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  • LFPeers: Temporal Similarity Search in Covid-19 Data 

    Burmeister, Jan; Bernard, Jürgen; Kohlhammer, Jörn (The Eurographics Association, 2021)
    While there is a wide variety of visualizations and dashboards to help understand the data of the Covid-19 pandemic, hardly any of these support important analytical tasks, especially of temporal attributes. In this paper, ...
  • Towards the Detection and Visual Analysis of COVID-19 Infection Clusters 

    Antweiler, Dario; Sessler, David; Ginzel, Sebastian; Kohlhammer, Jörn (The Eurographics Association, 2021)
    A major challenge for departments of public health (DPHs) in dealing with the ongoing COVID-19 pandemic is tracing contacts in exponentially growing SARS-CoV2 infection clusters. Prevention of further disease spread requires ...
  • Multi-resolution Analysis for Vector Plots of Time Series Data 

    Nguyen, Bao; Hewett, Rattikorn; Dang, Tommy (The Eurographics Association, 2021)
    Vector plots can directly visualize both temporal variation and spatial distribution, so it is interesting to use this type of plot for displaying multivariate time series. However, vector plots cannot reveal global temporal ...
  • Rumble Flow++ Interactive Visual Analysis of Dota2 Encounters 

    Weixelbaum, Wilma; Matkovic, Kresimir (The Eurographics Association, 2021)
    In the last decade, the popularity of ESports has grown rapidly. The financial leader in the tournament scene is Dota2, a complex and strategic multiplayer game. Analysis and exploration of game data could lead to better ...
  • A Taxonomy of Attribute Scoring Functions 

    Schmid, Jenny; Bernard, Jürgen (The Eurographics Association, 2021)
    Shifting the analysis from items to the granularity of attributes is a promising approach to address complex decision-making problems. In this work, we study attribute scoring functions (ASFs), which transform values from ...
  • Customizable Coordination of Independent Visual Analytics Tools 

    Nonnemann, Lars; Hogräfer, Marius; Schumann, Heidrun; Urban, Bodo; Schulz, Hans-Jörg (The Eurographics Association, 2021)
    While it is common to use multiple independent analysis tools in combination, it is still cumbersome to carry out a cross-tool visual analysis. Some dedicated frameworks addressing this issue exist, yet in order to use ...
  • Lessons learned while supporting Cyber Situational Awareness 

    Blasilli, Graziano; Paoli, Emiliano De; Lenti, Simone; Picca, Sergio (The Eurographics Association, 2021)
    The increasing number of cyberattacks against critical infrastructures has pushed researchers to develop many Visual Analytics solutions to provide valid defensive approaches and improve the situational awareness of the ...
  • Immersive Analytics of Heterogeneous Biological Data Informed through Need-finding Interviews 

    Ripken, Christine; Tusk, Sebastian; Tominski, Christian (The Eurographics Association, 2021)
    The goal of this work is to improve existing biological analysis processes by means of immersive analytics. In a first step, we conducted need-finding interviews with 12 expert biologists to understand the limits of current ...
  • Immersive 3D Visualization of Multi-Modal Brain Connectivity 

    Pester, Britta; Winke, Oliver; Ligges, Carolin; Dachselt, Raimund; Gumhold, Stefan (The Eurographics Association, 2021)
    In neuroscience, the investigation of connectivity between different brain regions suffers from the lack of adequate solutions for visualizing detected networks. One reason is the high number of dimensions that have to be ...
  • Talk2Hand: Knowledge Board Interaction in Augmented Reality Easing Analysis with Machine Learning Assistants 

    Hong, Yu-Lun; Watson, Benjamin; Thompson, Kenneth; Davis, Paul (The Eurographics Association, 2021)
    Analysts now often use machine learning (ML) assistants, but find them difficult to use, since most have little ML expertise. Talk2Hand improves the usability of ML assistants by supporting interaction with them using ...
  • EuroVa 2021: Frontmatter 

    Bernard, Jürgen; Vrotsou, Katerina (The Eurographics Association, 2021)
  • 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. ...
  • 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 ...
  • 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 ...
  • 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 ...

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