EuroVisPosters2016

Permanent URI for this collection

https://diglib.eg.org/handle/10.2312/15276
Groningen, the Netherlands, 6-10 June 2016
Table of Contents
Posters
Hierarchical Clustering with Multiple-Height Branch-Cut Applied to Short Time-Series Gene Expression Data
[full paper Image] [meta data Image]
Athanasios Vogogias, Jessie Kennedy, and Daniel Archambault
User Interaction Visualization for Design Synthesis
[full paper Image] [meta data Image]
Anet Aselmaa, Yu Song, Richard H. M. Goossens
MetricScalpel: Analyzing Diagnostic Outcomes with Exploratory Data Visualization
[full paper Image] [meta data Image]
Wei Li, Joep Elderman, Erwin Hoogerwoord, Mathias Funk, Aarnout C. Brombacher
When Individual Data Points Matter: Interactively Analysing Classification Landscapes
[full paper Image] [meta data Image]
Bruno Schneider, Sebastian Mittelstädt, and Daniel A. Keim
Quantitative Evaluation for Edge Bundling Based on Structural Aesthetics
[full paper Image] [meta data Image]
Ryosuke Saga
Coloring Interactive Compositional Dot Maps
[full paper Image] [meta data Image]
Martijn Tennekes and Edwin de Jonge
Visual Data Exploration for Balance Quantification During Exergaming
[full paper Image] [meta data Image]
Venustiano Soancatl, J. J. van de Gronde, C. J. C. Lamoth, N. M. Maurits, and Jos B. T. M. Roerdink
Tracking and Visualizing Dynamic Structures in Multichannel EEG Coherence Networks
[full paper Image] [meta data Image]
Chengtao Ji, J. J. van de Gronde, N. M. Maurits, and Jos B. T. M. Roerdink
Transfer Function Optimization Based on a Combined Model of Visibility and Saliency
[full paper Image] [meta data Image]
Shengzhou Luo and John Dingliana
Geometry-Aware Visualization of Performance Data
[full paper Image] [meta data Image]
Tom Vierjahn, Bernd Hentschel, and Torsten W. Kuhlen
Query by Visual Words: Visual Search for Scatter Plot Visualizations
[full paper Image] [meta data Image]
Lin Shao, Timo Schleicher, and Tobias Schreck
Visual Analytics for Fraud Detection: Focusing on Profile Analysis
[full paper Image] [meta data Image]
Roger Almeida Leite, Theresia Gschwandtner, Silvia Miksch, Erich Gstrein, and Johannes Kuntner
Visual Analysis of Text Annotations for Stance Classification with ALVA
[full paper Image] [meta data Image]
Kostiantyn Kucher, Andreas Kerren, Carita Paradis, and Magnus Sahlgren
Interactive Exploration of Student Generated Content presented in Blogs
[full paper Image] [meta data Image]
Ilir Jusufi, Marcelo Milrad, and Xurxo Legaspi
InVITe - Towards Intuitive Visualization of Iterations over Text
[full paper Image] [meta data Image]
Houda Lamqaddam and Jan Aerts
Features vs Prototypes: Amplifying Cognition with Common Data Graphics
[full paper Image] [meta data Image]
M. A. Migut and M. Worring
Large-scale Argument Visualization (LSAV)
[full paper Image] [meta data Image]
Dana Khartabil, S. Wells, and Jessie Kennedy
Visualizing Article Similarities in Wikipedia
[full paper Image] [meta data Image]
Patrick Riehmann, Martin Potthast, Henning Gruendl, Johannes Kiesel, Dean Jürges, Giuliano Castiglia, Bagrat Ter-Akopyan, and Bernd Froehlich
Towards Combining Attribute-based and Time Series-based Visual Querying
[full paper Image] [meta data Image]
David Sessler, Martin Spott, Detlef Nauck, William Harmer, Jörn Kohlhammer, and Jürgen Bernard
Tracking Space-Filling Features by Two-Step Optimization
[full paper Image] [meta data Image]
Andrea Schnorr, Sebastian Freitag, Torsten W. Kuhlen, and Bernd Hentschel
Understanding Networks beyond Overlapping Clusters
[full paper Image] [meta data Image]
Vladimir Guchev, S. Angelini, and G. Amati
Volume Rendering Using Principal Component Analysis
[full paper Image] [meta data Image]
Salaheddin Alakkari and John Dingliana
TaCo: Comparative Visualization of Large Tabular Data
[full paper Image] [meta data Image]
Reem Hourieh, Holger Stitz, Nils Gehlenborg, and Marc Streit
Styrian Diversity Visualisation: Visualising Statistical Open Data with a LeanWeb App and Data Server
[full paper Image] [meta data Image]
Keith Andrews, Thomas Traunmüller, Thomas Wolkinger, Eva Goldgruber, Robert Gutounig, and Julian Ausserhofer
Visualization-Aware Color Design
[full paper Image] [meta data Image]
Danielle Albers Szafir and Michael Gleicher

BibTeX (EuroVisPosters2016)
@inproceedings{
10.2312:eurp.20161128,

booktitle = {
EuroVis 2016 - Posters},

editor = {
Tobias Isenberg and Filip Sadlo
},
title = {{
User Interaction Visualization for Design Synthesis}},

author = {
Aselmaa, Anet
 and 
Song, Yu
 and 
Goossens, Richard H. M.
},
year = {
2016},

publisher = {
The Eurographics Association},


ISSN = {-},
ISBN = {978-3-03868-015-4},

DOI = {
10.2312/eurp.20161128}

}
@inproceedings{
10.2312:eurp.20161127,

booktitle = {
EuroVis 2016 - Posters},

editor = {
Tobias Isenberg and Filip Sadlo
},
title = {{
Hierarchical Clustering with Multiple-Height Branch-Cut Applied to Short Time-Series Gene Expression Data}},

author = {
Vogogias, Athanasios
 and 
Kennedy, Jessie
 and 
Archambault, Daniel
},
year = {
2016},

publisher = {
The Eurographics Association},


ISSN = {-},
ISBN = {978-3-03868-015-4},

DOI = {
10.2312/eurp.20161127}

}
@inproceedings{
10.2312:eurp.20161131,

booktitle = {
EuroVis 2016 - Posters},

editor = {
Tobias Isenberg and Filip Sadlo
},
title = {{
Quantitative Evaluation for Edge Bundling Based on Structural Aesthetics}},

author = {
Saga, Ryosuke
},
year = {
2016},

publisher = {
The Eurographics Association},


ISSN = {-},
ISBN = {978-3-03868-015-4},

DOI = {
10.2312/eurp.20161131}

}
@inproceedings{
10.2312:eurp.20161129,

booktitle = {
EuroVis 2016 - Posters},

editor = {
Tobias Isenberg and Filip Sadlo
},
title = {{
MetricScalpel: Analyzing Diagnostic Outcomes with Exploratory Data Visualization}},

author = {
Li, Wei
 and 
Elderman, Joep
 and 
Hoogerwoord, Erwin
 and 
Funk, Mathias
 and 
Brombacher, Aarnout C.
},
year = {
2016},

publisher = {
The Eurographics Association},


ISSN = {-},
ISBN = {978-3-03868-015-4},

DOI = {
10.2312/eurp.20161129}

}
@inproceedings{
10.2312:eurp.20161130,

booktitle = {
EuroVis 2016 - Posters},

editor = {
Tobias Isenberg and Filip Sadlo
},
title = {{
When Individual Data Points Matter: Interactively Analysing Classification Landscapes}},

author = {
Schneider, Bruno
 and 
Mittelstädt, Sebastian
 and 
Keim, Daniel A.
},
year = {
2016},

publisher = {
The Eurographics Association},


ISSN = {-},
ISBN = {978-3-03868-015-4},

DOI = {
10.2312/eurp.20161130}

}
@inproceedings{
10.2312:eurp.20161135,

booktitle = {
EuroVis 2016 - Posters},

editor = {
Tobias Isenberg and Filip Sadlo
},
title = {{
Transfer Function Optimization Based on a Combined Model of Visibility and Saliency}},

author = {
Luo, Shengzhou
 and 
Dingliana, John
},
year = {
2016},

publisher = {
The Eurographics Association},


ISSN = {-},
ISBN = {978-3-03868-015-4},

DOI = {
10.2312/eurp.20161135}

}
@inproceedings{
10.2312:eurp.20161134,

booktitle = {
EuroVis 2016 - Posters},

editor = {
Tobias Isenberg and Filip Sadlo
},
title = {{
Tracking and Visualizing Dynamic Structures in Multichannel EEG Coherence Networks}},

author = {
Ji, Chengtao
 and 
Gronde, J. J. van de
 and 
Maurits, N. M.
 and 
Roerdink, Jos B. T. M.
},
year = {
2016},

publisher = {
The Eurographics Association},


ISSN = {-},
ISBN = {978-3-03868-015-4},

DOI = {
10.2312/eurp.20161134}

}
@inproceedings{
10.2312:eurp.20161133,

booktitle = {
EuroVis 2016 - Posters},

editor = {
Tobias Isenberg and Filip Sadlo
},
title = {{
Visual Data Exploration for Balance Quantification During Exergaming}},

author = {
Soancatl, Venustiano
 and 
Gronde, J. J. van de
 and 
Lamoth, C. J. C.
 and 
Maurits, N. M.
 and 
Roerdink, Jos B. T. M.
},
year = {
2016},

publisher = {
The Eurographics Association},


ISSN = {-},
ISBN = {978-3-03868-015-4},

DOI = {
10.2312/eurp.20161133}

}
@inproceedings{
10.2312:eurp.20161132,

booktitle = {
EuroVis 2016 - Posters},

editor = {
Tobias Isenberg and Filip Sadlo
},
title = {{
Coloring Interactive Compositional Dot Maps}},

author = {
Tennekes, Martijn
 and 
Jonge, Edwin de
},
year = {
2016},

publisher = {
The Eurographics Association},


ISSN = {-},
ISBN = {978-3-03868-015-4},

DOI = {
10.2312/eurp.20161132}

}
@inproceedings{
10.2312:eurp.20161136,

booktitle = {
EuroVis 2016 - Posters},

editor = {
Tobias Isenberg and Filip Sadlo
},
title = {{
Geometry-Aware Visualization of Performance Data}},

author = {
Vierjahn, Tom
 and 
Hentschel, Bernd
 and 
Kuhlen, Torsten W.
},
year = {
2016},

publisher = {
The Eurographics Association},


ISSN = {-},
ISBN = {978-3-03868-015-4},

DOI = {
10.2312/eurp.20161136}

}
@inproceedings{
10.2312:eurp.20161139,

booktitle = {
EuroVis 2016 - Posters},

editor = {
Tobias Isenberg and Filip Sadlo
},
title = {{
Visual Analysis of Text Annotations for Stance Classification with ALVA}},

author = {
Kucher, Kostiantyn
 and 
Kerren, Andreas
 and 
Paradis, Carita
 and 
Sahlgren, Magnus
},
year = {
2016},

publisher = {
The Eurographics Association},


ISSN = {-},
ISBN = {978-3-03868-015-4},

DOI = {
10.2312/eurp.20161139}

}
@inproceedings{
10.2312:eurp.20161138,

booktitle = {
EuroVis 2016 - Posters},

editor = {
Tobias Isenberg and Filip Sadlo
},
title = {{
Visual Analytics for Fraud Detection: Focusing on Profile Analysis}},

author = {
Leite, Roger Almeida
 and 
Gschwandtner, Theresia
 and 
Miksch, Silvia
 and 
Gstrein, Erich
 and 
Kuntner, Johannes
},
year = {
2016},

publisher = {
The Eurographics Association},


ISSN = {-},
ISBN = {978-3-03868-015-4},

DOI = {
10.2312/eurp.20161138}

}
@inproceedings{
10.2312:eurp.20161140,

booktitle = {
EuroVis 2016 - Posters},

editor = {
Tobias Isenberg and Filip Sadlo
},
title = {{
Interactive Exploration of Student Generated Content presented in Blogs}},

author = {
Jusufi, Ilir
 and 
Milrad, Marcelo
 and 
Legaspi, Xurxo
},
year = {
2016},

publisher = {
The Eurographics Association},


ISSN = {-},
ISBN = {978-3-03868-015-4},

DOI = {
10.2312/eurp.20161140}

}
@inproceedings{
10.2312:eurp.20161137,

booktitle = {
EuroVis 2016 - Posters},

editor = {
Tobias Isenberg and Filip Sadlo
},
title = {{
Query by Visual Words: Visual Search for Scatter Plot Visualizations}},

author = {
Shao, Lin
 and 
Schleicher, Timo
 and 
Schreck, Tobias
},
year = {
2016},

publisher = {
The Eurographics Association},


ISSN = {-},
ISBN = {978-3-03868-015-4},

DOI = {
10.2312/eurp.20161137}

}
@inproceedings{
10.2312:eurp.20161141,

booktitle = {
EuroVis 2016 - Posters},

editor = {
Tobias Isenberg and Filip Sadlo
},
title = {{
InVITe - Towards Intuitive Visualization of Iterations over Text}},

author = {
Lamqaddam, Houda
 and 
Aerts, Jan
},
year = {
2016},

publisher = {
The Eurographics Association},


ISSN = {-},
ISBN = {978-3-03868-015-4},

DOI = {
10.2312/eurp.20161141}

}
@inproceedings{
10.2312:eurp.20161142,

booktitle = {
EuroVis 2016 - Posters},

editor = {
Tobias Isenberg and Filip Sadlo
},
title = {{
Features vs Prototypes: Amplifying Cognition with Common Data Graphics}},

author = {
Migut, M. A.
 and 
Worring, M.
},
year = {
2016},

publisher = {
The Eurographics Association},


ISSN = {-},
ISBN = {978-3-03868-015-4},

DOI = {
10.2312/eurp.20161142}

}
@inproceedings{
10.2312:eurp.20161143,

booktitle = {
EuroVis 2016 - Posters},

editor = {
Tobias Isenberg and Filip Sadlo
},
title = {{
Large-scale Argument Visualization (LSAV)}},

author = {
Khartabil, Dana
 and 
Wells, S.
 and 
Kennedy, Jessie
},
year = {
2016},

publisher = {
The Eurographics Association},


ISSN = {-},
ISBN = {978-3-03868-015-4},

DOI = {
10.2312/eurp.20161143}

}
@inproceedings{
10.2312:eurp.20161146,

booktitle = {
EuroVis 2016 - Posters},

editor = {
Tobias Isenberg and Filip Sadlo
},
title = {{
Tracking Space-Filling Features by Two-Step Optimization}},

author = {
Schnorr, Andrea
 and 
Freitag, Sebastian
 and 
Kuhlen, Torsten W.
 and 
Hentschel, Bernd
},
year = {
2016},

publisher = {
The Eurographics Association},


ISSN = {-},
ISBN = {978-3-03868-015-4},

DOI = {
10.2312/eurp.20161146}

}
@inproceedings{
10.2312:eurp.20161145,

booktitle = {
EuroVis 2016 - Posters},

editor = {
Tobias Isenberg and Filip Sadlo
},
title = {{
Towards Combining Attribute-based and Time Series-based Visual Querying}},

author = {
Sessler, David
 and 
Spott, Martin
 and 
Nauck, Detlef
 and 
Harmer, William
 and 
Kohlhammer, Jörn
 and 
Bernard, Jürgen
},
year = {
2016},

publisher = {
The Eurographics Association},


ISSN = {-},
ISBN = {978-3-03868-015-4},

DOI = {
10.2312/eurp.20161145}

}
@inproceedings{
10.2312:eurp.20161144,

booktitle = {
EuroVis 2016 - Posters},

editor = {
Tobias Isenberg and Filip Sadlo
},
title = {{
Visualizing Article Similarities in Wikipedia}},

author = {
Riehmann, Patrick
 and 
Potthast, Martin
 and 
Gruendl, Henning
 and 
Kiesel, Johannes
 and 
Jürges, Dean
 and 
Castiglia, Giuliano
 and 
Ter-Akopyan, Bagrat
 and 
Froehlich, Bernd
},
year = {
2016},

publisher = {
The Eurographics Association},


ISSN = {-},
ISBN = {978-3-03868-015-4},

DOI = {
10.2312/eurp.20161144}

}
@inproceedings{
10.2312:eurp.20161148,

booktitle = {
EuroVis 2016 - Posters},

editor = {
Tobias Isenberg and Filip Sadlo
},
title = {{
Volume Rendering Using Principal Component Analysis}},

author = {
Alakkari, Salaheddin
 and 
Dingliana, John
},
year = {
2016},

publisher = {
The Eurographics Association},


ISSN = {-},
ISBN = {978-3-03868-015-4},

DOI = {
10.2312/eurp.20161148}

}
@inproceedings{
10.2312:eurp.20161147,

booktitle = {
EuroVis 2016 - Posters},

editor = {
Tobias Isenberg and Filip Sadlo
},
title = {{
Understanding Networks beyond Overlapping Clusters}},

author = {
Guchev, Vladimir
 and 
Angelini, S.
 and 
Amati, G.
},
year = {
2016},

publisher = {
The Eurographics Association},


ISSN = {-},
ISBN = {978-3-03868-015-4},

DOI = {
10.2312/eurp.20161147}

}
@inproceedings{
10.2312:eurp.20161149,

booktitle = {
EuroVis 2016 - Posters},

editor = {
Tobias Isenberg and Filip Sadlo
},
title = {{
TaCo: Comparative Visualization of Large Tabular Data}},

author = {
Hourieh, Reem
 and 
Stitz, Holger
 and 
Gehlenborg, Nils
 and 
Streit, Marc
},
year = {
2016},

publisher = {
The Eurographics Association},


ISSN = {-},
ISBN = {978-3-03868-015-4},

DOI = {
10.2312/eurp.20161149}

}
@inproceedings{
10.2312:eurp.20161150,

booktitle = {
EuroVis 2016 - Posters},

editor = {
Tobias Isenberg and Filip Sadlo
},
title = {{
Styrian Diversity Visualisation: Visualising Statistical Open Data with a LeanWeb App and Data Server}},

author = {
Andrews, Keith
 and 
Traunmüller, Thomas
 and 
Wolkinger, Thomas
 and 
Goldgruber, Eva
 and 
Gutounig, Robert
 and 
Ausserhofer, Julian
},
year = {
2016},

publisher = {
The Eurographics Association},


ISSN = {-},
ISBN = {978-3-03868-015-4},

DOI = {
10.2312/eurp.20161150}

}
@inproceedings{
10.2312:eurp.20161151,

booktitle = {
EuroVis 2016 - Posters},

editor = {
Tobias Isenberg and Filip Sadlo
},
title = {{
Visualization-Aware Color Design}},

author = {
Szafir, Danielle Albers
 and 
Gleicher, Michael
},
year = {
2016},

publisher = {
The Eurographics Association},


ISSN = {-},
ISBN = {978-3-03868-015-4},

DOI = {
10.2312/eurp.20161151}

}

Browse

Recent Submissions

Now showing 1 - 26 of 26
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    Eurovis Posters 2016: Frontmatter
    (Eurographics Association, 2016) Tobias Isenberg; Filip Sadlo;
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    User Interaction Visualization for Design Synthesis
    (The Eurographics Association, 2016) Aselmaa, Anet; Song, Yu; Goossens, Richard H. M.; Tobias Isenberg and Filip Sadlo
    Through the synthesis of gathered user research data, interaction designers are able to generate design proposals. Logging user interactions with a software provides a rich set of data that can give further insights into users' behavior. We present a case study of visualizing interactions log files of the manual tumor contouring task. We identify two types of visualizations needed for comprehending the tumor contouring process. Based on these visualizations, designer was able to gain a holistic view of the process, detailed understanding of the different phases of the task, and identify re-occurring interaction patterns.
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    Hierarchical Clustering with Multiple-Height Branch-Cut Applied to Short Time-Series Gene Expression Data
    (The Eurographics Association, 2016) Vogogias, Athanasios; Kennedy, Jessie; Archambault, Daniel; Tobias Isenberg and Filip Sadlo
    Rigid adherence to pre-specified thresholds and static graphical representations can lead to incorrect decisions on merging of clusters. As an alternative to existing automated or semi-automated methods, we developed a visual analytics approach for performing hierarchical clustering analysis of short time-series gene expression data. Dynamic sliders control parameters such as the similarity threshold at which clusters are merged and the level of relative intra-cluster distinctiveness, which can be used to identify "weak-edges" within clusters. An expert user can drill down to further explore the dendrogram and detect nested clusters and outliers. This is done by using the sliders and by pointing and clicking on the representation to cut the branches of the tree in multiple-heights. A prototype of this tool has been developed in collaboration with a small group of biologists for analysing their own datasets. Initial feedback on the tool has been positive.
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    Quantitative Evaluation for Edge Bundling Based on Structural Aesthetics
    (The Eurographics Association, 2016) Saga, Ryosuke; Tobias Isenberg and Filip Sadlo
    This study proposes a method to evaluate the efficiency of edge bundling. Edge bundling is important to improve visual clutter of edge visualization. However, the evaluation of edge bundling is based only on qualitative evaluations, and the evaluation cost is expensive. Therefore, this paper proposes three measurement strategies to evaluate edge bundling, namely, the edge lengths before and after edge bundling, occupation area, and edge density.
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    MetricScalpel: Analyzing Diagnostic Outcomes with Exploratory Data Visualization
    (The Eurographics Association, 2016) Li, Wei; Elderman, Joep; Hoogerwoord, Erwin; Funk, Mathias; Brombacher, Aarnout C.; Tobias Isenberg and Filip Sadlo
    Healthcare data is the emerging force to push ahead smarter clinical solutions. However, unforeseen challenges like unmanaged massive data and costly access to it make it difficult for domain experts to easily derive actionable insights. In collaboration with a local diagnostic service provider, we designed MetricScalpel, a web-based visualization tool to help people quickly look into the real-life diagnostic data in the local community. The tool enables swift exploration into the multivariate diagnostic data sets from different sources and facilitates data selection/subsetting for deeper analysis. It can be used to reveal overlooked health conditions on almost any level without the requirement of heavy technical knowledge. Such design makes it easier to be accepted by a wider user group in the healthcare related organizations. It was proven to well serve the domain experts in validating pre-exist hypotheses in cohort analysis as well as revealing undiscovered patterns of health conditions in the local community. External evaluation shows operation cost was remarkably confined as domain experts were assisted with direct and intuitive access to the relevant data in need.
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    When Individual Data Points Matter: Interactively Analysing Classification Landscapes
    (The Eurographics Association, 2016) Schneider, Bruno; Mittelstädt, Sebastian; Keim, Daniel A.; Tobias Isenberg and Filip Sadlo
    The selection of classification models among several options with similar accuracy cannot be done through purely automated methods, and especially in scenarios in which the cost of misclassified instances is crucial, such as criminal intelligence analysis. To tackle this problem and illustrate our ideas, we developed a prototype for the visualization and comparison of classification landscapes. In our system, the same data is given to different classification models. Classification landscapes are shown in the scatter plots, together with their geographical location on a map and detailed textual description for each data record. To enhance model comparison, we implemented interactive anchor-points selection in classification landscapes. Using those anchors, the user can manipulate and reproject the model results in order to get more comparable classification landscapes. We provided a use case with crime data, for crime intelligence analysis.
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    Transfer Function Optimization Based on a Combined Model of Visibility and Saliency
    (The Eurographics Association, 2016) Luo, Shengzhou; Dingliana, John; Tobias Isenberg and Filip Sadlo
    We present an automated technique to optimize the clarity of features in visualizations of 3D volume datasets. By adjusting the opacity transfer function, we achieve user-specified target distributions of feature conspicuity. Unlike previous techniques our approach accounts for both the issues of view-dependent occlusion and visual saliency of features in volume data. We demonstrate how the automated approach is useful in particular for optimizing the visualization of time-varying volume datasets.
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    Tracking and Visualizing Dynamic Structures in Multichannel EEG Coherence Networks
    (The Eurographics Association, 2016) Ji, Chengtao; Gronde, J. J. van de; Maurits, N. M.; Roerdink, Jos B. T. M.; Tobias Isenberg and Filip Sadlo
    An electroencephalography (EEG) coherence network represents functional brain connectivity, and is constructed by calculating the coherence between pairs of electrode signals as a function of frequency. Visualization of coherence networks can provide insight into unexpected patterns of cognitive processing and help neuroscientists understand brain mechanisms. However, most studies have been limited to static EEG coherence networks or were focused on individual network nodes. In this poster, we consider groups of nodes for visualizing the evolution of network communities and their corresponding spatial location. We use a timeline-based representation to provide an overview of the evolution of functional units (FUs) and their corresponding spatial location over time. This representation can help the viewer identify functional units across the whole time window, as well as to identify relations between functional units and brain regions. In addition, a time-annotated FU map is provided to facilitate comparison of the behavior of the nodes between consecutive FU maps. This time-annotated FU map provides more detail about how the classification of electrodes into FUs changes over time. Our method is proposed as a first step towards a complete analysis of EEG coherence networks.
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    Visual Data Exploration for Balance Quantification During Exergaming
    (The Eurographics Association, 2016) Soancatl, Venustiano; Gronde, J. J. van de; Lamoth, C. J. C.; Maurits, N. M.; Roerdink, Jos B. T. M.; Tobias Isenberg and Filip Sadlo
    Recently, digital games controlled by real-time body movements (exergames) have been proposed as an innovative method to improve balance among older adults. One of the main challenges for exergames is to automatically quantify balance during game-play to adapt the game difficulty according to the skills of the player. Here we perform a multidimensional exploratory data analysis, using visualization and force plate data, to establish suitable measures for quantifying balance in real-time. Our visualizations provide quick insight and directions for further data exploration. They suggest that speed, curvature, the root mean square of the mediolateral displacement of the center of pressure, and a turbulence measure are the most promising measures for balance quantification. The next step is to apply the present techniques to data of whole body movements as recorded by devices such as Kinect, that are available for gameplay at home.
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    Coloring Interactive Compositional Dot Maps
    (The Eurographics Association, 2016) Tennekes, Martijn; Jonge, Edwin de; Tobias Isenberg and Filip Sadlo
    We propose an algorithmic color scheme for zoom-able compositional dot maps. Contrary to existing methods, it uses density, composition, and zoom level to color the pixels of the resulting dot map. We describe the method and its application.
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    Geometry-Aware Visualization of Performance Data
    (The Eurographics Association, 2016) Vierjahn, Tom; Hentschel, Bernd; Kuhlen, Torsten W.; Tobias Isenberg and Filip Sadlo
    Phenomena in the performance behaviour of high-performance computing (HPC) applications can stem from the HPC system itself, from the application's code, but also from the simulation domain. In order to analyse the latter phenomena, we propose a system that visualizes profile-based performance data in its spatial context, i.e., on the geometry, in the simulation domain. It thus helps HPC experts but also simulation experts understand the performance data better. In addition, our tool reduces the initially large search space by automatically labelling large-variation views on the data which require detailed analysis.
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    Visual Analysis of Text Annotations for Stance Classification with ALVA
    (The Eurographics Association, 2016) Kucher, Kostiantyn; Kerren, Andreas; Paradis, Carita; Sahlgren, Magnus; Tobias Isenberg and Filip Sadlo
    The automatic detection and classification of stance taking in text data using natural language processing and machine learning methods create an opportunity to gain insight about the writers' feelings and attitudes towards their own and other people's utterances. However, this task presents multiple challenges related to the training data collection as well as the actual classifier training. In order to facilitate the process of training a stance classifier, we propose a visual analytics approach called ALVA for text data annotation and visualization. Our approach supports the annotation process management and supplies annotators with a clean user interface for labeling utterances with several stance categories. The analysts are provided with a visualization of stance annotations which facilitates the analysis of categories used by the annotators. ALVA is already being used by our domain experts in linguistics and computational linguistics in order to improve the understanding of stance phenomena and to build a stance classifier for applications such as social media monitoring.
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    Visual Analytics for Fraud Detection: Focusing on Profile Analysis
    (The Eurographics Association, 2016) Leite, Roger Almeida; Gschwandtner, Theresia; Miksch, Silvia; Gstrein, Erich; Kuntner, Johannes; Tobias Isenberg and Filip Sadlo
    Financial institutions are always interested in ensuring security and quality for their customers. Banks, for instance, need to identify and avoid harmful transactions. In order to detect fraudulent operations, data mining techniques based on customer profile generation and verification are commonly used. However, these approaches are not supported by Visual Analytics techniques yet. We propose a Visual Analytics approach for supporting and fine-tuning profile analysis and reducing false positive alarms.
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    Interactive Exploration of Student Generated Content presented in Blogs
    (The Eurographics Association, 2016) Jusufi, Ilir; Milrad, Marcelo; Legaspi, Xurxo; Tobias Isenberg and Filip Sadlo
    Nowadays blogs are regarded as tools for communication as well as an important source for spreading information in almost every subject. In recent years, school teachers have started to take advantage of this technology in order to support their educational practices. In this paper we focus on the data generated by a project involving more than 50 Swedish schools where teachers and pupils are posting content related to their astronomy class activities in their blogs with the aims of improving the teaching process. The challenge here is to find suitable methods to explore all these blogs in an interactive and discovery fashion. Our proposed solution to this challenge is to provide a visual and interactive tool for the exploration of blog corpora by teachers, pupils, project managers and parents.
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    Query by Visual Words: Visual Search for Scatter Plot Visualizations
    (The Eurographics Association, 2016) Shao, Lin; Schleicher, Timo; Schreck, Tobias; Tobias Isenberg and Filip Sadlo
    Finding interesting views in large collections of data visualizations, e.g., scatter plots, is challenging. Recently, ranking views based on heuristic quality measures has been proposed. However, quality measures may fail to reflect given user interest, since interestingness is strongly dependent on the application domain and user context. As an alternative, interactive exploration in combination with example based user queries can be used to find patterns of interest. We introduce a novel approach for searching in large sets of scatter plot views based on a dictionary of frequent local scatter plot patterns. The dictionary is used for interactive construction of scatter plot queries, taking into account similarity of local scatter plot patterns as well as their approximate location in the plot. We introduce the overall approach, present a glyph design for visualization of dictionary entries, and illustrate the applicability of our implementation.
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    InVITe - Towards Intuitive Visualization of Iterations over Text
    (The Eurographics Association, 2016) Lamqaddam, Houda; Aerts, Jan; Tobias Isenberg and Filip Sadlo
    With InVITe, we are working towards intuitive visualization to support review of iterative modifications on text documents. In order to accomplish this, we perform simple matching of text snippets between the two versions of text, across a large range of parameter settings. Next, an overview graphic indicating the effect of parameter space on the output allows the user to select those combinations that are of interest. Finally, such selection will display an alluvial diagram with annotations and covering different resolutions. With this tool, co-authors can keep an overview of changes made, both structural and local.
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    Features vs Prototypes: Amplifying Cognition with Common Data Graphics
    (The Eurographics Association, 2016) Migut, M. A.; Worring, M.; Tobias Isenberg and Filip Sadlo
    The most common and important data visualizations, such as barcharts or scatterplots are typically feature-based. In this paper we question whether feature-based representations are favorable from the cognition point of view. We show through the examples how the notion of prototypes can be introduced and discuss based on Card's taxonomy how feature- and prototypebased representations amplify cognition.
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    Large-scale Argument Visualization (LSAV)
    (The Eurographics Association, 2016) Khartabil, Dana; Wells, S.; Kennedy, Jessie; Tobias Isenberg and Filip Sadlo
    Arguments are structures of premises and conclusions that underpin rational reasoning processes. Within complex knowledge domains, especially if they are contentious, argument structures can become large and complex. Visualization tools have been developed that support argument analysts and help them to work with arguments. Until recently, arguments were manually analyzed from natural language text, or constructed from scratch, but new communication modes mean that increasing amounts of debate and the arguments therein can be captured digitally. Furthermore, new tools and techniques for argument mining are beginning to automate the process of extracting argument structure from natural language; leading to much larger argument datasets that present problems for the current generation of argument visualization tools. Additionally, individual argument analysts have different foci which can lead to increased complexity within datasets, and additional facets that argument visualizations should account for but do not. We propose a tool for interacting with argument corpora that enable users to explore and understand the reasoning structure of large-scale arguments. The tool will support a range of interactivity techniques and will help users to explore and analyse large-scale arguments, to more rapidly comprehend complex new problem domains.
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    Tracking Space-Filling Features by Two-Step Optimization
    (The Eurographics Association, 2016) Schnorr, Andrea; Freitag, Sebastian; Kuhlen, Torsten W.; Hentschel, Bernd; Tobias Isenberg and Filip Sadlo
    We present a novel approach for tracking space-filling features, i.e., a set of features covering the entire domain. The assignment between successive time steps is determined by a two-step, global optimization scheme. First, a maximum-weight, maximal matching on a bi-partite graph is computed to provide one-to-one assignments between features of successive time steps. Second, events are detected in a subsequent step; here the matching step serves to restrict the exponentially large set of potential solutions. To this end, we compute an independent set on a graph representing conflicting event explanations. The method is evaluated by tracking dissipation elements, a structure definition from turbulent flow analysis.
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    Towards Combining Attribute-based and Time Series-based Visual Querying
    (The Eurographics Association, 2016) Sessler, David; Spott, Martin; Nauck, Detlef; Harmer, William; Kohlhammer, Jörn; Bernard, Jürgen; Tobias Isenberg and Filip Sadlo
    We present a concept for the visual-interactive definition of meaningful subsets in data sets comprising multivariate attributes and time series data. Based on a generalization of requirements of a real-world user group, we propose a three-stage approach, combining visual-interactive querying, query filter analysis, and result exploration. The approach includes several design parameters that can easily be adapted in future design studies for alternative applications.
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    Visualizing Article Similarities in Wikipedia
    (The Eurographics Association, 2016) Riehmann, Patrick; Potthast, Martin; Gruendl, Henning; Kiesel, Johannes; Jürges, Dean; Castiglia, Giuliano; Ter-Akopyan, Bagrat; Froehlich, Bernd; Tobias Isenberg and Filip Sadlo
    In this poster we present intermediate results regarding visual text analytics on Wikipedia. We implemented a visualization providing insight about similarities among Wikipedia articles in terms of structure as well as content. The presented data was gathered and processed via a pairwise comparison of all Wikipedia articles. Comparisons were appropriately pruned due to time and memory reasons when providing our in-memory database with the computed similarity values for visualization.
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    Volume Rendering Using Principal Component Analysis
    (The Eurographics Association, 2016) Alakkari, Salaheddin; Dingliana, John; Tobias Isenberg and Filip Sadlo
    We investigate the use of Principal Component Analysis (PCA) for image-based volume rendering. We compute an eigenspace using training images, pre-rendered using a standard raycaster, from a spherically distributed range of camera positions. Our system is then able to synthesize novel views of the data set with minimal computation at run time. Results indicate that PCA is able to sufficiently learn the full volumetric model through a finite number of training images and generalize the computed eigenspace to produce high quality novel view images.
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    Understanding Networks beyond Overlapping Clusters
    (The Eurographics Association, 2016) Guchev, Vladimir; Angelini, S.; Amati, G.; Tobias Isenberg and Filip Sadlo
    Tasks associated with the investigation of large complex clustered networks are widespread in various research areas. Among the popular and common approaches to exploratory analysis, it is definitely worthwhile to underscore the node-link-based graph visualization. However, despite the prevalence of node-link-based tools, its graphic design and geometric representation of topology almost invariably formed by a spontaneous spatial structure, or on the contrary, by a too rigidly ordered arrangement. Transformation possibilities of multivariate data structures may allow finding a suitable graphic balance between optic chaos and visual primitiveness by the use of partially ordered sets for grouping. By taking the studying of Twitter communities as a task, the paper presents a data modelling method in conjunction with a set of visualization techniques, which implement a convenient and perceivable interactive toolset for analytical exploration of overlapping network clusters.
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    TaCo: Comparative Visualization of Large Tabular Data
    (The Eurographics Association, 2016) Hourieh, Reem; Stitz, Holger; Gehlenborg, Nils; Streit, Marc; Tobias Isenberg and Filip Sadlo
    Tabular data plays a vital role in many different domains. In the course of a project, changes to the structure and content of tables can result in multiple instances of a table. A challenging task when working with such derived tables is to understand what exactly has changed from one version to another. Traditional comparison tools assist users in inspecting differences between multiple table instances, however, the resulting visualizations are often hard to interpret or do not scale to large tables with thousands of rows and columns. To address these challenges, we developed TaCo, an interactive comparison tool that effectively visualizes the differences between multiple tables at various levels of granularity: (1) the aggregated differences between all table instances, (2) the differences between one table compared to all others, and (3) the detailed differences between two instances.
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    Styrian Diversity Visualisation: Visualising Statistical Open Data with a LeanWeb App and Data Server
    (The Eurographics Association, 2016) Andrews, Keith; Traunmüller, Thomas; Wolkinger, Thomas; Goldgruber, Eva; Gutounig, Robert; Ausserhofer, Julian; Tobias Isenberg and Filip Sadlo
    Statistical open data is usually provided only in the form of spreadsheets or CSV files. The developers of open data apps must either restrict themselves to managable bite-sized chunks of data, which can be consumed (read, parsed, and held in memory) in one go, or must install and maintain their own data server which the app can query on demand. The Styrian Diversity Visualisation (in German ''Steirische Vielfalt Visualisiert'' or SVV) project demonstrates the use of a dedicated data server (triple store) to host large amounts of statistical open data. The SVV web app queries the data server dynamically using SPARQL queries to obtain exactly the data required at that particular time, greatly simplifying its internal logic. There is no need to parse and store entire data sets in memory.
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    Visualization-Aware Color Design
    (The Eurographics Association, 2016) Szafir, Danielle Albers; Gleicher, Michael; Tobias Isenberg and Filip Sadlo
    Color encoding design currently focuses on the colors themselves: visualization designers choose sets of colors that work well in isolation. However, the effectiveness of a color encoding depends on properties of the visualization it is used for, such as the size or shape of marks. We argue for a new way of thinking about color design in visualizations: designers should choose colors based on a given context rather than in isolation. We identify three categories of design constraints that contribute to the effective color choices in visualization: aesthetic constraints, perceptual constraints, and functional constraints. The conceptual framework formed by these constraints helps designers optimize color choices based on known properties of a given visualization. In this poster, we discuss this framework in detail and illustrate how it informs more effective visualization design.