EuroVisShort2020

Permanent URI for this collection

EuroVis 2020 - 22nd EG/VGTC Conference on Visualization
Norrköping, Sweden, May 25-29, 2020 (Virtual)
Analytics and Evaluation
The Effect of Graph Layout on the Perception of Graph Properties
Elektra Kypridemou, Michele Zito, and Marco Bertamini
Exploring Time Series Segmentations Using Uncertainty and Focus+Context Techniques
Christian Bors, Christian Eichner, Silvia Miksch, Christian Tominski, Heidrun Schumann, and Theresia Gschwandtner
SAMBAVis: Design Study of a Visual Analytics Tool for the Music Industry Powered by YouTube Comments
Victor Adriel de Jesus Oliveira, Christina Stoiber, Johanna Grüblbauer, Christoph Musik, Alexis Ringot, and Andreas Gebesmair
Configuration Finder: A Tidy Visual Interface for Effective Faceted Search
Patrick Riehmann, Andreas Schädler, Jannis Harder, Jakob Herpel, and Bernd Froehlich
ARGUS: Interactive Visual Analytics Framework for the Discovery of Disruptions in Bio-Behavioral Rhythms
Hamid Mansoor, Walter Gerych, Luke Buquicchio, Abdulaziz Alajaji, Kavin Chandrasekaran, Emmanuel Agu, and Elke Rundensteiner
Design of a Real Time Visual Analytics Support Tool for Conflict Detection and Resolution in Air Traffic Control
Elmira Zohrevandi, Carl A. L. Westin, Jonas Lundberg, and Anders Ynnerman
Dissecting Visual Analytics: Comparing Frameworks for Interpreting and Modelling Observed Visual Analytics Behavior
Vanessa Brown, Cagatay Turkay, and Radu Jianu
Examining Design-Centric Test Participants in Graphical Perception Experiments
Grace Guo, Bianchi Dy, Nazim Ibrahim, Sam Conrad Joyce, and Ate Poorthuis
Mix: Color, Design, etc.
Designing Pairs of Colormaps for Visualizing Bivariate Scalar Fields
Colin Ware, Francesca Samsel, David H. Rogers, Paul Navratil, and Ayat Mohammed
Interactive Creation of Perceptually Uniform Color Maps
Martin Lambers
Task-based Colormap Design Supporting Visual Comprehension in Process Tomography
Yuchong Zhang, Morten Fjeld, Alan Said, and Marco Fratarcangeli
Investigating the Role of Locus of Control in Moderating Complex Analytic Workflows
R. Jordan Crouser, Alvitta Ottley, Kendra Swanson, and Ananda Montoly
Exploring Design Opportunities for Visually Congruent Proxemics in Information Visualization: A Design Space
Neil Chulpongsatorn, Jackie Yu, and Søren Knudsen
Characterizing Exploratory Behaviors on a Personal Visualization Interface Using Interaction Logs
Poorna Talkad Sukumar, Gonzalo J. Martinez, Ted Grover, Gloria Mark, Sidney K. D'Mello, Nitesh V. Chawla, Stephen M. Mattingly, and Aaron D. Striegel
TopoLines: Topological Smoothing for Line Charts
Paul Rosen, Ashley Suh, Christopher Salgado, and Mustafa Hajij
Evaluating Strategies of Exploratory Visual Data Analysis in Multi Device Environments
Abeer Alsaiari, Jillian Aurisano, and Andrew E. Johnson
Representation, Perception, and ML
Influence of Container Resolutions on the Layout Stability of Squarified and Slice-And-Dice Treemaps
Volker Knauthe, Kathrin Ballweg, Marcel Wunderlich, Tatiana von Landesberger, and Stefan Guthe
Width-Scale Bar Charts for Data with Large Value Range
Markus Höhn, Marcel Wunderlich, Kathrin Ballweg, and Tatiana von Landesberger
A Force-Directed Power Diagram Approach for Interactive Voronoi Treemaps
Ala Abuthawabeh and Michaël Aupetit
Fast Design Space Rendering of Scatterplots
Simo Santala, Antti Oulasvirta, and Tino Weinkauf
Glyph-Based Visualization of Affective States
Nikola Kovacevic, Rafael Wampfler, Barbara Solenthaler, Markus Gross, and Tobias Günther
GaCoVi: a Correlation Visualization to Support Interpretability-Aware Feature Selection for Regression Models
Diego Rojo, Nyi Nyi Htun, and Katrien Verbert
Progressive Uniform Manifold Approximation and Projection
Hyung-Kwon Ko, Jaemin Jo, and Jinwook Seo
Rendering, Images, and Applications
Sketchy Rendering to Aid the Recollection of Regular Visualizations
Michael Reidun Engelbrecht Larsen, Wenkai Han, and Hans-Jörg Schulz
Progressive Rendering of Transparent Integral Surfaces
Xingze Tian and Tobias Günther
Effective Visualization of Sparse Image-to-Image Correspondences
Carlos Andujar, Antonio Chica, and Marc Comino
Joint-Sphere: Intuitive and Detailed Human Joint Motion Representation
Seonghun Kim, Adithya Balasubramanyam, Dubeom Kim, Young Ho Chai, and Ashok Kumar Patil
MODELAR: A MODular and EvaLuative framework to improve surgical Augmented Reality visualization
Georges Hattab, Felix Meyer, Remke Dirk Albrecht, and Stefanie Speidel
Comprehensive Visualization of Longitudinal Patient Data for the Dermatological Oncological Tumor Board
Nastasja Steinhauer, Marc Hörbrugger, Andreas Dominik Braun, Thomas Tüting, Steffen Oeltze-Jafra, and Juliane Müller
RankBooster: Visual Analysis of Ranking Predictions
Abishek Puri, Bon Kyung Ku, Yong Wang, and Huamin Qu
Visualising Collocation for Close Writing
Jonathan C. Roberts, Peter W. S. Butcher, Robert Lew, Geraint Paul Rees, Nirwan Sharma, and Ana Frankenberg-Garcia

BibTeX (EuroVisShort2020)
@inproceedings{
10.2312:evs.20201039,
booktitle = {
EuroVis 2020 - Short Papers},
editor = {
Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
}, title = {{
The Effect of Graph Layout on the Perception of Graph Properties}},
author = {
Kypridemou, Elektra
 and
Zito, Michele
 and
Bertamini, Marco
}, year = {
2020},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-106-9},
DOI = {
10.2312/evs.20201039}
}
@inproceedings{
10.2312:evs.20201041,
booktitle = {
EuroVis 2020 - Short Papers},
editor = {
Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
}, title = {{
SAMBAVis: Design Study of a Visual Analytics Tool for the Music Industry Powered by YouTube Comments}},
author = {
Oliveira, Victor Adriel de Jesus
 and
Stoiber, Christina
 and
Grüblbauer, Johanna
 and
Musik, Christoph
 and
Ringot, Alexis
 and
Gebesmair, Andreas
}, year = {
2020},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-106-9},
DOI = {
10.2312/evs.20201041}
}
@inproceedings{
10.2312:evs.20201040,
booktitle = {
EuroVis 2020 - Short Papers},
editor = {
Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
}, title = {{
Exploring Time Series Segmentations Using Uncertainty and Focus+Context Techniques}},
author = {
Bors, Christian
 and
Eichner, Christian
 and
Miksch, Silvia
 and
Tominski, Christian
 and
Schumann, Heidrun
 and
Gschwandtner, Theresia
}, year = {
2020},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-106-9},
DOI = {
10.2312/evs.20201040}
}
@inproceedings{
10.2312:evs.20201042,
booktitle = {
EuroVis 2020 - Short Papers},
editor = {
Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
}, title = {{
Configuration Finder: A Tidy Visual Interface for Effective Faceted Search}},
author = {
Riehmann, Patrick
 and
Schädler, Andreas
 and
Harder, Jannis
 and
Herpel, Jakob
 and
Froehlich, Bernd
}, year = {
2020},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-106-9},
DOI = {
10.2312/evs.20201042}
}
@inproceedings{
10.2312:evs.20201043,
booktitle = {
EuroVis 2020 - Short Papers},
editor = {
Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
}, title = {{
ARGUS: Interactive Visual Analytics Framework for the Discovery of Disruptions in Bio-Behavioral Rhythms}},
author = {
Mansoor, Hamid
 and
Gerych, Walter
 and
Buquicchio, Luke
 and
Alajaji, Abdulaziz
 and
Chandrasekaran, Kavin
 and
Agu, Emmanuel
 and
Rundensteiner, Elke
}, year = {
2020},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-106-9},
DOI = {
10.2312/evs.20201043}
}
@inproceedings{
10.2312:evs.20201044,
booktitle = {
EuroVis 2020 - Short Papers},
editor = {
Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
}, title = {{
Design of a Real Time Visual Analytics Support Tool for Conflict Detection and Resolution in Air Traffic Control}},
author = {
Zohrevandi, Elmira
 and
Westin, Carl A. L.
 and
Lundberg, Jonas
 and
Ynnerman, Anders
}, year = {
2020},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-106-9},
DOI = {
10.2312/evs.20201044}
}
@inproceedings{
10.2312:evs.20201045,
booktitle = {
EuroVis 2020 - Short Papers},
editor = {
Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
}, title = {{
Dissecting Visual Analytics: Comparing Frameworks for Interpreting and Modelling Observed Visual Analytics Behavior}},
author = {
Brown, Vanessa
 and
Turkay, Cagatay
 and
Jianu, Radu
}, year = {
2020},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-106-9},
DOI = {
10.2312/evs.20201045}
}
@inproceedings{
10.2312:evs.20201046,
booktitle = {
EuroVis 2020 - Short Papers},
editor = {
Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
}, title = {{
Examining Design-Centric Test Participants in Graphical Perception Experiments}},
author = {
Guo, Grace
 and
Dy, Bianchi
 and
Ibrahim, Nazim
 and
Joyce, Sam Conrad
 and
Poorthuis, Ate
}, year = {
2020},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-106-9},
DOI = {
10.2312/evs.20201046}
}
@inproceedings{
10.2312:evs.20201048,
booktitle = {
EuroVis 2020 - Short Papers},
editor = {
Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
}, title = {{
Interactive Creation of Perceptually Uniform Color Maps}},
author = {
Lambers, Martin
}, year = {
2020},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-106-9},
DOI = {
10.2312/evs.20201048}
}
@inproceedings{
10.2312:evs.20201049,
booktitle = {
EuroVis 2020 - Short Papers},
editor = {
Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
}, title = {{
Task-based Colormap Design Supporting Visual Comprehension in Process Tomography}},
author = {
Zhang, Yuchong
 and
Fjeld, Morten
 and
Said, Alan
 and
Fratarcangeli, Marco
}, year = {
2020},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-106-9},
DOI = {
10.2312/evs.20201049}
}
@inproceedings{
10.2312:evs.20201047,
booktitle = {
EuroVis 2020 - Short Papers},
editor = {
Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
}, title = {{
Designing Pairs of Colormaps for Visualizing Bivariate Scalar Fields}},
author = {
Ware, Colin
 and
Samsel, Francesca
 and
Rogers, David H.
 and
Navratil, Paul
 and
Mohammed, Ayat
}, year = {
2020},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-106-9},
DOI = {
10.2312/evs.20201047}
}
@inproceedings{
10.2312:evs.20201050,
booktitle = {
EuroVis 2020 - Short Papers},
editor = {
Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
}, title = {{
Investigating the Role of Locus of Control in Moderating Complex Analytic Workflows}},
author = {
Crouser, R. Jordan
 and
Ottley, Alvitta
 and
Swanson, Kendra
 and
Montoly, Ananda
}, year = {
2020},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-106-9},
DOI = {
10.2312/evs.20201050}
}
@inproceedings{
10.2312:evs.20201052,
booktitle = {
EuroVis 2020 - Short Papers},
editor = {
Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
}, title = {{
Characterizing Exploratory Behaviors on a Personal Visualization Interface Using Interaction Logs}},
author = {
Sukumar, Poorna Talkad
 and
Martinez, Gonzalo J.
 and
Grover, Ted
 and
Mark, Gloria
 and
D'Mello, Sidney K.
 and
Chawla, Nitesh V.
 and
Mattingly, Stephen M.
 and
Striegel, Aaron D.
}, year = {
2020},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-106-9},
DOI = {
10.2312/evs.20201052}
}
@inproceedings{
10.2312:evs.20201051,
booktitle = {
EuroVis 2020 - Short Papers},
editor = {
Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
}, title = {{
Exploring Design Opportunities for Visually Congruent Proxemics in Information Visualization: A Design Space}},
author = {
Chulpongsatorn, Neil
 and
Yu, Jackie
 and
Knudsen, Søren
}, year = {
2020},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-106-9},
DOI = {
10.2312/evs.20201051}
}
@inproceedings{
10.2312:evs.20201053,
booktitle = {
EuroVis 2020 - Short Papers},
editor = {
Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
}, title = {{
TopoLines: Topological Smoothing for Line Charts}},
author = {
Rosen, Paul
 and
Suh, Ashley
 and
Salgado, Christopher
 and
Hajij, Mustafa
}, year = {
2020},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-106-9},
DOI = {
10.2312/evs.20201053}
}
@inproceedings{
10.2312:evs.20201055,
booktitle = {
EuroVis 2020 - Short Papers},
editor = {
Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
}, title = {{
Influence of Container Resolutions on the Layout Stability of Squarified and Slice-And-Dice Treemaps}},
author = {
Knauthe, Volker
 and
Ballweg, Kathrin
 and
Wunderlich, Marcel
 and
Landesberger, Tatiana von
 and
Guthe, Stefan
}, year = {
2020},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-106-9},
DOI = {
10.2312/evs.20201055}
}
@inproceedings{
10.2312:evs.20201054,
booktitle = {
EuroVis 2020 - Short Papers},
editor = {
Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
}, title = {{
Evaluating Strategies of Exploratory Visual Data Analysis in Multi Device Environments}},
author = {
Alsaiari, Abeer
 and
Aurisano, Jillian
 and
Johnson, Andrew E.
}, year = {
2020},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-106-9},
DOI = {
10.2312/evs.20201054}
}
@inproceedings{
10.2312:evs.20201056,
booktitle = {
EuroVis 2020 - Short Papers},
editor = {
Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
}, title = {{
Width-Scale Bar Charts for Data with Large Value Range}},
author = {
Höhn, Markus
 and
Wunderlich, Marcel
 and
Ballweg, Kathrin
 and
Landesberger, Tatiana von
}, year = {
2020},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-106-9},
DOI = {
10.2312/evs.20201056}
}
@inproceedings{
10.2312:evs.20201058,
booktitle = {
EuroVis 2020 - Short Papers},
editor = {
Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
}, title = {{
Fast Design Space Rendering of Scatterplots}},
author = {
Santala, Simo
 and
Oulasvirta, Antti
 and
Weinkauf, Tino
}, year = {
2020},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-106-9},
DOI = {
10.2312/evs.20201058}
}
@inproceedings{
10.2312:evs.20201057,
booktitle = {
EuroVis 2020 - Short Papers},
editor = {
Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
}, title = {{
A Force-Directed Power Diagram Approach for Interactive Voronoi Treemaps}},
author = {
Abuthawabeh, Ala
 and
Aupetit, Michaël
}, year = {
2020},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-106-9},
DOI = {
10.2312/evs.20201057}
}
@inproceedings{
10.2312:evs.20201059,
booktitle = {
EuroVis 2020 - Short Papers},
editor = {
Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
}, title = {{
Glyph-Based Visualization of Affective States}},
author = {
Kovacevic, Nikola
 and
Wampfler, Rafael
 and
Solenthaler, Barbara
 and
Gross, Markus
 and
Günther, Tobias
}, year = {
2020},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-106-9},
DOI = {
10.2312/evs.20201059}
}
@inproceedings{
10.2312:evs.20201062,
booktitle = {
EuroVis 2020 - Short Papers},
editor = {
Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
}, title = {{
Sketchy Rendering to Aid the Recollection of Regular Visualizations}},
author = {
Larsen, Michael Reidun Engelbrecht
 and
Han, Wenkai
 and
Schulz, Hans-Jörg
}, year = {
2020},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-106-9},
DOI = {
10.2312/evs.20201062}
}
@inproceedings{
10.2312:evs.20201060,
booktitle = {
EuroVis 2020 - Short Papers},
editor = {
Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
}, title = {{
GaCoVi: a Correlation Visualization to Support Interpretability-Aware Feature Selection for Regression Models}},
author = {
Rojo, Diego
 and
Htun, Nyi Nyi
 and
Verbert, Katrien
}, year = {
2020},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-106-9},
DOI = {
10.2312/evs.20201060}
}
@inproceedings{
10.2312:evs.20201061,
booktitle = {
EuroVis 2020 - Short Papers},
editor = {
Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
}, title = {{
Progressive Uniform Manifold Approximation and Projection}},
author = {
Ko, Hyung-Kwon
 and
Jo, Jaemin
 and
Seo, Jinwook
}, year = {
2020},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-106-9},
DOI = {
10.2312/evs.20201061}
}
@inproceedings{
10.2312:evs.20201063,
booktitle = {
EuroVis 2020 - Short Papers},
editor = {
Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
}, title = {{
Progressive Rendering of Transparent Integral Surfaces}},
author = {
Tian, Xingze
 and
Günther, Tobias
}, year = {
2020},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-106-9},
DOI = {
10.2312/evs.20201063}
}
@inproceedings{
10.2312:evs.20201064,
booktitle = {
EuroVis 2020 - Short Papers},
editor = {
Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
}, title = {{
Effective Visualization of Sparse Image-to-Image Correspondences}},
author = {
Andujar, Carlos
 and
Chica, Antonio
 and
Comino Trinidad, Marc
}, year = {
2020},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-106-9},
DOI = {
10.2312/evs.20201064}
}
@inproceedings{
10.2312:evs.20201065,
booktitle = {
EuroVis 2020 - Short Papers},
editor = {
Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
}, title = {{
Joint-Sphere: Intuitive and Detailed Human Joint Motion Representation}},
author = {
Kim, Seonghun
 and
Balasubramanyam, Adithya
 and
Kim, Dubeom
 and
Chai, Young Ho
 and
Patil, Ashok Kumar
}, year = {
2020},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-106-9},
DOI = {
10.2312/evs.20201065}
}
@inproceedings{
10.2312:evs.20201066,
booktitle = {
EuroVis 2020 - Short Papers},
editor = {
Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
}, title = {{
MODELAR: A MODular and EvaLuative framework to improve surgical Augmented Reality visualization}},
author = {
Hattab, Georges
 and
Meyer, Felix
 and
Albrecht, Remke Dirk
 and
Speidel, Stefanie
}, year = {
2020},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-106-9},
DOI = {
10.2312/evs.20201066}
}
@inproceedings{
10.2312:evs.20201067,
booktitle = {
EuroVis 2020 - Short Papers},
editor = {
Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
}, title = {{
Comprehensive Visualization of Longitudinal Patient Data for the Dermatological Oncological Tumor Board}},
author = {
Steinhauer, Nastasja
 and
Hörbrugger, Marc
 and
Braun, Andreas Dominik
 and
Tüting, Thomas
 and
Oeltze-Jafra, Steffen
 and
Müller, Juliane
}, year = {
2020},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-106-9},
DOI = {
10.2312/evs.20201067}
}
@inproceedings{
10.2312:evs.20201068,
booktitle = {
EuroVis 2020 - Short Papers},
editor = {
Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
}, title = {{
RankBooster: Visual Analysis of Ranking Predictions}},
author = {
Puri, Abishek
 and
Ku, Bon Kyung
 and
Wang, Yong
 and
Qu, Huamin
}, year = {
2020},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-106-9},
DOI = {
10.2312/evs.20201068}
}
@inproceedings{
10.2312:evs.20201069,
booktitle = {
EuroVis 2020 - Short Papers},
editor = {
Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
}, title = {{
Visualising Collocation for Close Writing}},
author = {
Roberts, Jonathan C.
 and
Butcher, Peter W. S.
 and
Lew, Robert
 and
Rees, Geraint Paul
 and
Sharma, Nirwan
 and
Frankenberg-Garcia, Ana
}, year = {
2020},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-106-9},
DOI = {
10.2312/evs.20201069}
}

Browse

Recent Submissions

Now showing 1 - 32 of 32
  • Item
    EuroVis 2020 Short Papers: Frontmatter
    (The Eurographics Association, 2020) Kerren, Andreas; Garth, Christoph; Marai, G. Elisabeta; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
  • Item
    The Effect of Graph Layout on the Perception of Graph Properties
    (The Eurographics Association, 2020) Kypridemou, Elektra; Zito, Michele; Bertamini, Marco; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    The way in which a graph is described visually is crucial for the understanding and analysis of its structure. In this study we explore how different drawing layouts affect our perception of the graph's properties. We study the perception of connectedness, tree-ness and density using four different layouts: the Circular, Grid, Planar and Spring layouts. Results show that some layouts are better than others when we need to decide whether a graph is a tree or is connected. More sophisticated algorithms, like Planar and Spring, facilitate our perception, while Circular and Grid layouts lead to performance not better than chance. However, when perceiving the density of a graph, no layout was found to be better than the others.
  • Item
    SAMBAVis: Design Study of a Visual Analytics Tool for the Music Industry Powered by YouTube Comments
    (The Eurographics Association, 2020) Oliveira, Victor Adriel de Jesus; Stoiber, Christina; Grüblbauer, Johanna; Musik, Christoph; Ringot, Alexis; Gebesmair, Andreas; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    Data from comments on social media platforms offer valuable information about trends and market changes. Aiming at the music industry, we propose SAMBAVis: a visual analytics tool to handle user-generated content from comments left on YouTube music videos. SAMBAVis displays main key performance indexes, video lifecycle, and engagement with comments. It also performs sentiment analysis and extracts the main keywords from the comments, expanding YouTube capabilities. In this paper, we contribute with a design study, explaining the development of SAMBAVis and the rationale of our design. We present a usage scenario and reflect on our methods and results when creating a visualization tool for experts in the music business.
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    Exploring Time Series Segmentations Using Uncertainty and Focus+Context Techniques
    (The Eurographics Association, 2020) Bors, Christian; Eichner, Christian; Miksch, Silvia; Tominski, Christian; Schumann, Heidrun; Gschwandtner, Theresia; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    Time series segmentation is employed in various domains and continues to be a relevant topic of research. A segmentation pipeline is composed of different steps involving several parameterizable algorithms. Existing Visual Analytics approaches can help experts determine appropriate parameterizations and corresponding segmentation results for a given dataset. However, the results may also be afflicted with different types of uncertainties. Hence, experts face the additional challenge of understanding the reliability of multiple alternative the segmentation results. So far, the influence of uncertainties in the context of time series segmentation could not be investigated. We present an uncertainty-aware exploration approach for analyzing large sets of multivariate time series segmentations. The approach features an overview of uncertainties and time series segmentations, while detailed exploration is facilitated by (1) a lens-based focus+context technique and (2) uncertainty-based re-arrangement. The suitability of our uncertainty-aware design was evaluated in a quantitative user study, which resulted in interesting findings of general validity.
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    Configuration Finder: A Tidy Visual Interface for Effective Faceted Search
    (The Eurographics Association, 2020) Riehmann, Patrick; Schädler, Andreas; Harder, Jannis; Herpel, Jakob; Froehlich, Bernd; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    We present an interactive visualization aiding users in making informed decisions about large product data sets consisting of quantitative and categorical attributes. Our approach tries to overcome common problems between parallel attribute axes, for instance limited horizontal space or clutter, by introducing novel visual concepts such as proxy axes, fusion axes, and hybrids of set-based and individual axis connections. A proxy axis represents a group of semantically related attributes, which can be interactively explored and seamlessly integrated into the display. Fusion axes allow users to reduce the number of axes by merging categorical+categorical or categorical+quantitative attribute axes. Set-based or individual connections between axis pairs are chosen according to the involved attribute types. The pilot study and expert reviews showed that these novel concepts are understood, considered to be very useful and favored over up-to-date webshop interfaces.
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    ARGUS: Interactive Visual Analytics Framework for the Discovery of Disruptions in Bio-Behavioral Rhythms
    (The Eurographics Association, 2020) Mansoor, Hamid; Gerych, Walter; Buquicchio, Luke; Alajaji, Abdulaziz; Chandrasekaran, Kavin; Agu, Emmanuel; Rundensteiner, Elke; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    Human Bio-Behavioral Rhythms (HBRs) such as sleep-wake cycles and their regularity have important health ramifications. Smartphones can sense HBRs by gathering and analyzing data from built-in sensors, which provide behavioral clues. The multichannel nature (multiple sensor streams) of such data makes it challenging to pin-point the causes of disruptions in HBRs. Prior work has utilized machine learning for HBR classification but has not facilitated deeper understanding or reasoning about the potential disruption causes. In this paper, we propose ARGUS, an interactive visual analytics framework to discover and understand HBR disruptions and causes. The foundation of ARGUS is a Rhythm Deviation Score (RDS) that extracts a user's underlying 24-hour rhythm from their smartphone sensor data and quantifies its irregularity. ARGUS then visualizes the RDS using a glyph to easily recognize disruptions in HBRs, along with multiple linked panes that overlay sensor information and user-provided or smartphone-inferred ground truth as supporting context. This framework visually captures a comprehensive picture of HBRs and their disruptions. ARGUS was designed by an expert lead goal-and-task analysis. To demonstrate its generalizability, two different smartphone-sensed datasets were visualized using ARGUS in conjunction with expert feedback.
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    Design of a Real Time Visual Analytics Support Tool for Conflict Detection and Resolution in Air Traffic Control
    (The Eurographics Association, 2020) Zohrevandi, Elmira; Westin, Carl A. L.; Lundberg, Jonas; Ynnerman, Anders; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    Air traffic control is a safety critical high-risk environment where operators need to analyse and interpret traffic dynamics of spatio-temporal data in real-time. To support the air traffic controller in safely separating traffic, earlier research has applied real-time visualisation techniques that explore the constraints and solution spaces of separation problems. Traditionally, situation displays for conflict detection and resolution have used visualisations that convey information about the relative horizontal position between aircraft. Although vertical solutions for solving conflicts are common, and often a preferred among controllers, visualisations typically provide limited information about the vertical relationship between aircraft. This paper presents a design study of an interactive conflict detection and resolution support tool and explores techniques for real-time visualisation of spatio-temporal data. The design evolution has incorporated several activities, including an initial work domain analysis, iterative rounds of programming, design, and evaluations with a domain expert, and an evaluation with eight active controllers. The heading-time-altitude visualisation system is developed based on formulating and solving aircraft movements in a relative coordinate system. A polar-graph visualisation technique is used to construct a view of conflicting aircraft vertical solution spaces in the temporal domain. Using composite glyphs, the final heading-time-altitude visualisation provides a graphical representation of both horizontal and vertical solution spaces for the traffic situation.
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    Dissecting Visual Analytics: Comparing Frameworks for Interpreting and Modelling Observed Visual Analytics Behavior
    (The Eurographics Association, 2020) Brown, Vanessa; Turkay, Cagatay; Jianu, Radu; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    This paper provides an empirical, comparative exploration of the role of analytic frameworks in interpreting and modelling visual analytics behavior through data gathered in observational studies. The crucial research on understanding the complex and multi-faceted interplay between visual analytics tools and their users is often done through controlled or naturalistic observations of analysts engaging in the visual analytic process, followed by the interpretation of the observation data. The researchers in Human Computer Interaction and Cognitive Sciences have long used structured analytic frameworks for such analyses, where a guiding set of principles and questions direct attention to relevant aspects of the studied behavior, eventually leading to more complete and consistent analyses. Such frameworks are rarely applied in the visualization domain however, and information about how to apply them and their benefits is scarce. With this paper, we contribute a comparative account, grounded in empirical data collected in a user study with 10 participants using Tableau to analyze domain-specific data, of the types of insights we can glean from interpreting observational data using three different frameworks: Joint Action Theory, Distributed Cognition, and Situated Cognition.
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    Examining Design-Centric Test Participants in Graphical Perception Experiments
    (The Eurographics Association, 2020) Guo, Grace; Dy, Bianchi; Ibrahim, Nazim; Joyce, Sam Conrad; Poorthuis, Ate; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    In this paper, we replicate a foundational study in graphical perception, and compare our findings from using design-centric participants with that of previous studies. We also assess the visual accuracy of two groups, students and professionals, both with design backgrounds, to identify the potential effects of participants' backgrounds on their ability to accurately read charts. Our findings demonstrate that results for reading accuracy for different chart types of previous empirical studies [CM84,HB10] are applicable to participants of design backgrounds. We also demonstrate that besides significant differences in response time, there are no significant differences in reading accuracy between the student and professional groups in our study. This indicates that, despite bias in research participants for visualization research, previous conclusions about graphical perception are likely applicable across different populations and possibly work fields.
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    Interactive Creation of Perceptually Uniform Color Maps
    (The Eurographics Association, 2020) Lambers, Martin; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    A large number of design rules have been identified for color maps used in Scientific Visualization. One of the most important of these is perceptual uniformity, which at the same time is one of the hardest to guarantee when color maps are created from user input. In this paper, we propose parameterized color map models for a variety of application areas. To allow interactive creation of color maps, these models are based on few intuitive parameters, and at the same time guarantee approximate perceptual uniformity.
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    Task-based Colormap Design Supporting Visual Comprehension in Process Tomography
    (The Eurographics Association, 2020) Zhang, Yuchong; Fjeld, Morten; Said, Alan; Fratarcangeli, Marco; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    Color coding is a fundamental technique for mapping data to visual representations, allowing people to carry out comprehension-based tasks. Process tomography is a rapidly developing non-invasive imaging technique used in various fields of science due to its effective flow monitoring and data acquisition [KLS*19]. To study how well colormaps can support visual comprehension of tomographic data, we conduct a feasibility evaluation of 11 widely-used color schemes. We employ the same segmentation tasks characterized by Microwave Tomography (MWT) on each individual chosen colormap, and then conduct a quantitative assessment of those schemes. Based on the insight gained, we conclude that autumn, viridis, and parula colormaps yield the best segmentation results. According to our findings, we propose a colormap design guideline for practitioners and researchers in the field of process tomography.
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    Designing Pairs of Colormaps for Visualizing Bivariate Scalar Fields
    (The Eurographics Association, 2020) Ware, Colin; Samsel, Francesca; Rogers, David H.; Navratil, Paul; Mohammed, Ayat; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    In scientific visualization there is sometimes a requirement for two colormaps to be used to represent two co-registered scalar fields. One solution is to represent one of the fields as a continuous colormapped image, and the second field by means of a dense distribution of small glyphs overlaid on the background image and coded using a different colormap. This requires the design of pairs of colormaps which each can be easily read, but which minimally interfere with one another. Colormap pairs separated according to lightness, saturation and hue, were designed and evaluated using both a key accuracy task and a pattern identification task. The saturation separation pair (one colormap having high saturation and the other low saturation) was the best overall.
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    Investigating the Role of Locus of Control in Moderating Complex Analytic Workflows
    (The Eurographics Association, 2020) Crouser, R. Jordan; Ottley, Alvitta; Swanson, Kendra; Montoly, Ananda; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    Throughout the last decade, researchers have shown that the effectiveness of a visualization tool depends on the experience, personality, and cognitive abilities of the user. This work has also demonstrated that these individual traits can have significant implications for tools that support reasoning and decision-making with data. However, most studies in this area to date have involved only short-duration tasks performed by lay users. This short paper presents a preliminary analysis of a series of exercises with 22 trained intelligence analysts that seeks to deepen our understanding of how individual differences modulate expert behavior in complex analysis tasks.
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    Characterizing Exploratory Behaviors on a Personal Visualization Interface Using Interaction Logs
    (The Eurographics Association, 2020) Sukumar, Poorna Talkad; Martinez, Gonzalo J.; Grover, Ted; Mark, Gloria; D'Mello, Sidney K.; Chawla, Nitesh V.; Mattingly, Stephen M.; Striegel, Aaron D.; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    Personal visualizations present a separate class of visualizations where users interact with their own data to draw inferences about themselves. In this paper, we study how a realistic understanding of personal visualizations can be gained from analyzing user interactions. We designed an interface presenting visualizations of the personal data gathered in a prior study and logged interactions from 369 participants as they each explored their own data. We found that the participants spent different amounts of time in exploring their data and used a variety of physical devices which could have affected their engagement with the visualizations. Our findings also suggest that the participants made more comparisons between their data instances than with the provided baselines and certain interface design choices, such as the ordering of options, influenced their exploratory behaviors.
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    Exploring Design Opportunities for Visually Congruent Proxemics in Information Visualization: A Design Space
    (The Eurographics Association, 2020) Chulpongsatorn, Neil; Yu, Jackie; Knudsen, Søren; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    We explore design opportunities for varying visual complexity of information visualizations based on distance. Through considering visual congruency and proxemics interaction, we describe a design space that considers potential transitions between visualizations in relation to distance. Our design space is based on exploring prototyping and design possibilities. It describes three properties (boundedness, connectedness, and cardinality) and five design patterns (subdivision, particalization, peculiarization, multiplication, and nesting) that might be considered in design. We describe our design ideas and prototypes, as well as reflect on their usefulness. Finally, we discuss limitations and implications of our work.
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    TopoLines: Topological Smoothing for Line Charts
    (The Eurographics Association, 2020) Rosen, Paul; Suh, Ashley; Salgado, Christopher; Hajij, Mustafa; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    Line charts are commonly used to visualize a series of data values. When the data are noisy, smoothing is applied to make the signal more apparent. Conventional methods used to smooth line charts, e.g., using subsampling or filters, such as median, Gaussian, or low-pass, each optimize for different properties of the data. The properties generally do not include retaining peaks (i.e., local minima and maxima) in the data, which is an important feature for certain visual analytics tasks. We present TopoLines, a method for smoothing line charts using techniques from Topological Data Analysis. The design goal of TopoLines is to maintain prominent peaks in the data while minimizing any residual error. We evaluate TopoLines for 2 visual analytics tasks by comparing to 5 popular line smoothing methods with data from 4 application domains.
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    Influence of Container Resolutions on the Layout Stability of Squarified and Slice-And-Dice Treemaps
    (The Eurographics Association, 2020) Knauthe, Volker; Ballweg, Kathrin; Wunderlich, Marcel; Landesberger, Tatiana von; Guthe, Stefan; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    In this paper, we analyze the layout stability for the squarify and slice-and-dice treemap layout algorithms when changing the visualization containers resolution. We also explore how rescaling a finished layout to another resolution compares to a recalculated layout, i.e. fixed layout versus changing layout. For our evaluation, we examine a real world use-case and use a total of 240000 random data treemap visualizations. Rescaling slice-and-dice or squarify layouts affects the aspect ratios. Recalculating slice-and-dice layouts is equivalent to rescaling since the layout is not affected by changing the container resolution. Recalculating squarify layouts, on the other hand, yields stable aspect ratios but results in potentially huge layout changes. Finally, we provide guidelines for using rescaling, recalculation and the choice of algorithm.
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    Evaluating Strategies of Exploratory Visual Data Analysis in Multi Device Environments
    (The Eurographics Association, 2020) Alsaiari, Abeer; Aurisano, Jillian; Johnson, Andrew E.; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    Supporting exploratory visual data analysis is essential when multiple analysts collaborate using multiple devices. Yet, we still have no full understanding of how the iterative process of analysis unfolds in complex settings. In this paper, we present the results from an exploratory study where six groups of three participants performed a collaborative visual data analysis task in a complex multi-user multi-device environment. We found that the course of the analysis happens at two levels. Within each level, we observed a set of exploration patterns. We present a categorization of the analysis structure in such a complex environment and discuss the implications of device affordances on this categorization. We also discuss this categorization in relation to the current structural assumptions of exploratory visual analysis.
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    Width-Scale Bar Charts for Data with Large Value Range
    (The Eurographics Association, 2020) Höhn, Markus; Wunderlich, Marcel; Ballweg, Kathrin; Landesberger, Tatiana von; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    Data sets with large value range are difficult to visualize with traditional linear bar charts. Usually, a logarithmic scale is used in these cases. However, the logarithmic scale suffers from non-linearity. Recently, scale-stack bar charts and magnitude markers, improve the readability of values. However, they have other disadvantages such as various scales or several objects for visualizing one value. We propose the width-scale bar chart that uses width, height and color to cover a large value range within one linear scale. A quantitative user study shows advantages of our design - especially for reading values.
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    Fast Design Space Rendering of Scatterplots
    (The Eurographics Association, 2020) Santala, Simo; Oulasvirta, Antti; Weinkauf, Tino; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    The design space of scatterplots consists of a number of parameters such as marker size and shape, image width and aspect ratio, and opacity. Different parameters yield different visual impressions of the scatterplot. Perceptual optimization of scatterplots means finding the best design parameters to support a given visualization task. This requires rendering thousands of design variations. We describe an image-based method for rendering scatterplots, which is tailored to this scenario: it enables quick updates of the design by re-using previously calculated intermediate results, and is independent of the data set size. Our approach outperforms the classic method of rendering scatterplots, i.e., drawing each marker individually onto an image, and can therefore dramatically speed up the perceptual optimization of scatterplots. We provide an open-source implementation and an online service for our method.
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    A Force-Directed Power Diagram Approach for Interactive Voronoi Treemaps
    (The Eurographics Association, 2020) Abuthawabeh, Ala; Aupetit, Michaël; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    Voronoi treemaps represent weighted hierarchical data as nested Voronoi diagram partitions with cells' area proportional to the weights. Current techniques to compute them propose static visualizations which can be used for reporting, or dynamic one to capture data update. However, no ideal solution exists yet to interactively rearrange the treemap layout, for instance for a data journalist to tell a story, or for a scientist to create data categorization. We propose a new way to get an interactive Voronoi treemap, where a child cell can be moved by drag-and-drop within a parent cell attempting to preserve both stability (position) and weight (area) during the move. We use a force-directed approach applied to the dual circles of the Power cells to guide the computation of the Power diagram under the hood. Our preliminary quantitative experiments show the force-directed approach provides areas with 10% weighted average error, which is an order of magnitude higher than standard static approaches, but qualitative observations show that it gives a more predictable and smoother interaction, and a direct control over the stability of the remaining cells. Assuming the user would focus less on getting high accuracy of the areas than keeping a good and stable overview of the treemap while dragging a cell, the force-directed approach appears to be a valuable option to explore further. We also discovered a trade-off between stability and accuracy and the force-directed approach lets the user control it directly.
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    Glyph-Based Visualization of Affective States
    (The Eurographics Association, 2020) Kovacevic, Nikola; Wampfler, Rafael; Solenthaler, Barbara; Gross, Markus; Günther, Tobias; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    Decades of research in psychology on the formal measurement of emotions led to the concept of affective states. Visualizing the measured affective state can be useful in education, as it allows teachers to adapt lessons based on the affective state of students. In the entertainment industry, game mechanics can be adapted based on the boredom and frustration levels of a player. Visualizing the affective state can also increase emotional self-awareness of the user whose state is being measured, which can have an impact on well-being. However, graphical user interfaces seldom visualize the user's affective state, but rather focus on the purely objective interaction between the system and the user. This paper proposes two graphical user interface widgets that visualize the user's affective state, ensuring a compact and unobtrusive visualization. In a user study with 644 participants, the widgets were evaluated in relation to a baseline widget and were tested on intuitiveness and understandability. Particularly in terms of understandability, the baseline was outperformed by our two widgets.
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    Sketchy Rendering to Aid the Recollection of Regular Visualizations
    (The Eurographics Association, 2020) Larsen, Michael Reidun Engelbrecht; Han, Wenkai; Schulz, Hans-Jörg; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    Some visualizations have a more regular visual appearance than others. For example, while stream graphs or force-directed network layouts feature a unique, almost organic 'look and feel', matrices or unit treemaps can become rather bland, grid-like visualizations in which one data item is hard to tell apart from the next. In this paper, we investigate the use of sketchy rendering for such grid-like visualizations to give them a slightly more unique 'look and feel' themselves. We evaluate our approach in a lab study (N = 16) where participants were asked to re-find a given grid cell in regular and sketchy grids. We find that users who make conscious use of the sketchy features can benefit from certain forms of sketchy rendering in terms of task completion times.
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    GaCoVi: a Correlation Visualization to Support Interpretability-Aware Feature Selection for Regression Models
    (The Eurographics Association, 2020) Rojo, Diego; Htun, Nyi Nyi; Verbert, Katrien; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    The recent growth of interest in explainable artificial intelligence (XAI) has resulted in a large number of research efforts to provide accountable and transparent machine learning systems. Although a large volume of research has focused on algorithm transparency, there are other factors that influence the interpretability of a system, such as end-users' understanding of individual features and the total number of features. Thus, involving end-users in the feature selection process may be key to achieving interpretability. In addition, previous work has suggested that to obtain satisfactory interpretability and predictive performance, the feature selection process should look for a subset of features that are highly correlated with the response variable yet uncorrelated to each other. Taking this into account, in this paper, we present a work-in-progress design study of a novel system for correlation visualization, GaCoVi. GaCoVi is designed to put domain experts in the loop of feature selection for regression models in scenarios where transparency of the machine learning systems is crucial.
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    Progressive Uniform Manifold Approximation and Projection
    (The Eurographics Association, 2020) Ko, Hyung-Kwon; Jo, Jaemin; Seo, Jinwook; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    We present a progressive algorithm for the Uniform Manifold Approximation and Projection (UMAP), called the Progressive UMAP. Based on the theory of Riemannian geometry and algebraic topology, UMAP is an emerging dimensionality reduction technique that offers better versatility and stability than t-SNE. Although UMAP is also more efficient than t-SNE, it still suffers from an initial delay of a few minutes to produce the first projection, which limits its use in interactive data exploration. To tackle this problem, we improve the sequential computations in UMAP by making them progressive, which allows people to incrementally append a batch of data points into the projection at the desired pace. In our experiment with the Fashion MNIST dataset, we found that Progressive UMAP could generate the first approximate projection within a few seconds while also sufficiently capturing the important structures of the high-dimensional dataset.
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    Progressive Rendering of Transparent Integral Surfaces
    (The Eurographics Association, 2020) Tian, Xingze; Günther, Tobias; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    Integral surfaces are a useful method in illustrative and geometry-based flow visualization, as they convey shading, depth and geometric information better than their line-based counterparts. However, they are not as frequently used as line-based techniques due to the added complexity that arises from their computation. Frontline-based methods, such as stream surfaces and path surfaces require an adaptive subdivision of the frontline, whereas advected surfaces, such as streak surfaces and time surfaces, require refinement and possibly retriangulation of the entire surface after each time step. In this paper, we extend an image-space surface rendering technique to support transparency, which enables the application of illustrative surface rendering techniques without the need to adaptively refine frontlines or entire surfaces. We develop a pixel-based dynamic tree data structure that is progressively filled with integral curves and compactly stores the transparent layers arising in the rendering of the surfaces. We apply the method to the illustrative rendering of path surfaces and streak surfaces in a number of time-dependent vector fields.
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    Effective Visualization of Sparse Image-to-Image Correspondences
    (The Eurographics Association, 2020) Andujar, Carlos; Chica, Antonio; Comino Trinidad, Marc; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    Finding robust correspondences between images is a crucial step in photogrammetry applications. The traditional approach to visualize sparse matches between two images is to place them side-by-side and draw link segments connecting pixels with matching features. In this paper we present new visualization techniques for sparse correspondences between image pairs. Key ingredients of our techniques include (a) the clustering of consistent matches, (b) the optimization of the image layout to minimize occlusions due to the super-imposed links, (c) a color mapping to minimize color interference among links (d) a criterion for giving visibility priority to isolated links, (e) the bending of link segments to put apart nearby links, and (f) the use of glyphs to facilitate the identification of matching keypoints. We show that our technique substantially reduces the clutter in the final composite image and thus makes it easier to detect and inspect both inlier and outlier matches. Potential applications include the validation of image pairs in difficult setups and the visual comparison of feature detection / matching algorithms.
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    Joint-Sphere: Intuitive and Detailed Human Joint Motion Representation
    (The Eurographics Association, 2020) Kim, Seonghun; Balasubramanyam, Adithya; Kim, Dubeom; Chai, Young Ho; Patil, Ashok Kumar; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    A motion comparison method using images allows for the motions to be easily recognized and to see differences between each action. However, when using images, orientation differences between similar motions cannot be quantified. Although many studies have been conducted on methods to represent the data and apply detailed motion comparisons, these representations are difficult to understand because the relationship between the motion and the representation is not clear. This paper introduces a novel motion representation method called the Joint-Sphere that enables detailed motion comparisons and an intuitive understanding of each joint movement. In each Joint-Sphere, the movement of a specific joint part is represented. Several Joint- Spheres can be used to represent a full-body motion. The results from a dance motion pattern show that each joint movement can be compared accurately even when several joints are moving quickly.
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    MODELAR: A MODular and EvaLuative framework to improve surgical Augmented Reality visualization
    (The Eurographics Association, 2020) Hattab, Georges; Meyer, Felix; Albrecht, Remke Dirk; Speidel, Stefanie; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    The use of Augmented Reality (AR) for the visualization of 3D biomedical image data is possible thanks to a growing number of hardware and software solutions. Considerable efforts are made during surgery, where the visual information of the target structures can either be highlighted or dulled. However, as technical challenges and barriers to development decrease, it's increasingly important to take into account the specific capacities and constraints of the surgeon's perceptual and cognitive systems. To address this legitimate problem, we present a practical framework that evaluates the importance of visual encodings and renderings for surgical AR. By conducting a task-specific user study we observed a set of emerging visualization strategies. The given task is to make the kidney boundary visually salient and make the tumor and calyx distinguishable. After having recruited 23 participants, we found two preferred presets to tackle this task. With both presets, the usage of color, depth, and opacity improved the display of the organ bounds while contrasting the tumor and calyx. 19 participants successfully completed the task using MODELAR. Their preference was to either find a good preset where the organ bounds were visible then adjust the color of target objects or vice versa. MODELAR helped us better identify effective visualization that best fit the task requirements. Our evaluation results and the modular framework MODELAR is freely available and open source at https://github.com/ghattab/MODELAR.
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    Comprehensive Visualization of Longitudinal Patient Data for the Dermatological Oncological Tumor Board
    (The Eurographics Association, 2020) Steinhauer, Nastasja; Hörbrugger, Marc; Braun, Andreas Dominik; Tüting, Thomas; Oeltze-Jafra, Steffen; Müller, Juliane; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    In multidisciplinary oncological team meetings for patient-specific treatment decision-making, so-called tumor boards, usually one physician introduces a patient case verbally and proposes an initial therapy recommendation. This is followed by a short collaborative discussion of the recommendation's suitability. While patient-related image data, such as CT and MR scans, are displayed during the discussion, clinical patient data must be memorized from the introduction or repeatedly inquired by the participating domain experts. To support physicians in this concern, we propose a comprehensive visualization of longitudinal patient-specific information entities during case introduction and discussion. Our visual approach advances over existing work by simultaneously providing an overview of the current patient status as well as of previous therapy measures and their effects on the status. The latter assists in relating the currently proposed recommendation to the previous treatment measures and the related patient status. The visualization has been designed in close collaboration with dermatologists and oncologists aiming at a comprehensive yet easily comprehensible presentation of relevant patient-data and minimal user interaction. The usability and clinical relevance of the prototypical implementation of our visual approach have been evaluated in a qualitative user study with five domain experts based on real anonymized data of melanoma patients.
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    RankBooster: Visual Analysis of Ranking Predictions
    (The Eurographics Association, 2020) Puri, Abishek; Ku, Bon Kyung; Wang, Yong; Qu, Huamin; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    Ranking is a natural and ubiquitous way to facilitate decision-making in various applications. However, different rankings are often used for the same set of entities, with each ranking method placing emphasis on different factors. These factors can also be multi-dimensional in nature, compounding the problem. This complexity can make it challenging for an entity which is being ranked to understand what they can do to improve their rankings, and to analyze the effect of changes in various factors to their overall rank. In this paper, we present RankBooster, a novel visual analytics system to help users conveniently investigate ranking predictions.We take university rankings as an example and focus on helping universities to better explore their rankings, where they can compare themselves to their rivals in key areas as well as overall. Novel visualizations are proposed to enable efficient analysis of rankings, including a Scenario Analysis View to show a high-level summary of different ranking scenarios, a Relationship View to visualize the influence of each attribute on different indicators and a Rival View to compare the ranking of a university and those of its rivals. A case study demonstrates the usefulness and effectiveness of RankBooster in facilitating the visual analysis of ranking predictions and helping users better understand their current situation.
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    Visualising Collocation for Close Writing
    (The Eurographics Association, 2020) Roberts, Jonathan C.; Butcher, Peter W. S.; Lew, Robert; Rees, Geraint Paul; Sharma, Nirwan; Frankenberg-Garcia, Ana; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    We present how we have developed a visualisation tool and text editor to display collocations for the purpose of close writing. Collocations are words that combine together in a natural way. Our design study approach brought together a collaboration of experts in lexicography, language learning, and visualisation, starting with low-fidelity prototypes before developing fuller functional systems. We studied the challenge of how to visualise collocations, such to help language learners write more effectively. We have co-created (i) an expert-curated dataset of over 30,000 collocations, (ii) developed a text-editor which performs word analysis, and recommends collocations, and (iii) created several in-situ visualisations linked to the editor, to help users visualise and lookup collocations, and view example sentences. Every stage of development has been evaluated with language learners and other potential users, which has positively improved its design and functionality.