EuroVisPosters2025

Permanent URI for this collection

EuroVis 2025 - 27th EG Conference on Visualization
Luxembourg City, Luxembourg | June 2 - 6, 2025
Posters
A Method for Optimizing the Rendering Order of Scatterplots
Liqun Liu and Roy A. Ruddle
Automated Refined Comic Generation: From Investigation Provenance to Data Comics using Visual Narrative Structure
Kay Arne Roggenbuck, Anna Vilanova, and Stef van den Elzen
Certainly Uncertain: Reintroducing Uncertainty in Visualizations
Sandhya Rajendran, Alessio Arleo, Silvia Miksch, Michaela Tuscher, and Velitchko Andreev Filipov
Characterizing the Performance of Counterfactual and Correlation Guidance via Dataset Perturbations
Arran Zeyu Wang, David Borland, and David Gotz
Data-driven Education on Biodiversity through Visualizing Spatial Co-occurrence Clusters
Raquel Arguedas, Madhav Poddar, Lilliana Sancho-Chavarria, and Fabian Beck
Differential Gene Expression Analysis with Visual Analytics
Francesco Fortunato, Cristian Santaroni, Graziano Blasilli, Giulia Fiscon, Simone Lenti, and Giuseppe Santucci
Incorporating 3D-Rendered Materials in Visualization
Sotiris Piliouras, Pierre Dragicevic, Michel Beaudouin-Lafon, and Theophanis Tsandilas
MECpace: A Visual Analytics Tool for Comparing Multiple Embedding Spaces
Rachit Joshi, Purva Zinjarde, and Shah Rukh Humayoun
Motivating Through Design: Affective Visualization in mHealth
Go-Un Shin and Sylwia Frankowska-Takhari
OceanInsight: A Marine Waste Visualization Platform Empowering Community-Driven Sustainability and Coastal Cleanup Efforts
Qujing Feng, Gang Xu, Zi Dou, Yushan Pan, Hao Wang, and Di Wu
Pie Chart Glyph Visualization of Uncertain Connected Components
Marina Evers, Farhan Rasheed, Talha Bin Masood, Ingrid Hotz, and Daniel Weiskopf
Reviewer #2: ''Why didn't you use UMAP?''
Diede P. M. van der Hoorn, Alessio Arleo, and Fernando V. Paulovich
ReVISitPy: Python Bindings for the reVISit Study Framework
Hilson Shrestha, Jack Wilburn, Brian Bollen, Andrew M. McNutt, Alexander Lex, and Lane Harrison
Towards a Software Framework for Evaluating the Visualization Literacy of Large Language Models
Adrian Jobst, Daniel Atzberger, Willy Scheibel, and Jürgen Döllner
Towards Scalable Out-of-Core Volume Rendering for High-Performance Visualization of 3D Temporal Multivariate Gas and Fluid Data
Antoine Thebault, Stéphanie Prévost, Laurent Lucas, and Leonardo Brenner
TractMMR: Tractography Streamline Rating through User-guided Matchmaking
Ruben Vink, Anna Vilanova, and Maxime Chamberland
WebGraphViz: A WebGL-Based Interactive Graph Visualization Tool for Retail Analytics
Luis Miguel Aguilar, Ragaad Al-Tarawneh, and Shah Rukh Humayoun
Posters and Demos
A Graph Layout Evaluation System for Communication Graphs
Valentin Schröter, Willy Scheibel, and Jürgen Döllner
Augmented Reality for Training in Small and Medium-Sized Manufacturing Companies
Abdulla A. Ainin, Hatem Algabroun, and Claudio D. G. Linhares
Discussion and Showcase of an Implementation of Task Taxonomies in Visualizations Based on the Dust and Magnet Metaphor
Florence Böttger, Willy Scheibel, and Jürgen Döllner
Fairness-Aware Urban Planning in Sweden: An Interactive Visualization Tool for Equitable Cities
Reem Othman, Benjamin Powley, Rafael M. Martins, Amilcar Soares, Andreas Kerren, Nivan Ferreira, and Claudio D. G. Linhares
Kickin' Scarves: Time-Oriented Visual Comparison of Soccer Trajectories
Tobias Mertz and Jörn Kohlhammer
The Past Is All Around You: Augmenting Cultural Heritage On-Site
Markus Passecker, Silvia Miksch, Franziska Proksa, and Wolfgang Aigner
Towards Met.3D version 2: Creating a community research software for interactive 3-D visualization of meteorological data
Marc Rautenhaus, Christoph Fischer, Thorwin Vogt, and Andreas Beckert
Demos
Visual Analysis of Poker Hands for Individual Players
Konstantin Joachim Dotzler, Shivam Agarwal, and Fabian Beck

BibTeX (EuroVisPosters2025)
@inproceedings{
10.2312:evp.20252010,
booktitle = {
EuroVis 2025 - Posters},
editor = {
Diehl, Alexandra
and
Kucher, Kostiantyn
and
Médoc, Nicolas
}, title = {{
EuroVis 2025 Posters: Frontmatter}},
author = {
Diehl, Alexandra
and
Kucher, Kostiantyn
and
Médoc, Nicolas
}, year = {
2025},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-286-8},
DOI = {
10.2312/evp.20252010}
}
@inproceedings{
10.2312:evp.20251121,
booktitle = {
EuroVis 2025 - Posters},
editor = {
Diehl, Alexandra
and
Kucher, Kostiantyn
and
Médoc, Nicolas
}, title = {{
A Method for Optimizing the Rendering Order of Scatterplots}},
author = {
Liu, Liqun
and
Ruddle, Roy A.
}, year = {
2025},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-286-8},
DOI = {
10.2312/evp.20251121}
}
@inproceedings{
10.2312:evp.20251122,
booktitle = {
EuroVis 2025 - Posters},
editor = {
Diehl, Alexandra
and
Kucher, Kostiantyn
and
Médoc, Nicolas
}, title = {{
Automated Refined Comic Generation: From Investigation Provenance to Data Comics using Visual Narrative Structure}},
author = {
Roggenbuck, Kay Arne
and
Vilanova, Anna
and
Elzen, Stef van den
}, year = {
2025},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-286-8},
DOI = {
10.2312/evp.20251122}
}
@inproceedings{
10.2312:evp.20251123,
booktitle = {
EuroVis 2025 - Posters},
editor = {
Diehl, Alexandra
and
Kucher, Kostiantyn
and
Médoc, Nicolas
}, title = {{
Certainly Uncertain: Reintroducing Uncertainty in Visualizations}},
author = {
Rajendran, Sandhya
and
Arleo, Alessio
and
Miksch, Silvia
and
Tuscher, Michaela
and
Filipov, Velitchko Andreev
}, year = {
2025},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-286-8},
DOI = {
10.2312/evp.20251123}
}
@inproceedings{
10.2312:evp.20251124,
booktitle = {
EuroVis 2025 - Posters},
editor = {
Diehl, Alexandra
and
Kucher, Kostiantyn
and
Médoc, Nicolas
}, title = {{
Characterizing the Performance of Counterfactual and Correlation Guidance via Dataset Perturbations}},
author = {
Wang, Arran Zeyu
and
Borland, David
and
Gotz, David
}, year = {
2025},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-286-8},
DOI = {
10.2312/evp.20251124}
}
@inproceedings{
10.2312:evp.20251125,
booktitle = {
EuroVis 2025 - Posters},
editor = {
Diehl, Alexandra
and
Kucher, Kostiantyn
and
Médoc, Nicolas
}, title = {{
Data-driven Education on Biodiversity through Visualizing Spatial Co-occurrence Clusters}},
author = {
Arguedas, Raquel
and
Poddar, Madhav
and
Sancho-Chavarria, Lilliana
and
Beck, Fabian
}, year = {
2025},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-286-8},
DOI = {
10.2312/evp.20251125}
}
@inproceedings{
10.2312:evp.20251126,
booktitle = {
EuroVis 2025 - Posters},
editor = {
Diehl, Alexandra
and
Kucher, Kostiantyn
and
Médoc, Nicolas
}, title = {{
Differential Gene Expression Analysis with Visual Analytics}},
author = {
Fortunato, Francesco
and
Santaroni, Cristian
and
Blasilli, Graziano
and
Fiscon, Giulia
and
Lenti, Simone
and
Santucci, Giuseppe
}, year = {
2025},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-286-8},
DOI = {
10.2312/evp.20251126}
}
@inproceedings{
10.2312:evp.20251127,
booktitle = {
EuroVis 2025 - Posters},
editor = {
Diehl, Alexandra
and
Kucher, Kostiantyn
and
Médoc, Nicolas
}, title = {{
Incorporating 3D-Rendered Materials in Visualization}},
author = {
Piliouras, Sotiris
and
Dragicevic, Pierre
and
Beaudouin-Lafon, Michel
and
Tsandilas, Theophanis
}, year = {
2025},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-286-8},
DOI = {
10.2312/evp.20251127}
}
@inproceedings{
10.2312:evp.20251128,
booktitle = {
EuroVis 2025 - Posters},
editor = {
Diehl, Alexandra
and
Kucher, Kostiantyn
and
Médoc, Nicolas
}, title = {{
MECpace: A Visual Analytics Tool for Comparing Multiple Embedding Spaces}},
author = {
Joshi, Rachit
and
Zinjarde, Purva
and
Humayoun, Shah Rukh
}, year = {
2025},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-286-8},
DOI = {
10.2312/evp.20251128}
}
@inproceedings{
10.2312:evp.20251129,
booktitle = {
EuroVis 2025 - Posters},
editor = {
Diehl, Alexandra
and
Kucher, Kostiantyn
and
Médoc, Nicolas
}, title = {{
Motivating Through Design: Affective Visualization in mHealth}},
author = {
Shin, Go-Un
and
Frankowska-Takhari, Sylwia
}, year = {
2025},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-286-8},
DOI = {
10.2312/evp.20251129}
}
@inproceedings{
10.2312:evp.20251130,
booktitle = {
EuroVis 2025 - Posters},
editor = {
Diehl, Alexandra
and
Kucher, Kostiantyn
and
Médoc, Nicolas
}, title = {{
OceanInsight: A Marine Waste Visualization Platform Empowering Community-Driven Sustainability and Coastal Cleanup Efforts}},
author = {
Feng, Qujing
and
Xu, Gang
and
Dou, Zi
and
Pan, Yushan
and
Wang, Hao
and
Wu, Di
}, year = {
2025},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-286-8},
DOI = {
10.2312/evp.20251130}
}
@inproceedings{
10.2312:evp.20251131,
booktitle = {
EuroVis 2025 - Posters},
editor = {
Diehl, Alexandra
and
Kucher, Kostiantyn
and
Médoc, Nicolas
}, title = {{
Pie Chart Glyph Visualization of Uncertain Connected Components}},
author = {
Evers, Marina
and
Rasheed, Farhan
and
Masood, Talha Bin
and
Hotz, Ingrid
and
Weiskopf, Daniel
}, year = {
2025},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-286-8},
DOI = {
10.2312/evp.20251131}
}
@inproceedings{
10.2312:evp.20251132,
booktitle = {
EuroVis 2025 - Posters},
editor = {
Diehl, Alexandra
and
Kucher, Kostiantyn
and
Médoc, Nicolas
}, title = {{
Reviewer #2: ''Why didn't you use UMAP?''}},
author = {
Hoorn, Diede P. M. van der
and
Arleo, Alessio
and
Paulovich, Fernando V.
}, year = {
2025},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-286-8},
DOI = {
10.2312/evp.20251132}
}
@inproceedings{
10.2312:evp.20251133,
booktitle = {
EuroVis 2025 - Posters},
editor = {
Diehl, Alexandra
and
Kucher, Kostiantyn
and
Médoc, Nicolas
}, title = {{
ReVISitPy: Python Bindings for the reVISit Study Framework}},
author = {
Shrestha, Hilson
and
Wilburn, Jack
and
Bollen, Brian
and
McNutt, Andrew M.
and
Lex, Alexander
and
Harrison, Lane
}, year = {
2025},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-286-8},
DOI = {
10.2312/evp.20251133}
}
@inproceedings{
10.2312:evp.20251134,
booktitle = {
EuroVis 2025 - Posters},
editor = {
Diehl, Alexandra
and
Kucher, Kostiantyn
and
Médoc, Nicolas
}, title = {{
Towards a Software Framework for Evaluating the Visualization Literacy of Large Language Models}},
author = {
Jobst, Adrian
and
Atzberger, Daniel
and
Scheibel, Willy
and
Döllner, Jürgen
}, year = {
2025},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-286-8},
DOI = {
10.2312/evp.20251134}
}
@inproceedings{
10.2312:evp.20251135,
booktitle = {
EuroVis 2025 - Posters},
editor = {
Diehl, Alexandra
and
Kucher, Kostiantyn
and
Médoc, Nicolas
}, title = {{
Towards Scalable Out-of-Core Volume Rendering for High-Performance Visualization of 3D Temporal Multivariate Gas and Fluid Data}},
author = {
Thebault, Antoine
and
Prévost, Stéphanie
and
Lucas, Laurent
and
Brenner, Leonardo
}, year = {
2025},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-286-8},
DOI = {
10.2312/evp.20251135}
}
@inproceedings{
10.2312:evp.20251136,
booktitle = {
EuroVis 2025 - Posters},
editor = {
Diehl, Alexandra
and
Kucher, Kostiantyn
and
Médoc, Nicolas
}, title = {{
TractMMR: Tractography Streamline Rating through User-guided Matchmaking}},
author = {
Vink, Ruben
and
Vilanova, Anna
and
Chamberland, Maxime
}, year = {
2025},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-286-8},
DOI = {
10.2312/evp.20251136}
}
@inproceedings{
10.2312:evp.20251137,
booktitle = {
EuroVis 2025 - Posters},
editor = {
Diehl, Alexandra
and
Kucher, Kostiantyn
and
Médoc, Nicolas
}, title = {{
WebGraphViz: A WebGL-Based Interactive Graph Visualization Tool for Retail Analytics}},
author = {
Aguilar, Luis Miguel
and
Al-Tarawneh, Ragaad
and
Humayoun, Shah Rukh
}, year = {
2025},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-286-8},
DOI = {
10.2312/evp.20251137}
}
@inproceedings{
10.2312:evp.20251138,
booktitle = {
EuroVis 2025 - Posters},
editor = {
Diehl, Alexandra
and
Kucher, Kostiantyn
and
Médoc, Nicolas
}, title = {{
A Graph Layout Evaluation System for Communication Graphs}},
author = {
Schröter, Valentin
and
Scheibel, Willy
and
Döllner, Jürgen
}, year = {
2025},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-286-8},
DOI = {
10.2312/evp.20251138}
}
@inproceedings{
10.2312:evp.20251139,
booktitle = {
EuroVis 2025 - Posters},
editor = {
Diehl, Alexandra
and
Kucher, Kostiantyn
and
Médoc, Nicolas
}, title = {{
Augmented Reality for Training in Small and Medium-Sized Manufacturing Companies}},
author = {
Ainin, Abdulla A.
and
Algabroun, Hatem
and
Linhares, Claudio D. G.
}, year = {
2025},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-286-8},
DOI = {
10.2312/evp.20251139}
}
@inproceedings{
10.2312:evp.20251140,
booktitle = {
EuroVis 2025 - Posters},
editor = {
Diehl, Alexandra
and
Kucher, Kostiantyn
and
Médoc, Nicolas
}, title = {{
Discussion and Showcase of an Implementation of Task Taxonomies in Visualizations Based on the Dust and Magnet Metaphor}},
author = {
Böttger, Florence
and
Scheibel, Willy
and
Döllner, Jürgen
}, year = {
2025},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-286-8},
DOI = {
10.2312/evp.20251140}
}
@inproceedings{
10.2312:evp.20251141,
booktitle = {
EuroVis 2025 - Posters},
editor = {
Diehl, Alexandra
and
Kucher, Kostiantyn
and
Médoc, Nicolas
}, title = {{
Fairness-Aware Urban Planning in Sweden: An Interactive Visualization Tool for Equitable Cities}},
author = {
Othman, Reem
and
Powley, Benjamin
and
Martins, Rafael M.
and
Soares, Amilcar
and
Kerren, Andreas
and
Ferreira, Nivan
and
Linhares, Claudio D. G.
}, year = {
2025},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-286-8},
DOI = {
10.2312/evp.20251141}
}
@inproceedings{
10.2312:evp.20251142,
booktitle = {
EuroVis 2025 - Posters},
editor = {
Diehl, Alexandra
and
Kucher, Kostiantyn
and
Médoc, Nicolas
}, title = {{
Kickin' Scarves: Time-Oriented Visual Comparison of Soccer Trajectories}},
author = {
Mertz, Tobias
and
Kohlhammer, Jörn
}, year = {
2025},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-286-8},
DOI = {
10.2312/evp.20251142}
}
@inproceedings{
10.2312:evp.20251143,
booktitle = {
EuroVis 2025 - Posters},
editor = {
Diehl, Alexandra
and
Kucher, Kostiantyn
and
Médoc, Nicolas
}, title = {{
The Past Is All Around You: Augmenting Cultural Heritage On-Site}},
author = {
Passecker, Markus
and
Miksch, Silvia
and
Proksa, Franziska
and
Aigner, Wolfgang
}, year = {
2025},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-286-8},
DOI = {
10.2312/evp.20251143}
}
@inproceedings{
10.2312:evp.20251144,
booktitle = {
EuroVis 2025 - Posters},
editor = {
Diehl, Alexandra
and
Kucher, Kostiantyn
and
Médoc, Nicolas
}, title = {{
Towards Met.3D version 2: Creating a community research software for interactive 3-D visualization of meteorological data}},
author = {
Rautenhaus, Marc
and
Fischer, Christoph
and
Vogt, Thorwin
and
Beckert, Andreas
}, year = {
2025},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-286-8},
DOI = {
10.2312/evp.20251144}
}
@inproceedings{
10.2312:evp.20251145,
booktitle = {
EuroVis 2025 - Posters},
editor = {
Diehl, Alexandra
and
Kucher, Kostiantyn
and
Médoc, Nicolas
}, title = {{
Visual Analysis of Poker Hands for Individual Players}},
author = {
Dotzler, Konstantin Joachim
and
Agarwal, Shivam
and
Beck, Fabian
}, year = {
2025},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-286-8},
DOI = {
10.2312/evp.20251145}
}

Browse

Recent Submissions

Now showing 1 - 26 of 26
  • Item
    EuroVis 2025 Posters: Frontmatter
    (The Eurographics Association, 2025) Diehl, Alexandra; Kucher, Kostiantyn; Médoc, Nicolas; Diehl, Alexandra; Kucher, Kostiantyn; Médoc, Nicolas
  • Item
    A Method for Optimizing the Rendering Order of Scatterplots
    (The Eurographics Association, 2025) Liu, Liqun; Ruddle, Roy A.; Diehl, Alexandra; Kucher, Kostiantyn; Médoc, Nicolas
    Rendering order is crucial for generating effective scatterplots, as a rendering sequence can cause anomalous data points to be obscured by others. This issue is particularly significant in the field of explainable artificial intelligence (XAI), where large volumes of data can prevent users from observing misclassified instances. This poster introduces a novel method for sorting data points and rendering them sequentially to reduce the likelihood of anomalous points being hidden. First, we normalize the two coordinates of the scatterplots to mitigate the impact of differing value ranges. Next, we propose a method for calculating the anomaly index of each data point. Finally, we sort the data points based on their anomaly index and render them sequentially.We compare our method with existing approaches on scatterplots generated by dimensionality reduction (DR) techniques applied to a pretrained convolutional neural network (CNN) trained on the MNIST dataset. The results demonstrate that our method enables easier identification of misclassified (anomalous) data points compared to category-based and random rendering orders.
  • Item
    Automated Refined Comic Generation: From Investigation Provenance to Data Comics using Visual Narrative Structure
    (The Eurographics Association, 2025) Roggenbuck, Kay Arne; Vilanova, Anna; Elzen, Stef van den; Diehl, Alexandra; Kucher, Kostiantyn; Médoc, Nicolas
    Visual analytics has become an important approach for criminal investigations due to the increasing amount of physical and digital data related to cases. Although state-of-the-art tools are used daily to search for evidence in the data and report the investigator's findings, building such reports remains a labor-intensive manual process. Furthermore, these reports commonly contain only a manually selected set of the investigation results, but not how these results were derived. This lack of information about the chain of evidence not only weakens reproducibility and transparency, but also makes the evidence vulnerable by jurists in court. Instead of textual reports we believe annotated visuals of the actual data exploration process better portray what the investigators did and how they came to the evidence. To this end, we introduce ARC, a framework for automatically generating comic summaries for digital investigations based on the Visual Narrative Structure from comic theory. Especially, ARC is the first framework that fully automatically generates and refines comic summaries based on interactions with investigation tools.
  • Item
    Certainly Uncertain: Reintroducing Uncertainty in Visualizations
    (The Eurographics Association, 2025) Rajendran, Sandhya; Arleo, Alessio; Miksch, Silvia; Tuscher, Michaela; Filipov, Velitchko Andreev; Diehl, Alexandra; Kucher, Kostiantyn; Médoc, Nicolas
    Information Diffusion (ID) is shaped by uncertainty, yet most visualizations overlook it, leading to oversimplified or misleading interpretations. This work enhances two existing ID visualizations by integrating uncertainty through visual encodings within the original research goals. We are exploring how visualizing uncertainty might influence interpretation, including the potential for signal suppression or amplification. We discuss design alternatives and insights that apply to visualizing uncertainty in two existing visualization techniques. Future work directions are focusing on evaluating the designs and eliciting user feedback and comments on the interpretability and intuitiveness of the proposed uncertainty visualization encodings.
  • Item
    Characterizing the Performance of Counterfactual and Correlation Guidance via Dataset Perturbations
    (The Eurographics Association, 2025) Wang, Arran Zeyu; Borland, David; Gotz, David; Diehl, Alexandra; Kucher, Kostiantyn; Médoc, Nicolas
    Guidance methods are often employed in visual analytics systems to help users navigate complex datasets and discover meaningful insights. Guidance based on correlation is a common method that can steer users towards closely related variables. However, recent work has shown that guidance based on counterfactual subsets can more effectively capture and surface causal relationships. In this work we further explore these guidance methods by characterizing their performance by systematically introducing perturbations in both the data points generated from a ground truth causal graph, and the causal relationships in the graph itself. Our results indicate that while both guidance types exhibit similar sensitivity to global data point perturbations, counterfactual guidance can better capture perturbations affecting only a single dimension, and more effectively reflect changes in causal link strengths, indicating an improved ability to capture narrow data changes and causal relationships.
  • Item
    Data-driven Education on Biodiversity through Visualizing Spatial Co-occurrence Clusters
    (The Eurographics Association, 2025) Arguedas, Raquel; Poddar, Madhav; Sancho-Chavarria, Lilliana; Beck, Fabian; Diehl, Alexandra; Kucher, Kostiantyn; Médoc, Nicolas
    Educational efforts have raised awareness of biodiversity and ecosystems, but tools that enable broad audiences to explore and understand them through data collected by researchers and citizens remain limited. We propose a clustering approach that visually reveals co-occurrences of species from specific sightings. The interface offers two views: one showing co-occurrence clusters in projected space, the other highlighting them on a map.
  • Item
    Differential Gene Expression Analysis with Visual Analytics
    (The Eurographics Association, 2025) Fortunato, Francesco; Santaroni, Cristian; Blasilli, Graziano; Fiscon, Giulia; Lenti, Simone; Santucci, Giuseppe; Diehl, Alexandra; Kucher, Kostiantyn; Médoc, Nicolas
    Differential gene expression (DGE) analysis is one of the most used techniques for RNA-seq data analysis, and it is applied in various medical and biological contexts, including biomarkers for diagnosis and prognosis and evaluation of the effectiveness of specific treatments. The conduction of a DGE analysis typically involves navigating a complex, multi-step pipeline, which usually requires proficiency in programming languages like R. This presents a barrier to researchers like biologists and clinicians, who may have limited or no coding skills, and adds additional overhead even for experienced bioinformaticians. To overcome these challenges, we propose a preliminary visual analytics prototype that simplifies DGE analysis, enabling users to perform the analyses without coding expertise.
  • Item
    Incorporating 3D-Rendered Materials in Visualization
    (The Eurographics Association, 2025) Piliouras, Sotiris; Dragicevic, Pierre; Beaudouin-Lafon, Michel; Tsandilas, Theophanis; Diehl, Alexandra; Kucher, Kostiantyn; Médoc, Nicolas
    We investigate how 3D-rendered materials can support expressive forms of information visualization. We introduce an early snapshot of our design space, describing how inherent material properties and their state or structural transformations can be used as visual channels or simply as contextual attributes for sensory activation. We explore the potential of rendered materials to evoke emotional engagement, curiosity, aesthetic pleasure, and crossmodal sensory experiences.
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    MECpace: A Visual Analytics Tool for Comparing Multiple Embedding Spaces
    (The Eurographics Association, 2025) Joshi, Rachit; Zinjarde, Purva; Humayoun, Shah Rukh; Diehl, Alexandra; Kucher, Kostiantyn; Médoc, Nicolas
    Embeddings play a crucial role in machine learning (ML) by representing high-dimensional data in a lower-dimensional space, enhancing model efficiency and interoperability. Fine-grained analysis of embeddings enables optimization of model architectures, refinement of datasets, and more effective parameter adjustments. We introduce MECpace (Multiple Embedded Comparison Spaces), a web-based visualization tool designed to facilitate the comparison of multiple embedding spaces through intuitive visualizations. MECpace supports rapid comparisons of object neighbors across models using parallel coordinate plots and scatter plots, as well as pairwise comparisons through an integrated matrix-scatter view that combines scatter plots and histograms. Interactive features such as filtering and zooming enable seamless exploration of large datasets. By providing a comprehensive view of embedding similarities across multiple models, MECpace enhances decision-making in the ML pipeline.
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    Motivating Through Design: Affective Visualization in mHealth
    (The Eurographics Association, 2025) Shin, Go-Un; Frankowska-Takhari, Sylwia; Diehl, Alexandra; Kucher, Kostiantyn; Médoc, Nicolas
    Low retention and limited public health impact remain persistent challenges for mobile health (mHealth) apps [MAD*22]. This study explores affective visualization as a solution, advocating for a post-cognitivist perspective in defining the future of affective design. This approach proposes that technology should not tell users what or how to act or think but instead respond to how human minds work. This framework could transform user communication through visualization, fostering positive behavioural changes. The study also highlights affective visualization as a nascent yet promising domain for future research [LWC23].
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    OceanInsight: A Marine Waste Visualization Platform Empowering Community-Driven Sustainability and Coastal Cleanup Efforts
    (The Eurographics Association, 2025) Feng, Qujing; Xu, Gang; Dou, Zi; Pan, Yushan; Wang, Hao; Wu, Di; Diehl, Alexandra; Kucher, Kostiantyn; Médoc, Nicolas
    This paper explores the challenges of coastline cleaning efforts, which involve a wide range of community members, and presents a yearlong investigation into designing technology to support these cleaning tasks. It examines how participatory design research, combining interactive technology with co-design activities, can help facilitate collaboration among community-based stakeholders in alignment with the UN goals. The research delves into the difficulties stakeholders face in sharing responsibilities and collaborating effectively. This study contributes to the literature by providing new insights into designing interactive technologies that enhance stakeholder participation, foster a socially and environmentally sustainable society.
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    Pie Chart Glyph Visualization of Uncertain Connected Components
    (The Eurographics Association, 2025) Evers, Marina; Rasheed, Farhan; Masood, Talha Bin; Hotz, Ingrid; Weiskopf, Daniel; Diehl, Alexandra; Kucher, Kostiantyn; Médoc, Nicolas
    Edges of graphs are often associated with uncertainty. The inherent uncertainty of the data also induces uncertainty in derived graph attributes such as connected components. Even for planar graphs, visualizing the connected components in the graph embedding while encoding their uncertainty imposes challenges due to overlap. We present a visual encoding for uncertain connected components in a planar graph embedding. The underlying model does not require matching or assumptions on the overlap of the components and emphasizes uncertain boundary regions. We discuss different design options and show the applicability of our approach based on synthetic data and real-world data on force networks in granular materials.
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    Reviewer #2: ''Why didn't you use UMAP?''
    (The Eurographics Association, 2025) Hoorn, Diede P. M. van der; Arleo, Alessio; Paulovich, Fernando V.; Diehl, Alexandra; Kucher, Kostiantyn; Médoc, Nicolas
    t-SNE and UMAP are both popular Dimensionality Reduction (DR) techniques. Over recent years, UMAP has gained popularity, but there has been some debate on the difference between the two, and whether a preference for UMAP is justified. We apply a recently defined framework to gain new insights by analyzing these two techniques in two phases: how they model the relationships in the high-dimensional space (relationship phase) and how they create the embedding (mapping phase). Our findings suggest that the main difference lies in the UMAP mapping phase, and not in how the relationships are modeled.
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    ReVISitPy: Python Bindings for the reVISit Study Framework
    (The Eurographics Association, 2025) Shrestha, Hilson; Wilburn, Jack; Bollen, Brian; McNutt, Andrew M.; Lex, Alexander; Harrison, Lane; Diehl, Alexandra; Kucher, Kostiantyn; Médoc, Nicolas
    User experiments are an important part of visualization research, yet they remain costly, time-consuming to create, and difficult to prototype and pilot. The process of prototyping a study-from initial design to data collection and analysis-often requires the use of multiple systems (e.g. webservers and databases), adding complexity. We present reVISitPy, a Python library that enables visualization researchers to design, pilot deployments, and analyze pilot data entirely within a Jupyter notebook. Re- VISitPy provides a higher-level Python interface for the reVISit Domain-Specific Language (DSL) and study framework, which traditionally relies on manually authoring complex JSON configuration files. As study configurations grow larger, editing raw JSON becomes increasingly tedious and error-prone. By streamlining the configuration, testing, and preliminary analysis workflows, reVISitPy reduces the overhead of study prototyping and helps researchers quickly iterate on study designs before full deployment through the reVISit framework.
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    Towards a Software Framework for Evaluating the Visualization Literacy of Large Language Models
    (The Eurographics Association, 2025) Jobst, Adrian; Atzberger, Daniel; Scheibel, Willy; Döllner, Jürgen; Diehl, Alexandra; Kucher, Kostiantyn; Médoc, Nicolas
    Large Language Models (LLMs) are increasingly integrated into Natural Language Interfaces (NLIs) for visualizations, enabling users to inquire about visualizations through natural language. This work introduces a software framework for evaluating LLMs' visualization literacy, i.e., their ability to interpret and answer questions about visualizations. Our framework generates a set of data points across different LLMs, prompts, and question types, allowing for in-depth analysis. We demonstrate its utility by two experiments, examining the impact of the temperature parameter and predefined answer choices.
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    Towards Scalable Out-of-Core Volume Rendering for High-Performance Visualization of 3D Temporal Multivariate Gas and Fluid Data
    (The Eurographics Association, 2025) Thebault, Antoine; Prévost, Stéphanie; Lucas, Laurent; Brenner, Leonardo; Diehl, Alexandra; Kucher, Kostiantyn; Médoc, Nicolas
    Scientific visualization enables a deeper insight into the data structure and properties. For Gas and fluid simulations, particularly those resulting from real-world gas captures or Computational Fluid Dynamics (CFD) models, this requires the analysis and integration of multivariate attributes alongside dynamic temporal variations. We present an ongoing work to develop a scalable, Out-of-core volume rendering application designed for massive 3D temporal multivariate datasets. Our rendering framework, called FRIGAS (Fluid Rendering Infrastructure for Gas and Atmospheric Simulations), introduces a novel pipeline which leverages improvements in Direct Volume Rendering (DVR) techniques for large scale visualizations, addressing constraints regarding temporal structured data and multivariate analysis for interactive spatial and temporal navigation without HPC resources.
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    TractMMR: Tractography Streamline Rating through User-guided Matchmaking
    (The Eurographics Association, 2025) Vink, Ruben; Vilanova, Anna; Chamberland, Maxime; Diehl, Alexandra; Kucher, Kostiantyn; Médoc, Nicolas
    Diffusion MRI tractography suffers from an ever-increasing parameter problem in which little to no semantic connection exists between input parameters and output tractogram. We present an approach for users to semantically interact with their data in order to produce a ranking over the parameter space which can be used to filter outputs and in downstream tasks to improve parameter selection. Our approach is a first step in bringing visual analytics closer to daily neuropractice by providing users a direct semantic interaction with their data.
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    WebGraphViz: A WebGL-Based Interactive Graph Visualization Tool for Retail Analytics
    (The Eurographics Association, 2025) Aguilar, Luis Miguel; Al-Tarawneh, Ragaad; Humayoun, Shah Rukh; Diehl, Alexandra; Kucher, Kostiantyn; Médoc, Nicolas
    The growing volume and complexity of data from sources like social media, IoT systems, and security devices highlight the need for scalable, high-performance visualization tools. Traditional web technologies such as SVG and Canvas often struggle with large datasets, limiting interactivity. We present WebGraphViz, a WebGL-based graph visualization tool that leverages GPU parallelism to overcome these limitations. Performance evaluations across three interaction experiments in both high- and low-performance environments show that WebGraphViz significantly outperforms its SVG-based counterpart, enabling smooth exploration of large-scale graph data.
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    A Graph Layout Evaluation System for Communication Graphs
    (The Eurographics Association, 2025) Schröter, Valentin; Scheibel, Willy; Döllner, Jürgen; Diehl, Alexandra; Kucher, Kostiantyn; Médoc, Nicolas
    Communication networks are a type of graph that occurs in different areas such as robotic, Internet of Things, and general network communication. Layouting such networks for visualization is an ongoing research task, while already existing layout algorithms are plenty and allow for broad parameterization, making the choice of a fitting algorithm difficult. We propose a graph layout evaluation system where a user - a researcher or visualization designer - can upload own graphs, select preloaded ones, or generate synthetic graphs to explore different layouts through their generated layouts. The system allows for configuration of multiple layouts that can then be explored by the user using side-by-side comparison and an enlarged view. Further, the system allows for computation of layout metrics. The overview of different layouts and associated layout metrics can then be used to select a fitting algorithm. The system is prepared for further layout algorithms and layout quality metrics, building a starting point for graph layout research.
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    Augmented Reality for Training in Small and Medium-Sized Manufacturing Companies
    (The Eurographics Association, 2025) Ainin, Abdulla A.; Algabroun, Hatem; Linhares, Claudio D. G.; Diehl, Alexandra; Kucher, Kostiantyn; Médoc, Nicolas
    As manufacturing systems grow more complex, traditional 2D schematics and static models fall short in training and comprehension. This work explores Augmented Reality (AR) as a solution, enabling interactive and spatially meaningful learning experiences. Focusing on small and medium-sized enterprises (SMEs), the system integrates a Digital Twin (DT) with Microsoft HoloLens and Unity to provide immersive visualization and interaction with mechanical machines. Users can manipulate components through natural hand gestures, enhancing spatial reasoning and hands-on training. This mixed-reality approach offers SMEs a scalable and practical tool for modernizing workforce education in manufacturing.
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    Discussion and Showcase of an Implementation of Task Taxonomies in Visualizations Based on the Dust and Magnet Metaphor
    (The Eurographics Association, 2025) Böttger, Florence; Scheibel, Willy; Döllner, Jürgen; Diehl, Alexandra; Kucher, Kostiantyn; Médoc, Nicolas
    In order to visualize multivariate data, it is often necessary to reduce their dimensionality. Visualizations based on the Dust and Magnet metaphor aim to present the information of the reduced dimensions via interactivity, while also supporting user comprehension by using a metaphor of ferrous dust and magnets. We compare two approaches to implementing this metaphor into a visualization tool along a set of core visualization tasks and propose extensions to make such visualizations more comprehensible and less misleading.
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    Fairness-Aware Urban Planning in Sweden: An Interactive Visualization Tool for Equitable Cities
    (The Eurographics Association, 2025) Othman, Reem; Powley, Benjamin; Martins, Rafael M.; Soares, Amilcar; Kerren, Andreas; Ferreira, Nivan; Linhares, Claudio D. G.; Diehl, Alexandra; Kucher, Kostiantyn; Médoc, Nicolas
    This study presents an interactive visualization tool that facilitates fairness-aware urban planning. The system introduces a fairness scale to assess the accessibility of potential new developments, using color-coded scatter plots to visualize disparities. An intuitive interaction design minimizes complexity while enhancing usability, enabling users to analyze urban infrastructure and services. Developed with web technologies, the tool leverages OpenStreetMap data to ensure adaptability across different cities. Future optimizations include advanced analytical capabilities and broader dataset integrations to improve decisionmaking in urban development.
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    Kickin' Scarves: Time-Oriented Visual Comparison of Soccer Trajectories
    (The Eurographics Association, 2025) Mertz, Tobias; Kohlhammer, Jörn; Diehl, Alexandra; Kucher, Kostiantyn; Médoc, Nicolas
    Line-based trajectory drawings face several shortcomings in time-oriented visual comparison scenarios, primarily in their facilitation of the comparison itself as well as in their representation of time. To investigate these challenges, we perform an exploratory study focused on the application of scarf plots to the evaluation of tactics performance in soccer games. While our visual analytics prototype, Kickin' Scarves, manages to avoid the shortcomings of line-based trajectory visualizations, the application of scarf plots to real-world problems poses several design challenges that have not yet been addressed in research.
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    The Past Is All Around You: Augmenting Cultural Heritage On-Site
    (The Eurographics Association, 2025) Passecker, Markus; Miksch, Silvia; Proksa, Franziska; Aigner, Wolfgang; Diehl, Alexandra; Kucher, Kostiantyn; Médoc, Nicolas
    Digitized cultural heritage (CH) artifacts frequently lose their original immersive and historical context when presented through traditional digital means. Situated visualization, particularly through augmented reality (AR), offers a promising avenue to reconnect artifacts with their authentic physical environments. In this work, our objective is to explore methods for designing effective AR-based visualizations to enhance user engagement and understanding in cultural heritage contexts. We share initial insights derived from literature reviews, prototyping, and preliminary evaluations focusing on prominent Austrian CH sites.
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    Towards Met.3D version 2: Creating a community research software for interactive 3-D visualization of meteorological data
    (The Eurographics Association, 2025) Rautenhaus, Marc; Fischer, Christoph; Vogt, Thorwin; Beckert, Andreas; Diehl, Alexandra; Kucher, Kostiantyn; Médoc, Nicolas
    Visualization is an important and ubiquitous tool in the daily work of weather forecasters and atmospheric researchers to analyse data from simulations and observations. The domain-specific meteorological visualization tool Met.3D is an opensource effort to make interactive, 3D, feature-based, and ensemble visualization techniques accessible to the meteorological community, and at the same time to provide a framework for visualization research with application to meteorology. Since the public release of version 1.0 in 2015, Met.3D has been used in multiple visualization research projects, and has evolved into a feature-rich visual analysis tool facilitating rapid exploration of gridded atmospheric data. In this demo, we will present the current state of our efforts to contribute a new version 2 of Met.3D to the community, with extended funcionality and improved usability for meteorological users, and with a well documented implementation for extension by visualization researchers.
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    Visual Analysis of Poker Hands for Individual Players
    (The Eurographics Association, 2025) Dotzler, Konstantin Joachim; Agarwal, Shivam; Beck, Fabian; Diehl, Alexandra; Kucher, Kostiantyn; Médoc, Nicolas
    Poker requires complex decisions and, to improve play, careful analysis. Typical analytics tools focus on individual hands, overlooking broader performance trends. This paper proposes an approach for both individual hand review and a more comprehensive gameplay analysis. The linked visualizations comprise a line chart for cumulative winnings, a scatterplot for winnings vs. hand rankings, a bar chart for detailed hand winnings, and an event sequence visualization of the selected hand.