Jordan, Alex; Keim, Daniel A.; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Domain experts for collective animal behavior analyze relationships between single animal movers and groups of animals over time and space to detect emergent group properties. A common way to interpret this type of data is to visualize it as a spatio-temporal network. Collective behavior data sets are often large, and may hence result in dense and highly connected node-link diagrams, resulting in issues of node-overlap and edge clutter. In this design study, in an iterative design process, we developed glyphs as a design for seamlessly encoding relationships and movement characteristics of a single mover or clusters of movers. Based on these glyph designs, we developed a visual exploration prototype, MotionGlyphs, that supports domain experts in interactively filtering, clustering, and animating spatio-temporal networks for collective animal behavior analysis. By means of an expert evaluation, we show how MotionGlyphs supports important tasks and analysis goals of our domain experts, and we give evidence of the usefulness for analyzing spatio-temporal networks of collective animal behavior.
  • Item
    DRLViz: Understanding Decisions and Memory in Deep Reinforcement Learning
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Jaunet, Theo; Vuillemot, Romain; Wolf, Christian; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    We present DRLViz, a visual analytics interface to interpret the internal memory of an agent (e.g. a robot) trained using deep reinforcement learning. This memory is composed of large temporal vectors updated when the agent moves in an environment and is not trivial to understand due to the number of dimensions, dependencies to past vectors, spatial/temporal correlations, and co-correlation between dimensions. It is often referred to as a black box as only inputs (images) and outputs (actions) are intelligible for humans. Using DRLViz, experts are assisted to interpret decisions using memory reduction interactions, and to investigate the role of parts of the memory when errors have been made (e.g. wrong direction). We report on DRLViz applied in the context of video games simulators (ViZDoom) for a navigation scenario with item gathering tasks. We also report on experts evaluation using DRLViz, and applicability of DRLViz to other scenarios and navigation problems beyond simulation games, as well as its contribution to black box models interpretability and explain-ability in the field of visual analytics.
  • Item
    Reading Traces: Scalable Exploration in Elastic Visualizations of Cultural Heritage Data
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Bludau, Mark-Jan; Brüggemann, Viktoria; Busch, Anna; Dörk, Marian; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Through a design study, we develop an approach to data exploration that utilizes elastic visualizations designed to support varying degrees of detail and abstraction. Examining the notions of scalability and elasticity in interactive visualizations, we introduce a visualization of personal reading traces such as marginalia or markings inside the reference library of German realist author Theodor Fontane. To explore such a rich and extensive collection, meaningful visual forms of abstraction and detail are as important as the transitions between those states. Following a growing research interest in the role of fluid interactivity and animations between views, we are particularly interested in the potential of carefully designed transitions and consistent representations across scales. The resulting prototype addresses humanistic research questions about the interplay of distant and close reading with visualization research on continuous navigation along several granularity levels, using scrolling as one of the main interaction mechanisms. In addition to presenting the design process and resulting prototype, we present findings from a qualitative evaluation of the tool, which suggest that bridging between distant and close views can enhance exploration, but that transitions between views need to be crafted very carefully to facilitate comprehension.
  • Item
    Bombalytics: Visualization of Competition and Collaboration Strategies of Players in a Bomb Laying Game
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Agarwal, Shivam; Wallner, Günter; Beck, Fabian; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Competition and collaboration form complex interaction patterns between the agents and objects involved. Only by understanding these interaction patterns, we can reveal the strategies the participating parties applied. In this paper, we study such competition and collaboration behavior for a computer game. Serving as a testbed for artificial intelligence, the multiplayer bomb laying game Pommerman provides a rich source of advanced behavior of computer agents. We propose a visualization approach that shows an overview of multiple games, with a detailed timeline-based visualization for exploring the specifics of each game. Since an analyst can only fully understand the data when considering the direct and indirect interactions between agents, we suggest various visual encodings of these interactions. Based on feedback from expert users and an application example, we demonstrate that the approach helps identify central competition strategies and provides insights on collaboration.
  • Item
    VA-TRAC: Geospatial Trajectory Analysis for Monitoring, Identification, and Verification in Fishing Vessel Operations
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Storm-Furru, Syver; Bruckner, Stefan; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    In order to ensure sustainability, fishing operations are governed by many rules and regulations that restrict the use of certain techniques and equipment, specify the species and size of fish that can be harvested, and regulate commercial activities based on licensing schemes. As the world's second largest exporter of fish and seafood products, Norway invests a significant amount of effort into maintaining natural ecosystem dynamics by ensuring compliance with its constantly evolving sciencebased regulatory body. This paper introduces VA-TRAC, a geovisual analytics application developed in collaboration with the Norwegian Directorate of Fisheries in order to address this complex task. Our approach uses automatic methods to identify possible catch operations based on fishing vessel trajectories, embedded in an interactive web-based visual interface used to explore the results, compare them with licensing information, and incorporate the analysts' domain knowledge into the decision making process. We present a data and task analysis based on a close collaboration with domain experts, and the design and implementation of VA-TRAC to address the identified requirements.
  • Item
    Orchard: Exploring Multivariate Heterogeneous Networks on Mobile Phones
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Eichmann, Philipp; Edge, Darren; Evans, Nathan; Lee, Bongshin; Brehmer, Matthew; White, Christopher; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    People are becoming increasingly sophisticated in their ability to navigate information spaces using search, hyperlinks, and visualization. But, mobile phones preclude the use of multiple coordinated views that have proven effective in the desktop environment (e.g., for business intelligence or visual analytics). In this work, we propose to model information as multivariate heterogeneous networks to enable greater analytic expression for a range of sensemaking tasks while suggesting a new, list-based paradigm with gestural navigation of structured information spaces on mobile phones. We also present a mobile application, called Orchard, which combines ideas from both faceted search and interactive network exploration in a visual query language to allow users to collect facets of interest during exploratory navigation. Our study showed that users could collect and combine these facets with Orchard, specifying network queries and projections that would only have been possible previously using complex data tools or custom data science.
  • Item
    Ocupado: Visualizing Location-Based Counts Over Time Across Buildings
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Oppermann, Michael; Munzner, Tamara; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Understanding how spaces in buildings are being used is vital for optimizing space utilization, for improving resource allocation, and for the design of new facilities. We present a multi-year design study that resulted in Ocupado, a set of visual decision-support tools centered around occupancy data for stakeholders in facilities management and planning. Ocupado uses WiFi devices as a proxy for human presence, capturing location-based counts that preserve privacy without trajectories. We contribute data and task abstractions for studying space utilization for combinations of data granularities in both space and time. In addition, we contribute generalizable design choices for visualizing location-based counts relating to indoor environments. We provide evidence of Ocupado's utility through multiple analysis scenarios with real-world data refined through extensive stakeholder feedback, and discussion of its take-up by our industry partner.
  • Item
    A Visual Analytics Approach to Facilitate Crime Hotspot Analysis
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Neto, José F. de Queiroz; Santos, Emanuele; Vidal, Creto Augusto; Ebert, David S.; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Computer-based technology has played a significant role in crime prevention over the past 30 years, especially with the popularization of spatial databases and crime mapping systems. Police departments frequently use hotspot analysis to identify regions that should be a priority in receiving preventive resources. Practitioners and researchers agree that tracking crime over time and identifying its geographic patterns are vital information for planning efficiently. Frequently, police departments have access to systems that are too complicated and excessively technical, leading to modest usage. By working closely together with domain experts from police agencies of two different countries, we identified and characterized five domain tasks inherent to the hotspot analysis problem and developed SHOC, a visualization tool that strives for simplicity and ease of use in helping users to perform all the domain tasks. SHOC is included in a visual analytics system that allows users without technical expertise to annotate, save, and share analyses. We also demonstrate that our system effectively supports the completion of the domain tasks in two different real-world case studies.
  • Item
    QUESTO: Interactive Construction of Objective Functions for Classification Tasks
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Das, Subhajit; Xu, Shenyu; Gleicher, Michael; Chang, Remco; Endert, Alex; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Building effective classifiers requires providing the modeling algorithms with information about the training data and modeling goals in order to create a model that makes proper tradeoffs. Machine learning algorithms allow for flexible specification of such meta-information through the design of the objective functions that they solve. However, such objective functions are hard for users to specify as they are a specific mathematical formulation of their intents. In this paper, we present an approach that allows users to generate objective functions for classification problems through an interactive visual interface. Our approach adopts a semantic interaction design in that user interactions over data elements in the visualization are translated into objective function terms. The generated objective functions are solved by a machine learning solver that provides candidate models, which can be inspected by the user, and used to suggest refinements to the specifications. We demonstrate a visual analytics system QUESTO for users to manipulate objective functions to define domain-specific constraints. Through a user study we show that QUESTO helps users create various objective functions that satisfy their goals.
  • Item
    PEAX: Interactive Visual Pattern Search in Sequential Data Using Unsupervised Deep Representation Learning
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Lekschas, Fritz; Peterson, Brant; Haehn, Daniel; Ma, Eric; Gehlenborg, Nils; Pfister, Hanspeter; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    We present PEAX, a novel feature-based technique for interactive visual pattern search in sequential data, like time series or data mapped to a genome sequence. Visually searching for patterns by similarity is often challenging because of the large search space, the visual complexity of patterns, and the user's perception of similarity. For example, in genomics, researchers try to link patterns in multivariate sequential data to cellular or pathogenic processes, but a lack of ground truth and high variance makes automatic pattern detection unreliable. We have developed a convolutional autoencoder for unsupervised representation learning of regions in sequential data that can capture more visual details of complex patterns compared to existing similarity measures. Using this learned representation as features of the sequential data, our accompanying visual query system enables interactive feedback-driven adjustments of the pattern search to adapt to the users' perceived similarity. Using an active learning sampling strategy, PEAX collects user-generated binary relevance feedback. This feedback is used to train a model for binary classification, to ultimately find other regions that exhibit patterns similar to the search target. We demonstrate PEAX's features through a case study in genomics and report on a user study with eight domain experts to assess the usability and usefulness of PEAX. Moreover, we evaluate the effectiveness of the learned feature representation for visual similarity search in two additional user studies. We find that our models retrieve significantly more similar patterns than other commonly used techniques.
  • Item
    Boxer: Interactive Comparison of Classifier Results
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Gleicher, Michael; Barve, Aditya; Yu, Xinyi; Heimerl, Florian; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Machine learning practitioners often compare the results of different classifiers to help select, diagnose and tune models. We present Boxer, a system to enable such comparison. Our system facilitates interactive exploration of the experimental results obtained by applying multiple classifiers to a common set of model inputs. The approach focuses on allowing the user to identify interesting subsets of training and testing instances and comparing performance of the classifiers on these subsets. The system couples standard visual designs with set algebra interactions and comparative elements. This allows the user to compose and coordinate views to specify subsets and assess classifier performance on them. The flexibility of these compositions allow the user to address a wide range of scenarios in developing and assessing classifiers. We demonstrate Boxer in use cases including model selection, tuning, fairness assessment, and data quality diagnosis.
  • Item
    Classifier-Guided Visual Correction of Noisy Labels for Image Classification Tasks
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Bäuerle, Alex; Neumann, Heiko; Ropinski, Timo; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Training data plays an essential role in modern applications of machine learning. However, gathering labeled training data is time-consuming. Therefore, labeling is often outsourced to less experienced users, or completely automated. This can introduce errors, which compromise valuable training data, and lead to suboptimal training results. We thus propose a novel approach that uses the power of pretrained classifiers to visually guide users to noisy labels, and let them interactively check error candidates, to iteratively improve the training data set. To systematically investigate training data, we propose a categorization of labeling errors into three different types, based on an analysis of potential pitfalls in label acquisition processes. For each of these types, we present approaches to detect, reason about, and resolve error candidates, as we propose measures and visual guidance techniques to support machine learning users. Our approach has been used to spot errors in well-known machine learning benchmark data sets, and we tested its usability during a user evaluation. While initially developed for images, the techniques presented in this paper are independent of the classification algorithm, and can also be extended to many other types of training data.
  • Item
    VisuaLint: Sketchy In Situ Annotations of Chart Construction Errors
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Hopkins, Aspen K.; Correll, Michael; Satyanarayan, Arvind; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Chart construction errors, such as truncated axes or inexpressive visual encodings, can hinder reading a visualization, or worse, imply misleading facts about the underlying data. These errors can be caught by critical readings of visualizations, but readers must have a high level of data and design literacy and must be paying close attention. To address this issue, we introduce VisuaLint: a technique for surfacing chart construction errors in situ. Inspired by the ubiquitous red wavy underline that indicates spelling mistakes, visualization elements that contain errors (e.g., axes and legends) are sketchily rendered and accompanied by a concise annotation. VisuaLint is unobtrusive-it does not interfere with reading a visualization-and its direct display establishes a close mapping between erroneous elements and the expression of error. We demonstrate five examples of VisualLint and present the results of a crowdsourced evaluation (N = 62) of its efficacy. These results contribute an empirical baseline proficiency for recognizing chart construction errors, and indicate near-universal difficulty in error identification. We find that people more reliably identify chart construction errors after being shown examples of VisuaLint, and prefer more verbose explanations for unfamiliar or less obvious flaws.
  • Item
    Understanding the Design Space and Authoring Paradigms for Animated Data Graphics
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Thompson, John R.; Liu, Zhicheng; Li, Wilmot; Stasko, John; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Creating expressive animated data graphics often requires designers to possess highly specialized programming skills. Alternatively, the use of direct manipulation tools is popular among animation designers, but these tools have limited support for generating graphics driven by data. Our goal is to inform the design of next-generation animated data graphic authoring tools. To understand the composition of animated data graphics, we survey real-world examples and contribute a description of the design space. We characterize animated transitions based on object, graphic, data, and timing dimensions. We synthesize the primitives from the object, graphic, and data dimensions as a set of 10 transition types, and describe how timing primitives compose broader pacing techniques. We then conduct an ideation study that uncovers how people approach animation creation with three authoring paradigms: keyframe animation, procedural animation, and presets & templates. Our analysis shows that designers have an overall preference for keyframe animation. However, we find evidence that an authoring tool should combine these three paradigms as designers' preferences depend on the characteristics of the animated transition design and the authoring task. Based on these findings, we contribute guidelines and design considerations for developing future animated data graphic authoring tools.
  • Item
    Quantitative Evaluation of Time-Dependent Multidimensional Projection Techniques
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Vernier, Eduardo Faccin; Garcia, Rafael; Silva, Iron Prando da; Comba, João L. D.; Telea, Alexandru C.; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Dimensionality reduction methods are an essential tool for multidimensional data analysis, and many interesting processes can be studied as time-dependent multivariate datasets. There are, however, few studies and proposals that leverage on the concise power of expression of projections in the context of dynamic/temporal data. In this paper, we aim at providing an approach to assess projection techniques for dynamic data and understand the relationship between visual quality and stability. Our approach relies on an experimental setup that consists of existing techniques designed for time-dependent data and new variations of static methods. To support the evaluation of these techniques, we provide a collection of datasets that has a wide variety of traits that encode dynamic patterns, as well as a set of spatial and temporal stability metrics that assess the quality of the layouts. We present an evaluation of 9 methods, 10 datasets, and 12 quality metrics, and elect the best-suited methods for projecting time-dependent multivariate data, exploring the design choices and characteristics of each method. Additional results can be found in the online benchmark repository. We designed our evaluation pipeline and benchmark specifically to be a live resource, open to all researchers who can further add their favorite datasets and techniques at any point in the future.
  • Item
    Many At Once: Capturing Intentions to Create And Use Many Views At Once In Large Display Environments
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Aurisano, Jillian; Kumar, Abhinav; Alsaiari, Abeer; Eugenio, Barbara Di; Johnson, Andrew E.; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    This paper describes results from an observational, exploratory study of visual data exploration in a large, multi-view, flexible canvas environment. Participants were provided with a set of data exploration sub-tasks associated with a local crime dataset and were instructed to pose questions to a remote mediator who would respond by generating and organizing visualizations on the large display. We observed that participants frequently posed requests to cast a net around one or several subsets of the data or a set of data attributes. They accomplished this directly and by utilizing existing views in unique ways, including by requesting to copy and pivot a group of views collectively and posing a set of parallel requests on target views expressed in one command. These observed actions depart from multi-view flexible canvas environments that typically provide interfaces in support of generating one view at a time or actions that operate on one view at a time. We describe how participants used these 'cast-a-net' requests for tasks that spanned more than one view and describe design considerations for multi-view environments that would support the observed multi-view generation actions.
  • Item
    Phase Space Projection of Dynamical Systems
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Bartolovic, Nemanja; Gross, Markus; Günther, Tobias; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Dynamical systems are commonly used to describe the state of time-dependent systems. In many engineering and control problems, the state space is high-dimensional making it difficult to analyze and visualize the behavior of the system for varying input conditions. We present a novel dimensionality reduction technique that is tailored to high-dimensional dynamical systems. In contrast to standard general purpose dimensionality reduction algorithms, we use energy minimization to preserve properties of the flow in the high-dimensional space. Once the projection operator is optimized, further high-dimensional trajectories are projected easily. Our 3D projection maintains a number of useful flow properties, such as critical points and flow maps, and is optimized to match geometric characteristics of the high-dimensional input, as well as optional user constraints. We apply our method to trajectories traced in the phase spaces of second-order dynamical systems, including finite-sized objects in fluids, the circular restricted three-body problem and a damped double pendulum. We compare the projections with standard visualization techniques, such as PCA, t-SNE and UMAP, and visualize the dynamical systems with multiple coordinated views interactively, featuring a spatial embedding, projection to subspaces, our dimensionality reduction and a seed point exploration tool.
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    Structure and Empathy in Visual Data Storytelling: Evaluating their Influence on Attitude
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Liem, Johannes; Perin, Charles; Wood, Jo; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    In the visualization community, it is often assumed that visual data storytelling increases memorability and engagement, making it more effective at communicating information. However, many assumptions about the efficacy of storytelling in visualization lack empirical evaluation. Contributing to an emerging body of work, we study whether selected techniques commonly used in visual data storytelling influence people's attitudes towards immigration. We compare (a) personal visual narratives designed to generate empathy; (b) structured visual narratives of aggregates of people; and (c) an exploratory visualization without narrative acting as a control condition. We conducted two crowdsourced between-subject studies comparing the three conditions, each with 300 participants. To assess the differences in attitudes between conditions, we adopted established scales from the social sciences used in the European Social Survey (ESS). Although we found some differences between conditions, the effects on people's attitudes are smaller than we expected. Our findings suggest that we need to be more careful when it comes to our expectations about the effects visual data storytelling can have on attitudes.
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    Short-Contact Touch-Manipulation of Scatterplot Matrices on Wall Displays
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Riehmann, Patrick; Molina León, Gabriela; Reibert, Joshua; Echtler, Florian; Froehlich, Bernd; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    This paper presents a short-contact multitouch vocabulary for interacting with scatterplot matrices (SPLOMs) on wall-sized displays. Fling-based gestures overcome central interaction challenges of such large displays by avoiding long swipes on the typically blunt surfaces, frequent physical navigation by walking for accessing screen areas beyond arm's reach in the horizontal direction and uncomfortable postures for accessing screen areas in the vertical direction. Furthermore, we make use of the display's high resolution and large size by supporting the efficient specification of two-tiered focus + context regions which are consistently propagated across the SPLOM. These techniques are complemented by axis-centered and lasso-based selection techniques for specifying subsets of the data. An expert review as well as a user study confirmed the potential and general usability of our seamlessly integrated multitouch interaction techniques for SPLOMs on large vertical displays.
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    Co-creating Visualizations: A First Evaluation with Social Science Researchers
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Molina León, Gabriela; Breiter, Andreas; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Co-creation is a design method where designers and domain experts work together to develop a product. In this paper, we present and evaluate the use of co-creation to design a visual information system with social science researchers in order to explore and analyze their data. Co-creation proposes involving the future users in the design process to ensure that they play a critical role in the design, and to increase the chances of long-term adoption. We evaluated the co-creation process through surveys, interviews and a user study. According to the participants' feedback, they felt listened to through co-creation, and considered the methodology helpful to develop visualizations that support their research in the near future. However, participation was far from perfect, particularly early career researchers showed limited interest in participating because they did not see the process as beneficial for their research publication goals. We summarize benefits and limitations of co-creation, together with our recommendations, as lessons learned.
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    Extraction of Distinguished Hyperbolic Trajectories for 2D Time-Dependent Vector Field Topology
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Hofmann, Lutz; Sadlo, Filip; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    This paper does two main contributions to 2D time-dependent vector field topology. First, we present a technique for robust, accurate, and efficient extraction of distinguished hyperbolic trajectories (DHT), the generative structures of 2D time-dependent vector field topology. It is based on refinement of initial candidate curves. In contrast to previous approaches, it is robust because the refinement converges for reasonably close initial candidates, it is accurate due to its adaptive scheme, and it is efficient due to its high convergence speed. Second, we provide a detailed evaluation and discussion of previous approaches for the extraction of DHTs and time-dependent vector field topology in general. We demonstrate the utility of our approach using analytical flows, as well as data from computational fluid dynamics.
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    Fiber Surfaces for many Variables
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Blecha, Christian; Raith, Felix; Präger, Arne Jonas; Nagel, Thomas; Kolditz, Olaf; Maßmann, Jobst; Röber, Niklas; Böttinger, Michael; Scheuermann, Gerik; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Scientific visualization deals with increasingly complex data consisting of multiple fields. Typical disciplines generating multivariate data are fluid dynamics, structural mechanics, geology, bioengineering, and climate research. Quite often, scientists are interested in the relation between some of these variables. A popular visualization technique for a single scalar field is the extraction and rendering of isosurfaces. With this technique, the domain can be split into two parts, i.e. a volume with higher values and one with lower values than the selected isovalue. Fiber surfaces generalize this concept to two or three scalar variables up to now. This article extends the notion further to potentially any finite number of scalar fields. We generalize the fiber surface extraction algorithm of Raith et al. [RBN*19] from 3 to d dimensions and demonstrate the technique using two examples from geology and climate research. The first application concerns a generic model of a nuclear waste repository and the second one an atmospheric simulation over central Europe. Both require complex simulations which involve multiple physical processes. In both cases, the new extended fiber surfaces helps us finding regions of interest like the nuclear waste repository or the power supply of a storm due to their characteristic properties.
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    Visual Analysis of the Finite-Time Lyapunov Exponent
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Sagristà, Antoni; Jordan, Stefan; Sadlo, Filip; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    In this paper, we present an integrated visual analytics approach to support the parametrization and exploration of flow visualization based on the finite-time Lyapunov exponent. Such visualization of time-dependent flow faces various challenges, including the choice of appropriate advection times, temporal regions of interest, and spatial resolution. Our approach eases these challenges by providing the user with context by means of parametric aggregations, with support and guidance for a more directed exploration, and with a set of derived measures for better qualitative assessment. We demonstrate the utility of our approach with examples from computation fluid dynamics and time-dependent dynamical systems.
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    Fuzzy Contour Trees: Alignment and Joint Layout of Multiple Contour Trees
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Lohfink, Anna-Pia; Wetzels, Florian; Lukasczyk, Jonas; Weber, Gunther H.; Garth, Christoph; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    We describe a novel technique for the simultaneous visualization of multiple scalar fields, e.g. representing the members of an ensemble, based on their contour trees. Using tree alignments, a graph-theoretic concept similar to edit distance mappings, we identify commonalities across multiple contour trees and leverage these to obtain a layout that can represent all trees simultaneously in an easy-to-interpret, minimally-cluttered manner. We describe a heuristic algorithm to compute tree alignments for a given similarity metric, and give an algorithm to compute a joint layout of the resulting aligned contour trees. We apply our approach to the visualization of scalar field ensembles, discuss basic visualization and interaction possibilities, and demonstrate results on several analytic and real-world examples.
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    Metro Maps on Octilinear Grid Graphs
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Bast, Hannah; Brosi, Patrick; Storandt, Sabine; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Schematic transit maps (often called "metro maps" in the literature) are important to produce comprehensible visualizations of complex public transit networks. In this work, we investigate the problem of automatically drawing such maps on an octilinear grid with an arbitrary (but optimal) number of edge bends. Our approach can naturally deal with obstacles that should be respected in the final drawing (points of interest, rivers, coastlines) and can prefer grid edges near the real-world course of a line. This allows our drawings to be combined with existing maps, for example as overlays in map services. We formulate an integer linear program which can be used to solve the problem exactly. We also provide a fast approximation algorithm which greedily calculates shortest paths between node candidates on the underlying octilinear grid graph. Previous work used local search techniques to update node positions until a local optimum was found, but without guaranteeing octilinearity. We can thus calculate nearly optimal metro maps in a fraction of a second even for complex networks, enabling the interactive use of our method in map editors.
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    Augmenting Node-Link Diagrams with Topographic Attribute Maps
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Preiner, Reinhold; Schmidt, Johanna; Krösl, Katharina; Schreck, Tobias; Mistelbauer, Gabriel; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    We propose a novel visualization technique for graphs that are attributed with scalar data. In many scenarios, these attributes (e.g., birth date in a family network) provide ambient context information for the graph structure, whose consideration is important for different visual graph analysis tasks. Graph attributes are usually conveyed using different visual representations (e.g., color, size, shape) or by reordering the graph structure according to the attribute domain (e.g., timelines). While visual encodings allow graphs to be arranged in a readable layout, assessing contextual information such as the relative similarities of attributes across the graph is often cumbersome. In contrast, attribute-based graph reordering serves the comparison task of attributes, but typically strongly impairs the readability of the structural information given by the graph's topology. In this work, we augment force-directed node-link diagrams with a continuous ambient representation of the attribute context. This way, we provide a consistent overview of the graph's topological structure as well as its attributes, supporting a wide range of graph-related analysis tasks. We resort to an intuitive height field metaphor, illustrated by a topographic map rendering using contour lines and suitable color maps. Contour lines visually connect nodes of similar attribute values, and depict their relative arrangement within the global context. Moreover, our contextual representation supports visualizing attribute value ranges associated with graph nodes (e.g., lifespans in a family network) as trajectories routed through this height field. We discuss how user interaction with both the structural and the contextual information fosters exploratory graph analysis tasks. The effectiveness and versatility of our technique is confirmed in a user study and case studies from various application domains.
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    Set Streams: Visual Exploration of Dynamic Overlapping Sets
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Agarwal, Shivam; Beck, Fabian; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    In many applications, membership of set elements changes over time. Since each element can be present in multiple sets, the sets also overlap. As a result, it becomes challenging to visualize the temporal change in set membership of elements across several timesteps while showing individual set intersections.We propose Set Streams, a visualization technique that represents changing set structures on a timeline as branching and merging streams. The streams encode the changing membership of elements with set intersections. A query-based selection mechanism supports a flexible comparison of selected groups of elements across the temporal evolution. The main timeline view is complemented with additional panels to provide details about the elements. While the proposed visualization is an application-independent visualization technique for dynamic sets, we demonstrate its effectiveness and applicability through three diverse application examples and expert feedback.
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    Quantitative Comparison of Time-Dependent Treemaps
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Vernier, Eduardo; Sondag, Max; Comba, João; Speckmann, Bettina; Telea, Alexandru; Verbeek, Kevin; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Rectangular treemaps are often the method of choice to visualize large hierarchical datasets. Nowadays such datasets are available over time, hence there is a need for (a) treemaps that can handle time-dependent data, and (b) corresponding quality criteria that cover both a treemap's visual quality and its stability over time. In recent years a wide variety of (stable) treemapping algorithms has been proposed, with various advantages and limitations. We aim to provide insights to researchers and practitioners to allow them to make an informed choice when selecting a treemapping algorithm for specific applications and data. To this end, we perform an extensive quantitative evaluation of rectangular treemaps for time-dependent data. As part of this evaluation we propose a novel classification scheme for time-dependent datasets. Specifically, we observe that the performance of treemapping algorithms depends on the characteristics of the datasets used. We identify four potential representative features that characterize time-dependent hierarchical datasets and classify all datasets used in our experiments accordingly. We experimentally test the validity of this classification on more than 2000 datasets, and analyze the relative performance of 14 state-of-the-art rectangular treemapping algorithms across varying features. Finally, we visually summarize our results with respect to both visual quality and stability to aid users in making an informed choice among treemapping algorithms. All datasets, metrics, and algorithms are openly available to facilitate reuse and further comparative studies.
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    PAVED: Pareto Front Visualization for Engineering Design
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Cibulski, Lena; Mitterhofer, Hubert; May, Thorsten; Kohlhammer, Jörn; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Design problems in engineering typically involve a large solution space and several potentially conflicting criteria. Selecting a compromise solution is often supported by optimization algorithms that compute hundreds of Pareto-optimal solutions, thus informing a decision by the engineer. However, the complexity of evaluating and comparing alternatives increases with the number of criteria that need to be considered at the same time. We present a design study on Pareto front visualization to support engineers in applying their expertise and subjective preferences for selection of the most-preferred solution. We provide a characterization of data and tasks from the parametric design of electric motors. The requirements identified were the basis for our development of PAVED, an interactive parallel coordinates visualization for exploration of multi-criteria alternatives. We reflect on our user-centered design process that included iterative refinement with real data in close collaboration with a domain expert as well as a summative evaluation in the field. The results suggest a high usability of our visualization as part of a real-world engineering design workflow. Our lessons learned can serve as guidance to future visualization developers targeting multi-criteria optimization problems in engineering design or alternative domains.
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    A Globally Conforming Lattice Structure for 2D Stress Tensor Visualization
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Wang, Junpeng; Wu, Jun; Westermann, Rüdiger; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    We present a visualization technique for 2D stress tensor fields based on the construction of a globally conforming lattice. Conformity ensures that the lattice edges follow the principal stress directions and the aspect ratio of lattice elements represents the stress anisotropy. Since such a lattice structure cannot be space-filling in general, it is constructed from multiple intersecting lattice beams. Conformity at beam intersections is ensured via a constrained optimization problem, by computing the aspect ratio of elements at intersections so that their edges meet when continued along the principal stress lines. In combination with a coloring scheme that encodes relative stress magnitudes, a global visualization is achieved. By introducing additional constraints on the positional variation of the beam intersections, coherent visualizations are achieved when external loads or material parameters are changed. In a number of experiments using non-trivial scenarios, we demonstrate the capability of the proposed visualization technique to show the global and local structure of a given stress field.
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    Feature Driven Combination of Animated Vector Field Visualizations
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Lobo, María Jesús; Telea, Alexandru; Hurter, Christophe; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Animated visualizations are one of the methods for finding and understanding complex structures of time-dependent vector fields. Many visualization designs can be used to this end, such as streamlines, vector glyphs, and image-based techniques. While all such designs can depict any vector field, their effectiveness in highlighting particular field aspects has not been fully explored. To fill this gap, we compare three animated vector field visualization techniques, OLIC, IBFV, and particles, for a critical point detection-and-classification task through a user study. Our results show that the effectiveness of the studied techniques depends on the nature of the critical points. We use these results to design a new flow visualization technique that combines all studied techniques in a single view by locally using the most effective technique for the patterns present in the flow data at that location. A second user study shows that our technique is more efficient and less error prone than the three other techniques used individually for the critical point detection task.
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    LOCALIS: Locally-adaptive Line Simplification for GPU-based Geographic Vector Data Visualization
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Amiraghdam, Alireza; Diehl, Alexandra; Pajarola, Renato; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Visualization of large vector line data is a core task in geographic and cartographic systems. Vector maps are often displayed at different cartographic generalization levels, traditionally by using several discrete levels-of-detail (LODs). This limits the generalization levels to a fixed and predefined set of LODs, and generally does not support smooth LOD transitions. However, fast GPUs and novel line rendering techniques can be exploited to integrate dynamic vector map LOD management into GPU-based algorithms for locally-adaptive line simplification and real-time rendering. We propose a new technique that interactively visualizes large line vector datasets at variable LODs. It is based on the Douglas-Peucker line simplification principle, generating an exhaustive set of line segments whose specific subsets represent the lines at any variable LOD. At run time, an appropriate and view-dependent error metric supports screen-space adaptive LOD levels and the display of the correct subset of line segments accordingly. Our implementation shows that we can simplify and display large line datasets interactively. We can successfully apply line style patterns, dynamic LOD selection lenses, and anti-aliasing techniques to our line rendering.
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    GTMapLens: Interactive Lens for Geo-Text Data Browsing on Map
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Ma, Chao; Zhao, Ye; AL-Dohuki, Shamal; Yang, Jing; Ye, Xinyue; Kamw, Farah; Amiruzzaman, Md; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Data containing geospatial semantics, such as geotagged tweets, travel blogs, and crime reports, associates natural language texts with geographical locations. This paper presents a lens-based visual interaction technique, GTMapLens, to flexibly browse the geo-text data on a map. It allows users to perform dynamic focus+context exploration by using movable lenses to browse geographical regions, find locations of interest, and perform comparative and drill-down studies. Geo-text data is visualized in a way that users can easily perceive the underlying geospatial semantics along with lens moving. Based on a requirement analysis with a cohort of multidisciplinary domain experts, a set of lens interaction techniques are developed including keywords control, path management, context visualization, and snapshot anchors. They allow users to achieve a guided and controllable exploration of geo-text data. A hierarchical data model enables the interactive lens operations by accelerated data retrieval from a geo-text database. Evaluation with real-world datasets is presented to show the usability and effectiveness of GTMapLens.
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    Data Comets: Designing a Visualization Tool for Analyzing Autonomous Aerial Vehicle Logs with Grounded Evaluation
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Saffo, David; Leventidis, Aristotelis; Jain, Twinkle; Borkin, Michelle A.; Dunne, Cody; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Autonomous unmanned aerial vehicles are complex systems of hardware, software, and human input. Understanding this complexity is key to their development and operation. Information visualizations already exist for exploring flight logs but comprehensive analyses currently require several disparate and custom tools. This design study helps address the pain points faced by autonomous unmanned aerial vehicle developers and operators. We contribute: a spiral development process model for grounded evaluation visualization development focused on progressively broadening target user involvement and refining user goals; a demonstration of the model as part of developing a deployed and adopted visualization system; a data and task abstraction for developers and operators performing post-flight analysis of autonomous unmanned aerial vehicle logs; the design and implementation of DATA COMETS, an open-source and web-based interactive visualization tool for post-flight log analysis incorporating temporal, geospatial, and multivariate data; and the results of a summative evaluation of the visualization system and our abstractions based on in-the-wild usage.
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    Resolving Conflicting Insights in Asynchronous Collaborative Visual Analysis
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Li, Jianping Kelvin; Xu, Shenyu; Ye, Yecong (Chris); Ma, Kwan-Liu; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Analyzing large and complex datasets for critical decision making can benefit from a collective effort involving a team of analysts. However, insights and findings from different analysts are often incomplete, disconnected, or even conflicting. Most existing analysis tools lack proper support for examining and resolving the conflicts among the findings in order to consolidate the results of collaborative data analysis. In this paper, we present CoVA, a visual analytics system incorporating conflict detection and resolution for supporting asynchronous collaborative data analysis. By using a declarative visualization language and graph representation for managing insights and insight provenance, CoVA effectively leverages distributed revision control workflow from software engineering to automatically detect and properly resolve conflicts in collaborative analysis results. In addition, CoVA provides an effective visual interface for resolving conflicts as well as combining the analysis results. We conduct a user study to evaluate CoVA for collaborative data analysis. The results show that CoVA allows better understanding and use of the findings from different analysts.
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    WarehouseVis: A Visual Analytics Approach to Facilitating Warehouse Location Selection for Business Districts
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Li, Quan; Liu, Qiangqiang; Tang, Chunfeng; Li, Zhiwei; Wei, Shuaichao; Peng, Xianrui; Zheng, Minghua; Chen, Tianjian; Yang, Qiang; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Selecting a proper warehouse location serving to satisfy the demands of the goods from a certain business area is important to a successful retail business. However, the large solution space, uncertain traffic conditions, and varying business preferences impose great challenges on warehouse location selection. Conventional approaches mainly summarize relevant evaluation criteria and compile them into an analysis report to facilitate rapid data absorption but fail to support a comprehensive and joint decision-making process in warehouse location selection. In this paper, we propose a visual analytics approach to facilitating warehouse location selection. We first visually centralize relevant information of warehouses and adapts a widely-used methodology to efficiently rank warehouse candidates. We then design a delivering estimation model based on massive logistics trajectories to resolve the uncertainty issue of traffic conditions of warehouses. Based on these techniques, an interactive framework is proposed to generate and explore the candidate warehouses. We conduct a case study and a within-subject study with baseline systems to assess the efficacy of our system. Experts' feedback also suggests that our approach indeed helps them better tackle the problem of finding an ideal warehouse in the field of retail logistics management.
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    SeqDynamics: Visual Analytics for Evaluating Online Problem-solving Dynamics
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Xia, Meng; Xu, Min; Lin, Chuan-en; Cheng, Ta Ying; Qu, Huamin; Ma, Xiaojuan; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Problem-solving dynamics refers to the process of solving a series of problems over time, from which a student's cognitive skills and non-cognitive traits and behaviors can be inferred. For example, we can derive a student's learning curve (an indicator of cognitive skill) from the changes in the difficulty level of problems solved, or derive a student's self-regulation patterns (an example of non-cognitive traits and behaviors) based on the problem-solving frequency over time. Few studies provide an integrated overview of both aspects by unfolding the problem-solving process. In this paper, we present a visual analytics system named SeqDynamics that evaluates students' problem-solving dynamics from both cognitive and non-cognitive perspectives. The system visualizes the chronological sequence of learners' problem-solving behavior through a set of novel visual designs and coordinated contextual views, enabling users to compare and evaluate problem-solving dynamics on multiple scales. We present three scenarios to demonstrate the usefulness of SeqDynamics on a real-world dataset which consists of thousands of problem-solving traces. We also conduct five expert interviews to show that SeqDynamics enhances domain experts' understanding of learning behavior sequences and assists them in completing evaluation tasks efficiently.
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    SEEVis: A Smart Emergency Evacuation Plan Visualization System with Data-Driven Shot Designs
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Li, Quan; Liu, Yingjie J.; Chen, Li; Yang, Xingchao C.; Peng, Yi; Yuan, Xiaoru R.; Wijerathne, Maddegedara Lalith Lakshman; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Despite the significance of tracking human mobility dynamics in a large-scale earthquake evacuation for an effective first response and disaster relief, the general understanding of evacuation behaviors remains limited. Numerous individual movement trajectories, disaster damages of civil engineering, associated heterogeneous data attributes, as well as complex urban environment all obscure disaster evacuation analysis. Although visualization methods have demonstrated promising performance in emergency evacuation analysis, they cannot effectively identify and deliver the major features like speed or density, as well as the resulting evacuation events like congestion or turn-back. In this study, we propose a shot design approach to generate customized and narrative animations to track different evacuation features with different exploration purposes of users. Particularly, an intuitive scene feature graph that identifies the most dominating evacuation events is first constructed based on user-specific regions or their tracking purposes on a certain feature. An optimal camera route, i.e., a storyboard is then calculated based on the previous user-specific regions or features. For different evacuation events along this route, we employ the corresponding shot design to reveal the underlying feature evolution and its correlation with the environment. Several case studies confirm the efficacy of our system. The feedback from experts and users with different backgrounds suggests that our approach indeed helps them better embrace a comprehensive understanding of the earthquake evacuation.
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    Evaluating Reordering Strategies for Cluster Identification in Parallel Coordinates
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Blumenschein, Michael; Zhang, Xuan; Pomerenke, David; Keim, Daniel A.; Fuchs, Johannes; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    The ability to perceive patterns in parallel coordinates plots (PCPs) is heavily influenced by the ordering of the dimensions. While the community has proposed over 30 automatic ordering strategies, we still lack empirical guidance for choosing an appropriate strategy for a given task. In this paper, we first propose a classification of tasks and patterns and analyze which PCP reordering strategies help in detecting them. Based on our classification, we then conduct an empirical user study with 31 participants to evaluate reordering strategies for cluster identification tasks. We particularly measure time, identification quality, and the users' confidence for two different strategies using both synthetic and real-world datasets. Our results show that, somewhat unexpectedly, participants tend to focus on dissimilar rather than similar dimension pairs when detecting clusters, and are more confident in their answers. This is especially true when increasing the amount of clutter in the data. As a result of these findings, we propose a new reordering strategy based on the dissimilarity of neighboring dimension pairs.
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    Sunspot Plots: Model-based Structure Enhancement for Dense Scatter Plots
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Trautner, Thomas; Bolte, Fabian; Stoppel, Sergej; Bruckner, Stefan; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Scatter plots are a powerful and well-established technique for visualizing the relationships between two variables as a collection of discrete points. However, especially when dealing with large and dense data, scatter plots often exhibit problems such as overplotting, making the data interpretation arduous. Density plots are able to overcome these limitations in highly populated regions, but fail to provide accurate information of individual data points. This is particularly problematic in sparse regions where the density estimate may not provide a good representation of the underlying data. In this paper, we present sunspot plots, a visualization technique that communicates dense data as a continuous data distribution, while preserving the discrete nature of data samples in sparsely populated areas. We furthermore demonstrate the advantages of our approach on typical failure cases of scatter plots within synthetic and real-world data sets and validate its effectiveness in a user study.
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    v-plots: Designing Hybrid Charts for the Comparative Analysis of Data Distributions
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Blumenschein, Michael; Debbeler, Luka J.; Lages, Nadine C.; Renner, Britta; Keim, Daniel A.; El-Assady, Mennatallah; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Comparing data distributions is a core focus in descriptive statistics, and part of most data analysis processes across disciplines. In particular, comparing distributions entails numerous tasks, ranging from identifying global distribution properties, comparing aggregated statistics (e.g., mean values), to the local inspection of single cases. While various specialized visualizations have been proposed (e.g., box plots, histograms, or violin plots), they are not usually designed to support more than a few tasks, unless they are combined. In this paper, we present the v-plot designer; a technique for authoring custom hybrid charts, combining mirrored bar charts, difference encodings, and violin-style plots. v-plots are customizable and enable the simultaneous comparison of data distributions on global, local, and aggregation levels. Our system design is grounded in an expert survey that compares and evaluates 20 common visualization techniques to derive guidelines for the task-driven selection of appropriate visualizations. This knowledge externalization step allowed us to develop a guiding wizard that can tailor v-plots to individual tasks and particular distribution properties. Finally, we confirm the usefulness of our system design and the userguiding process by measuring the fitness for purpose and applicability in a second study with four domain and statistic experts.
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    Sublinear Time Force Computation for Big Complex Network Visualization
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Meidiana, Amyra; Hong, Seok-Hee; Torkel, Marnijati; Cai, Shijun; Eades, Peter; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    In this paper, we present a new framework for sublinear time force computation for visualization of big complex graphs. Our algorithm is based on the sampling of vertices for computing repulsion forces and edge sparsification for attraction force computation. More specifically, for vertex sampling, we present three types of sampling algorithms, including random sampling, geometric sampling, and combinatorial sampling, to reduce the repulsion force computation to sublinear in the number of vertices. We utilize a spectral sparsification approach to reduce the number of attraction force computations to sublinear in the number of edges for dense graphs. We also present a smart initialization method based on radial tree drawing of the BFS spanning tree rooted at the center. Experiments show that our new sublinear time force computation algorithms run quite fast, while producing good visualization of large and complex networks, with significant improvements in quality metrics such as shape-based and edge crossing metrics.
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    Infomages: Embedding Data into Thematic Images
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Coelho, Darius; Mueller, Klaus; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Recent studies have indicated that visually embellished charts such as infographics have the ability to engage viewers and positively affect memorability. Fueled by these findings, researchers have proposed a variety of infographic design tools. However, these tools do not cover the entire design space. In this work, we identify a subset of infographics that we call infomages. Infomages are casual visuals of data in which a data chart is embedded into a thematic image such that the content of the image reflects the subject and the designer's interpretation of the data. Creating an effective infomage, however, can require a fair amount of design expertise and is thus out of reach for most people. In order to also afford non-artists with the means to design convincing infomages, we first study the principled design of existing infomages and identify a set of key chart embedding techniques. Informed by these findings we build a design tool that links web-scale image search with a set of interactive image processing tools to empower novice users with the ability to design a wide variety of infomages. As the embedding process might introduce some amount of visual distortion of the data our tool also aids users to gauge the amount of this distortion, if any. We experimentally demonstrate the usability of our tool and conclude with a discussion of infomages and our design tool.
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    Canis: A High-Level Language for Data-Driven Chart Animations
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Ge, Tong; Zhao, Yue; Lee, Bongshin; Ren, Donghao; Chen, Baoquan; Wang, Yunhai; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    In this paper, we introduce Canis, a high-level domain-specific language that enables declarative specifications of data-driven chart animations. By leveraging data-enriched SVG charts, its grammar of animations can be applied to the charts created by existing chart construction tools. With Canis, designers can select marks from the charts, partition the selected marks into mark units based on data attributes, and apply animation effects to the mark units, with the control of when the effects start. The Canis compiler automatically synthesizes the Lottie animation JSON files [Aira], which can be rendered natively across multiple platforms. To demonstrate Canis' expressiveness, we present a wide range of chart animations. We also evaluate its scalability by showing the effectiveness of our compiler in reducing the output specification size and comparing its performance on different platforms against D3.