Norrköping, Sweden, May 25-29, 2020 (Virtual)


Visual Analytics Methods and Applications
SpatialRugs: Enhancing Spatial Awareness of Movement in Dense Pixel Visualizations
Juri F. Buchmüller, Udo Schlegel, Eren Cakmak, Daniel A. Keim, and Evanthia Dimara
SepEx: Visual Analysis of Class Separation Measures
Jürgen Bernard, Marco Hutter, Matthias Zeppelzauer, Michael Sedlmair, and Tamara Munzner
Dual Radial Set
Kresimir Matkovic, Denis Gracanin, Matea Bardun, Rainer Splechtna, and Helwig Hauser
An Exploratory Visual Analytics Tool for Multivariate Dynamic Networks
Hasan Alp Boz, Mohsen Bahrami, Yoshihiko Suhara, Burcin Bozkaya, and Selim Balcisoy
DualNetView: Dual Views for Visualizing the Dynamics of Networks
Vung Pham, V. T. Ngan Nguyen, and Tommy Dang
Visual Analysis of High Dimensional and Temporal Data
Quality Metrics to Guide Visual Analysis of High Dimensional Genomics Data
Sara Johansson Fernstad, Alexander Macquisten, Janet Berrington, Nicholas Embleton, and Christopher Stewart
Enhanced Attribute-Based Explanations of Multidimensional Projections
Daan van Driel, Xiaorui Zhai, Zonglin Tian, and Alexandru Telea
Progressive Parameter Space Visualization for Task-Driven SAX Configuration
Sebastian Loeschcke, Marius Hogräfer, and Hans-Jörg Schulz
Congnostics: Visual Features for Doubly Time Series Plots
Bao Dien Quoc Nguyen, Rattikorn Hewett, and Tommy Dang
A Window-based Approach for Mining Long Duration Event-sequences
Katerina Vrotsou and Aida Nordman
Intersecting Humans and AI
Learning and Teaching in Co-Adaptive Guidance for Mixed-Initiative Visual Analytics
Fabian Sperrle, Astrik Jeitler, Jürgen Bernard, Daniel A. Keim, and Mennatallah El-Assady
A Generic Model for Projection Alignment Applied to Neural Network Visualization
Gabriel Dias Cantareira and Fernando V. Paulovich
Visual Analysis for Hospital Infection Control using a RNN Model
Martin Müller, Markus Petzold, Marcel Wunderlich, Tom Baumgartl, Markus Höhn, Vanessa Eichel, Nico T. Mutters, Simone Scheithauer, Michael Marschollek, and Tatiana von Landesberger
Interactive Visualization of AI-based Speech Recognition Texts
Tsung Heng Wu, Ye Zhao, and Md Amiruzzaman

Recent Submissions

  • Interactive Visualization of AI-based Speech Recognition Texts 

    Wu, Tsung Heng; Zhao, Ye; Amiruzzaman, Md (The Eurographics Association, 2020)
    Speech recognition technology has achieved impressive success recently with AI techniques of deep learning networks. Speechto- text tools are becoming prevalent in many social applications such as field surveys. However, ...
  • Visual Analysis for Hospital Infection Control using a RNN Model 

    Müller, Martin; Petzold, Markus; Wunderlich, Marcel; Baumgartl, Tom; Höhn, Markus; Eichel, Vanessa; Mutters, Nico T.; Scheithauer, Simone; Marschollek, Michael; Landesberger, Tatiana von (The Eurographics Association, 2020)
    Bacteria and viruses are transmitted among patients in the hospital. Infection control experts develop strategies for infection control. Currently, this is done mostly manually, which is time-consuming and error-prone. ...
  • A Generic Model for Projection Alignment Applied to Neural Network Visualization 

    Cantareira, Gabriel Dias; Paulovich, Fernando V. (The Eurographics Association, 2020)
    Dimensionality reduction techniques are popular tools for the visualization of neural network models due to their ability to display hidden layer activations and aiding the understanding of how abstract representations are ...
  • Learning and Teaching in Co-Adaptive Guidance for Mixed-Initiative Visual Analytics 

    Sperrle, Fabian; Jeitler, Astrik; Bernard, Jürgen; Keim, Daniel A.; El-Assady, Mennatallah (The Eurographics Association, 2020)
    Guidance processes in visual analytics applications often lack adaptivity. In this position paper, we contribute the concept of co-adaptive guidance, building on the principles of initiation and adaptation. We argue that ...
  • A Window-based Approach for Mining Long Duration Event-sequences 

    Vrotsou, Katerina; Nordman, Aida (The Eurographics Association, 2020)
    This paper presents an interactive sequence mining approach for exploring long duration event-sequences and identifying interesting patterns within them. The approach extends previous work on exploratory sequence mining ...
  • Congnostics: Visual Features for Doubly Time Series Plots 

    Nguyen, Bao Dien Quoc; Hewett, Rattikorn; Dang, Tommy (The Eurographics Association, 2020)
    In this paper, we propose an analytical approach to automatically extract visual features from doubly time series capturing the unusual associations which are not otherwise possible by investigating individual time series ...
  • Enhanced Attribute-Based Explanations of Multidimensional Projections 

    Driel, Daan van; Zhai, Xiaorui; Tian, Zonglin; Telea, Alexandru (The Eurographics Association, 2020)
    Multidimensional projections (MPs) are established tools for exploring the structure of high-dimensional datasets to reveal groups of similar observations. For optimal usage, MPs can be augmented with mechanisms that explain ...
  • Quality Metrics to Guide Visual Analysis of High Dimensional Genomics Data 

    Fernstad, Sara Johansson; Macquisten, Alexander; Berrington, Janet; Embleton, Nicholas; Stewart, Christopher (The Eurographics Association, 2020)
    Studies of genome sequenced data are increasingly common in many domains. Technological advances enable detection of hundreds of thousands of biological entities in samples, resulting in extremely high dimensional data. ...
  • Progressive Parameter Space Visualization for Task-Driven SAX Configuration 

    Loeschcke, Sebastian; Hogräfer, Marius; Schulz, Hans-Jörg (The Eurographics Association, 2020)
    As time series datasets are growing in size, data reduction approaches like PAA and SAX are used to keep them storable and analyzable. Yet, finding the right trade-off between data reduction and remaining utility of the ...
  • An Exploratory Visual Analytics Tool for Multivariate Dynamic Networks 

    Boz, Hasan Alp; Bahrami, Mohsen; Suhara, Yoshihiko; Bozkaya, Burcin; Balcisoy, Selim (The Eurographics Association, 2020)
    Visualizing multivariate dynamic networks is a challenging task. The evolution of the dynamic network within the temporal axis must be depicted in conjunction with the associated multivariate attributes. In this paper, an ...
  • DualNetView: Dual Views for Visualizing the Dynamics of Networks 

    Pham, Vung; Nguyen, V. T. Ngan; Dang, Tommy (The Eurographics Association, 2020)
    The force-directed layout is a popular visual method for revealing network structures, such as clusters and important vertices. However, it is not capable of representing temporal patterns, such as how clusters/communities ...
  • Dual Radial Set 

    Matkovic, Kresimir; Gracanin, Denis; Bardun, Matea; Splechtna, Rainer; Hauser, Helwig (The Eurographics Association, 2020)
    Set-typed data visualizations require novel interactive representations, especially when visualizing multiple set-typed data attributes. The challenge is how to effectively analyze relations between data elements from ...
  • SpatialRugs: Enhancing Spatial Awareness of Movement in Dense Pixel Visualizations 

    Buchmüller, Juri F.; Schlegel, Udo; Cakmak, Eren; Keim, Daniel A.; Dimara, Evanthia (The Eurographics Association, 2020)
    Compact visual summaries of spatio-temporal movement data often strive to express accurate positions of movers. We present SpatialRugs, a technique to enhance the spatial awareness of movements in dense pixel visualizations. ...
  • SepEx: Visual Analysis of Class Separation Measures 

    Bernard, Jürgen; Hutter, Marco; Zeppelzauer, Matthias; Sedlmair, Michael; Munzner, Tamara (The Eurographics Association, 2020)
    Class separation is an important concept in machine learning and visual analytics. However, the comparison of class separation for datasets with varying dimensionality is non-trivial, given a) the various possible structural ...
  • EuroVa 2020: Frontmatter 

    Turkay, Cagatay; Vrotsou, Katerina (The Eurographics Association, 2020)