EuroVisPosters2024

Permanent URI for this collection

EuroVis 2024 - 26th EG Conference on Visualization
Odense, Denmark | May 27 - 31, 2024
Posters
A Dashboard for Simplifying Machine Learning Models using Feature Importances and Spurious Correlation Analysis
Tim Cech, Erik Kohlros, Willy Scheibel, and Jürgen Döllner
A Design Space for Static Visualizations with Several Orders of Magnitude
Katerina Batziakoudi, Florent Cabric, Stéphanie Rey, and Jean-Daniel Fekete
A Quality Metric to Improve Scatterplots for Explainable AI
Liqun Liu, Roy A. Ruddle, Leonid V. Bogachev, Mahdi Rezaei, and Arjun Khara
A Visual Approach to Fair or Negotiated Resource Division
Randy L. Ribler and Jackson Wise
A Visualization Tool for Private Investors: Stock Portfolio Planning and Risk Management
Jakob Mørup Wang, Esben Bay Sørensen, Gareth Walsh, Jakob Kusnick, and Stefan Jänicke
A Web Framework for Explainable and Malleable Visualisation
Simon Malthe Hansen, Ira Assent, and Hans-Jörg Schulz
Cooperative Design of a Dashboard for Monitoring the P4D Cohort Study on Major Depression
Hamidreza Maharlou, Nicole Bössel-Debbert, Michael Lucht, Hannah B. Maier, Stefanie Mücke, Fabian Müntefering, Barbara Neuhaus, Jana Prokein, Christine Reif-Leonhard, Jan Voges, Heike Weber, Antoine Weihs, Helge Frieling, and Steffen Oeltze-Jafra
Exploring Designs for Combined Visual Encoding of Absolute and Fractional Values
Madhav Poddar and Fabian Beck
Hey ChatGPT, can you visualize my data? - A Multi-Dimensional Study on using an LLM for Constructing Data Visualizations
Mara Ströbel, Kai Eckert, and Till Nagel
Hybrid Multilayer Network Visualization of Bibliographic Data
Eloi Durant, Alessandra Tappini, Walter Didimo, Giuseppe Liotta, and Mohammad Ghoniem
Interactive Human-guided Dimensionality Reduction using Landmark Positioning
Tim Cech, Christian Raue, Frederic Sadrieh, Willy Scheibel, and Jürgen Döllner
Interactive Visual Exploration of Arctic Sea Ice Extent 1978-2023
Ditte Parsberg Pedersen, Lærke Ina Krogaard Hansen, Esben Bay Sørensen, Gareth Walsh, Jakob Kusnick, and Stefan Jänicke
LaNe Plot: A Visual Fingerprinting Technique for Sequential Data
Harith Rathish, Ginés Carreto Picón, and Hans-Jörg Schulz
Manifold Modelling with Minimum Spanning Trees
Daniël M. Bot, Peiyang Huo, Alessio Arleo, Fernando Paulovich, and Jan Aerts
Peeking at Visualization Research on Information Diffusion
Mert Usul and Alessio Arleo
Personal Mobile Devices to Assist with Wrist Rehabilitation at Home
Fairouz Grioui, Pantelis Antoniadis, Xingyao Yu, and Tanja Blascheck
Supporting Astrophysical Visualization with Sonification
Ivar Gorenko, Lonni Besançon, Camilla Forsell, and Niklas Rönnberg
Towards a Visual Analytics System for Emotion Trajectories in Multiparty Conversations
Zeyang Huang, Kostiantyn Kucher, and Andreas Kerren
Towards Presenting Travel Times in a Bus Network as Immersive and Adaptive Data Stories
Lukas Panzer and Fabian Beck
Visplorify: Interactive Visual Analysis of Spotify Listening Histories
Louis Franzke, Christofer Meinecke, Jeremias Schebera, and Daniel Wiegreffe
Visual Analysis of Power Plant Data for European Countries
Jinyi Wang, Kostiantyn Kucher, and Andreas Kerren
Visual Exploration of Emotion Feelings Comparison in Tweet Data
Ilya Nemtsov, Jasmine Jahan, Chuting Yan, and Shah Rukh Humayoun
Visualizing Property Assessments and Taxation: A Danish Case Study
Kim Nellemann Lund, Mette Rosenfjeld, Aksel Næraa Høeg Vendelsøe, Esben Bay Sørensen, Gareth Walsh, Jakob Kusnick, and Stefan Jänicke
Weather Data and Representations: A Survey of Wear OS Apps
Jakob Rohwer, Fairouz Grioui, and Tanja Blascheck
Where Visualization Fails, Sonification Speaks
Niklas Rönnberg

BibTeX (EuroVisPosters2024)
@inproceedings{
10.2312:evp.20242007,
booktitle = {
EuroVis 2024 - Posters},
editor = {
Kucher, Kostiantyn
and
Diehl, Alexandra
and
Gillmann, Christina
}, title = {{
EuroVis 2024 Posters: Frontmatter}},
author = {
Kucher, Kostiantyn
and
Diehl, Alexandra
and
Gillmann, Christina
}, year = {
2024},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-258-5},
DOI = {
10.2312/evp.20242007}
}
@inproceedings{
10.2312:evp.20241075,
booktitle = {
EuroVis 2024 - Posters},
editor = {
Kucher, Kostiantyn
and
Diehl, Alexandra
and
Gillmann, Christina
}, title = {{
A Dashboard for Simplifying Machine Learning Models using Feature Importances and Spurious Correlation Analysis}},
author = {
Cech, Tim
and
Kohlros, Erik
and
Scheibel, Willy
and
Döllner, Jürgen
}, year = {
2024},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-258-5},
DOI = {
10.2312/evp.20241075}
}
@inproceedings{
10.2312:evp.20241076,
booktitle = {
EuroVis 2024 - Posters},
editor = {
Kucher, Kostiantyn
and
Diehl, Alexandra
and
Gillmann, Christina
}, title = {{
A Design Space for Static Visualizations with Several Orders of Magnitude}},
author = {
Batziakoudi, Katerina
and
Cabric, Florent
and
Rey, Stéphanie
and
Fekete, Jean-Daniel
}, year = {
2024},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-258-5},
DOI = {
10.2312/evp.20241076}
}
@inproceedings{
10.2312:evp.20241077,
booktitle = {
EuroVis 2024 - Posters},
editor = {
Kucher, Kostiantyn
and
Diehl, Alexandra
and
Gillmann, Christina
}, title = {{
A Quality Metric to Improve Scatterplots for Explainable AI}},
author = {
Liu, Liqun
and
Ruddle, Roy A.
and
Bogachev, Leonid V.
and
Rezaei, Mahdi
and
Khara, Arjun
}, year = {
2024},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-258-5},
DOI = {
10.2312/evp.20241077}
}
@inproceedings{
10.2312:evp.20241078,
booktitle = {
EuroVis 2024 - Posters},
editor = {
Kucher, Kostiantyn
and
Diehl, Alexandra
and
Gillmann, Christina
}, title = {{
A Visual Approach to Fair or Negotiated Resource Division}},
author = {
Ribler, Randy L.
and
Wise, Jackson
}, year = {
2024},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-258-5},
DOI = {
10.2312/evp.20241078}
}
@inproceedings{
10.2312:evp.20241079,
booktitle = {
EuroVis 2024 - Posters},
editor = {
Kucher, Kostiantyn
and
Diehl, Alexandra
and
Gillmann, Christina
}, title = {{
A Visualization Tool for Private Investors: Stock Portfolio Planning and Risk Management}},
author = {
Wang, Jakob Mørup
and
Sørensen, Esben Bay
and
Walsh, Gareth
and
Kusnick, Jakob
and
Jänicke, Stefan
}, year = {
2024},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-258-5},
DOI = {
10.2312/evp.20241079}
}
@inproceedings{
10.2312:evp.20241080,
booktitle = {
EuroVis 2024 - Posters},
editor = {
Kucher, Kostiantyn
and
Diehl, Alexandra
and
Gillmann, Christina
}, title = {{
A Web Framework for Explainable and Malleable Visualisation}},
author = {
Hansen, Simon Malthe
and
Assent, Ira
and
Schulz, Hans-Jörg
}, year = {
2024},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-258-5},
DOI = {
10.2312/evp.20241080}
}
@inproceedings{
10.2312:evp.20241081,
booktitle = {
EuroVis 2024 - Posters},
editor = {
Kucher, Kostiantyn
and
Diehl, Alexandra
and
Gillmann, Christina
}, title = {{
Cooperative Design of a Dashboard for Monitoring the P4D Cohort Study on Major Depression}},
author = {
Maharlou, Hamidreza
and
Bössel-Debbert, Nicole
and
Weber, Heike
and
Weihs, Antoine
and
Frieling, Helge
and
Oeltze-Jafra, Steffen
and
Lucht, Michael
and
Maier, Hannah B.
and
Mücke, Stefanie
and
Müntefering, Fabian
and
Neuhaus, Barbara
and
Prokein, Jana
and
Reif-Leonhard, Christine
and
Voges, Jan
}, year = {
2024},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-258-5},
DOI = {
10.2312/evp.20241081}
}
@inproceedings{
10.2312:evp.20241082,
booktitle = {
EuroVis 2024 - Posters},
editor = {
Kucher, Kostiantyn
and
Diehl, Alexandra
and
Gillmann, Christina
}, title = {{
Exploring Designs for Combined Visual Encoding of Absolute and Fractional Values}},
author = {
Poddar, Madhav
and
Beck, Fabian
}, year = {
2024},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-258-5},
DOI = {
10.2312/evp.20241082}
}
@inproceedings{
10.2312:evp.20241083,
booktitle = {
EuroVis 2024 - Posters},
editor = {
Kucher, Kostiantyn
and
Diehl, Alexandra
and
Gillmann, Christina
}, title = {{
Hey ChatGPT, can you visualize my data? - A Multi-Dimensional Study on using an LLM for Constructing Data Visualizations}},
author = {
Ströbel, Mara
and
Eckert, Kai
and
Nagel, Till
}, year = {
2024},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-258-5},
DOI = {
10.2312/evp.20241083}
}
@inproceedings{
10.2312:evp.20241084,
booktitle = {
EuroVis 2024 - Posters},
editor = {
Kucher, Kostiantyn
and
Diehl, Alexandra
and
Gillmann, Christina
}, title = {{
Hybrid Multilayer Network Visualization of Bibliographic Data}},
author = {
Durant, Eloi
and
Tappini, Alessandra
and
Didimo, Walter
and
Liotta, Giuseppe
and
Ghoniem, Mohammad
}, year = {
2024},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-258-5},
DOI = {
10.2312/evp.20241084}
}
@inproceedings{
10.2312:evp.20241085,
booktitle = {
EuroVis 2024 - Posters},
editor = {
Kucher, Kostiantyn
and
Diehl, Alexandra
and
Gillmann, Christina
}, title = {{
Interactive Human-guided Dimensionality Reduction using Landmark Positioning}},
author = {
Cech, Tim
and
Raue, Christian
and
Sadrieh, Frederic
and
Scheibel, Willy
and
Döllner, Jürgen
}, year = {
2024},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-258-5},
DOI = {
10.2312/evp.20241085}
}
@inproceedings{
10.2312:evp.20241086,
booktitle = {
EuroVis 2024 - Posters},
editor = {
Kucher, Kostiantyn
and
Diehl, Alexandra
and
Gillmann, Christina
}, title = {{
Interactive Visual Exploration of Arctic Sea Ice Extent 1978-2023}},
author = {
Pedersen, Ditte Parsberg
and
Hansen, Lærke Ina Krogaard
and
Sørensen, Esben Bay
and
Walsh, Gareth
and
Kusnick, Jakob
and
Jänicke, Stefan
}, year = {
2024},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-258-5},
DOI = {
10.2312/evp.20241086}
}
@inproceedings{
10.2312:evp.20241087,
booktitle = {
EuroVis 2024 - Posters},
editor = {
Kucher, Kostiantyn
and
Diehl, Alexandra
and
Gillmann, Christina
}, title = {{
LaNe Plot: A Visual Fingerprinting Technique for Sequential Data}},
author = {
Rathish, Harith
and
Picón, Ginés Carreto
and
Schulz, Hans-Jörg
}, year = {
2024},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-258-5},
DOI = {
10.2312/evp.20241087}
}
@inproceedings{
10.2312:evp.20241088,
booktitle = {
EuroVis 2024 - Posters},
editor = {
Kucher, Kostiantyn
and
Diehl, Alexandra
and
Gillmann, Christina
}, title = {{
Manifold Modelling with Minimum Spanning Trees}},
author = {
Bot, Daniël M.
and
Huo, Peiyang
and
Arleo, Alessio
and
Paulovich, Fernando
and
Aerts, Jan
}, year = {
2024},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-258-5},
DOI = {
10.2312/evp.20241088}
}
@inproceedings{
10.2312:evp.20241089,
booktitle = {
EuroVis 2024 - Posters},
editor = {
Kucher, Kostiantyn
and
Diehl, Alexandra
and
Gillmann, Christina
}, title = {{
Peeking at Visualization Research on Information Diffusion}},
author = {
Usul, Mert
and
Arleo, Alessio
}, year = {
2024},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-258-5},
DOI = {
10.2312/evp.20241089}
}
@inproceedings{
10.2312:evp.20241090,
booktitle = {
EuroVis 2024 - Posters},
editor = {
Kucher, Kostiantyn
and
Diehl, Alexandra
and
Gillmann, Christina
}, title = {{
Personal Mobile Devices to Assist with Wrist Rehabilitation at Home}},
author = {
Grioui, Fairouz
and
Antoniadis, Pantelis
and
Yu, Xingyao
and
Blascheck, Tanja
}, year = {
2024},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-258-5},
DOI = {
10.2312/evp.20241090}
}
@inproceedings{
10.2312:evp.20241091,
booktitle = {
EuroVis 2024 - Posters},
editor = {
Kucher, Kostiantyn
and
Diehl, Alexandra
and
Gillmann, Christina
}, title = {{
Supporting Astrophysical Visualization with Sonification}},
author = {
Gorenko, Ivar
and
Besançon, Lonni
and
Forsell, Camilla
and
Rönnberg, Niklas
}, year = {
2024},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-258-5},
DOI = {
10.2312/evp.20241091}
}
@inproceedings{
10.2312:evp.20241092,
booktitle = {
EuroVis 2024 - Posters},
editor = {
Kucher, Kostiantyn
and
Diehl, Alexandra
and
Gillmann, Christina
}, title = {{
Towards a Visual Analytics System for Emotion Trajectories in Multiparty Conversations}},
author = {
Huang, Zeyang
and
Kucher, Kostiantyn
and
Kerren, Andreas
}, year = {
2024},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-258-5},
DOI = {
10.2312/evp.20241092}
}
@inproceedings{
10.2312:evp.20241093,
booktitle = {
EuroVis 2024 - Posters},
editor = {
Kucher, Kostiantyn
and
Diehl, Alexandra
and
Gillmann, Christina
}, title = {{
Towards Presenting Travel Times in a Bus Network as Immersive and Adaptive Data Stories}},
author = {
Panzer, Lukas
and
Beck, Fabian
}, year = {
2024},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-258-5},
DOI = {
10.2312/evp.20241093}
}
@inproceedings{
10.2312:evp.20241094,
booktitle = {
EuroVis 2024 - Posters},
editor = {
Kucher, Kostiantyn
and
Diehl, Alexandra
and
Gillmann, Christina
}, title = {{
Visplorify: Interactive Visual Analysis of Spotify Listening Histories}},
author = {
Franzke, Louis
and
Meinecke, Christofer
and
Schebera, Jeremias
and
Wiegreffe, Daniel
}, year = {
2024},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-258-5},
DOI = {
10.2312/evp.20241094}
}
@inproceedings{
10.2312:evp.20241095,
booktitle = {
EuroVis 2024 - Posters},
editor = {
Kucher, Kostiantyn
and
Diehl, Alexandra
and
Gillmann, Christina
}, title = {{
Visual Analysis of Power Plant Data for European Countries}},
author = {
Wang, Jinyi
and
Kucher, Kostiantyn
and
Kerren, Andreas
}, year = {
2024},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-258-5},
DOI = {
10.2312/evp.20241095}
}
@inproceedings{
10.2312:evp.20241096,
booktitle = {
EuroVis 2024 - Posters},
editor = {
Kucher, Kostiantyn
and
Diehl, Alexandra
and
Gillmann, Christina
}, title = {{
Visual Exploration of Emotion Feelings Comparison in Tweet Data}},
author = {
Nemtsov, Ilya
and
Jahan, Jasmine
and
Yan, Chuting
and
Humayoun, Shah Rukh
}, year = {
2024},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-258-5},
DOI = {
10.2312/evp.20241096}
}
@inproceedings{
10.2312:evp.20241097,
booktitle = {
EuroVis 2024 - Posters},
editor = {
Kucher, Kostiantyn
and
Diehl, Alexandra
and
Gillmann, Christina
}, title = {{
Visualizing Property Assessments and Taxation: A Danish Case Study}},
author = {
Lund, Kim Nellemann
and
Rosenfjeld, Mette
and
Vendelsøe, Aksel Næraa Høeg
and
Sørensen, Esben Bay
and
Walsh, Gareth
and
Kusnick, Jakob
and
Jänicke, Stefan
}, year = {
2024},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-258-5},
DOI = {
10.2312/evp.20241097}
}
@inproceedings{
10.2312:evp.20241098,
booktitle = {
EuroVis 2024 - Posters},
editor = {
Kucher, Kostiantyn
and
Diehl, Alexandra
and
Gillmann, Christina
}, title = {{
Weather Data and Representations: A Survey of Wear OS Apps}},
author = {
Rohwer, Jakob
and
Grioui, Fairouz
and
Blascheck, Tanja
}, year = {
2024},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-258-5},
DOI = {
10.2312/evp.20241098}
}
@inproceedings{
10.2312:evp.20241099,
booktitle = {
EuroVis 2024 - Posters},
editor = {
Kucher, Kostiantyn
and
Diehl, Alexandra
and
Gillmann, Christina
}, title = {{
Where Visualization Fails, Sonification Speaks}},
author = {
Rönnberg, Niklas
}, year = {
2024},
publisher = {
The Eurographics Association},
ISBN = {978-3-03868-258-5},
DOI = {
10.2312/evp.20241099}
}

Browse

Recent Submissions

Now showing 1 - 26 of 26
  • Item
    EuroVis 2024 Posters: Frontmatter
    (The Eurographics Association, 2024) Kucher, Kostiantyn; Diehl, Alexandra; Gillmann, Christina; Kucher, Kostiantyn; Diehl, Alexandra; Gillmann, Christina
  • Item
    A Dashboard for Simplifying Machine Learning Models using Feature Importances and Spurious Correlation Analysis
    (The Eurographics Association, 2024) Cech, Tim; Kohlros, Erik; Scheibel, Willy; Döllner, Jürgen; Kucher, Kostiantyn; Diehl, Alexandra; Gillmann, Christina
    Machine Learning models underlie a trade-off between accurracy and explainability. Given a trained, complex model, we contribute a dashboard that supports the process to derive more explainable models, here: Fast-and-Frugal Trees, with further introspection using feature importances and spurious correlation analyses. The dashboard further allows to iterate over the feature selection and assess the trees' performance in comparison to the complex model.
  • Item
    A Design Space for Static Visualizations with Several Orders of Magnitude
    (The Eurographics Association, 2024) Batziakoudi, Katerina; Cabric, Florent; Rey, Stéphanie; Fekete, Jean-Daniel; Kucher, Kostiantyn; Diehl, Alexandra; Gillmann, Christina
    We describe the design space for visualizations with attributes spanning several orders of magnitude, termed Orders of Magnitude Values (OMVs), and present OMVis, a tool for the interactive exploration of this design space. We divide OMVs into mantissa and exponent for separate visual encoding, similar to scientific notation. We create visualizations combining an OMV with another attribute-nominal, ordinal, time, or quantitative-using various marks and visual channels following the rules of the Grammar of Graphics. We refine this space by enforcing integrity constraints from visualization literature, aiming to enhance the effectiveness of the generated visualizations.
  • Item
    A Quality Metric to Improve Scatterplots for Explainable AI
    (The Eurographics Association, 2024) Liu, Liqun; Ruddle, Roy A.; Bogachev, Leonid V.; Rezaei, Mahdi; Khara, Arjun; Kucher, Kostiantyn; Diehl, Alexandra; Gillmann, Christina
    Scatterplots are widely utilised in Explainable Artificial Intelligence (XAI) to investigate misclassifications and patterns among instances. However, when datasets are large, overplotting diminishes the effectiveness of scatterplots. This poster introduces a new quality metric to measure the overplotting of scatterplots in the context of XAI. Initially, we assess the significance of each data point within a scatterplot by continuous density transformation, Mahalanobis Distance and a mapping function. Building on this foundation, we develop a quality metric for scatterplots. Our metric performs well accounting for rendering orders and marker sizes in scatterplots, showcasing the metric's potential to improve the effectiveness of XAI scatterplots.
  • Item
    A Visual Approach to Fair or Negotiated Resource Division
    (The Eurographics Association, 2024) Ribler, Randy L.; Wise, Jackson; Kucher, Kostiantyn; Diehl, Alexandra; Gillmann, Christina
    The fair division problem addresses the frequently encountered situation in which a set of resources must be fairly divided between two or more stakeholders. Dividing possessions after a divorce, assigning tasks to workers, and determining the terms of contracts or treaties are all examples of this problem. Algorithms have been developed to provide solutions that optimize for various metrics, but for many reasons, including the lack of agreement on what constitutes fairness, algorithms cannot provide a definitive result. Visualizations, rather than providing a single candidate solution, can be used effectively to browse the search space and generate a pool of candidate allocations that are most likely to be appealing to all parties. Candidate solutions can be used by stakeholders, either separately or cooperatively, as the basis for negotiation. We demonstrate prototype software that provides this capability for a set of indivisible resources that are divided between two stakeholders.
  • Item
    A Visualization Tool for Private Investors: Stock Portfolio Planning and Risk Management
    (The Eurographics Association, 2024) Wang, Jakob Mørup; Sørensen, Esben Bay; Walsh, Gareth; Kusnick, Jakob; Jänicke, Stefan; Kucher, Kostiantyn; Diehl, Alexandra; Gillmann, Christina
    We propose a visualization prototype for stock portfolio planning and risk management. Unlike existing tools, we enable amateur investors to make informed investment choices by simplifying analytical concepts through visualizations. In practice, the tool allows for dynamic building, giving weight to, and visually inspecting a stock portfolio from the perspective of various riskrelated metrics. Currently, the prototype presented includes perspectives on key financial characteristics.
  • Item
    A Web Framework for Explainable and Malleable Visualisation
    (The Eurographics Association, 2024) Hansen, Simon Malthe; Assent, Ira; Schulz, Hans-Jörg; Kucher, Kostiantyn; Diehl, Alexandra; Gillmann, Christina
    We present a novel web-framework which combines malleability in both the visualisation and pre-processing steps of the data visualisation pipeline. The framework lets users create Charts which can be visually modified to the use case, and each have their own fully editable Python code model with access to Python's extensive libraries. This puts the user in control over both pre-processing in Python and the final visualisation, making the effects of each pipeline step explainable and transparent.
  • Item
    Cooperative Design of a Dashboard for Monitoring the P4D Cohort Study on Major Depression
    (The Eurographics Association, 2024) Maharlou, Hamidreza; Bössel-Debbert, Nicole; Lucht, Michael; Maier, Hannah B.; Mücke, Stefanie; Müntefering, Fabian; Neuhaus, Barbara; Prokein, Jana; Reif-Leonhard, Christine; Voges, Jan; Weber, Heike; Weihs, Antoine; Frieling, Helge; Oeltze-Jafra, Steffen; Kucher, Kostiantyn; Diehl, Alexandra; Gillmann, Christina
    The P4D (Personalised, Predictive, Precise, and Preventive Medicine for Major Depression) study aims at an improved prediction of treatment outcomes based on a more precise stratification of major depression subtypes. It is collecting very complex data from 1,000 patients across five German university hospitals. We have designed a dashboard to monitor the study and share the collected data among the study partners. We employed a state-of-the-art cooperative dashboard design approach by Setlur et al. [SCST24] in two design cycles: user feedback and dashboard revision. We observed a significant improvement in user satisfaction from the first (Mean=3.57 std=0.95) to the second (Mean=3.87 std=0.80) cycle and an overall positive assessment.
  • Item
    Exploring Designs for Combined Visual Encoding of Absolute and Fractional Values
    (The Eurographics Association, 2024) Poddar, Madhav; Beck, Fabian; Kucher, Kostiantyn; Diehl, Alexandra; Gillmann, Christina
    Datasets with absolute values that represent fractions of a whole are commonplace. To visualize these datasets, one can decide between visualizations highlighting the absolute value or the fractional value, but there are variants of visualizations that account for both. In this work, we explore the design space of such visualizations that show both the absolute and fractional values. Along with this, we include an initial assessment on what analysis tasks pertain to these designs and how these tasks might be influenced by the input data characteristics.
  • Item
    Hey ChatGPT, can you visualize my data? - A Multi-Dimensional Study on using an LLM for Constructing Data Visualizations
    (The Eurographics Association, 2024) Ströbel, Mara; Eckert, Kai; Nagel, Till; Kucher, Kostiantyn; Diehl, Alexandra; Gillmann, Christina
    This paper explores the effectiveness of an LLM in creating data visualizations across a spectrum of scenarios, characterized by three key dimensions: the complexity of the underlying data, the user's data visualization competencies, and the requirements of the resulting visualization. Based on an empirical study, we offer insights into the potential role of LLMs as tools for empowering users with varied expertise to effectively visualize data.
  • Item
    Hybrid Multilayer Network Visualization of Bibliographic Data
    (The Eurographics Association, 2024) Durant, Eloi; Tappini, Alessandra; Didimo, Walter; Liotta, Giuseppe; Ghoniem, Mohammad; Kucher, Kostiantyn; Diehl, Alexandra; Gillmann, Christina
    To reify the concept of layers, multilayer network visualizations often lay out nodes on distinct hyperplanes, one per layer. In this work, we consider the case of a 2D representation where layer nodes are laid out on parallel rectilinear axes. The adoption of classic edge drawing strategies here would lead to much visual clutter due to overlapping inter-layer and intra-layer edges. Moreover, distinguishing between these two types of edges would be fairly difficult. In this preliminary work, we explore the potential of using a hybrid visualization blending the adjacency matrix and node-link metaphors to distinguish undirected intraand inter-layer edges, respectively.We apply this approach to the analysis of bibliographic data, and discuss current limitations.
  • Item
    Interactive Human-guided Dimensionality Reduction using Landmark Positioning
    (The Eurographics Association, 2024) Cech, Tim; Raue, Christian; Sadrieh, Frederic; Scheibel, Willy; Döllner, Jürgen; Kucher, Kostiantyn; Diehl, Alexandra; Gillmann, Christina
    Dimensionality Reduction Techniques (DRs) are used for projecting high-dimensional data onto a two-dimensional plane. One subclass of DRs are such techniques that utilize landmarks. Landmarks are a subset of the original data space that are projected by a slow and more precise technique. The other data points are then placed in relation to these landmarks with respect to their distance in the high-dimensional space. We propose a technique to refine the placement of the landmarks by a human user. We test two different techniques for unprojecting the movement of the low-dimensional landmarks into the high-dimensional data space. We showcase that such a movement can increase certain quality metrics while decreasing others. Therefore, users may use our technique to challenge their understanding of the high-dimensional data space.
  • Item
    Interactive Visual Exploration of Arctic Sea Ice Extent 1978-2023
    (The Eurographics Association, 2024) Pedersen, Ditte Parsberg; Hansen, Lærke Ina Krogaard; Sørensen, Esben Bay; Walsh, Gareth; Kusnick, Jakob; Jänicke, Stefan; Kucher, Kostiantyn; Diehl, Alexandra; Gillmann, Christina
    The Arctic region and it ecosystem is undergoing rapid and significant environmental transformations by climate change. Traditional visualizations on this lack interactivity, hindering in-depth exploration by domain experts. This paper presents a participatory approach to developing a more interactive visualization tool for exploring the extent of Arctic sea ice. Leveraging data from the National Snow and Ice Data Center, our prototype offers insights into overall trends, seasonal variations, regional differences, and historical comparisons. By combining geospatial and temporal overviews, users can analyze changes comprehensively. Our visualization tool is a step towards interactively exploring the Arctic sea ice developments and thereby facilitating researchers to gain informed insights into the complex dynamics of a key aspect in the Arctic ecosystem.
  • Item
    LaNe Plot: A Visual Fingerprinting Technique for Sequential Data
    (The Eurographics Association, 2024) Rathish, Harith; Picón, Ginés Carreto; Schulz, Hans-Jörg; Kucher, Kostiantyn; Diehl, Alexandra; Gillmann, Christina
    Visual summaries of sequential data are often used to identify common trends at a glance. In this poster, we propose a visualization technique to fingerprint sequential data by showing the difference between contiguous data points. For each data point in the sequence, we visualize the difference between itself and the last data point as well as the next data point. As an application, we visualized the revision histories of Wikipedia articles to demonstrate the exploratory value of this technique.
  • Item
    Manifold Modelling with Minimum Spanning Trees
    (The Eurographics Association, 2024) Bot, Daniël M.; Huo, Peiyang; Arleo, Alessio; Paulovich, Fernando; Aerts, Jan; Kucher, Kostiantyn; Diehl, Alexandra; Gillmann, Christina
    Recent dimensionality reduction algorithms operate on a manifold assumption and expect data to be uniformly sampled from that underlying manifold. While some algorithms attempt to be robust for non-uniform sampling, their reliance on k-nearest neighbours to approximate manifolds limits how well they can span sampling gaps without introducing shortcuts. We present a minimum-spanning-tree-based manifold approximation approach that overcomes this problem and demonstrate it crosses sampling-gaps without introducing shortcuts while creating networks with few edges. A python package implementing our algorithm is available at https://github.com/vda-lab/multi_mst.
  • Item
    Peeking at Visualization Research on Information Diffusion
    (The Eurographics Association, 2024) Usul, Mert; Arleo, Alessio; Kucher, Kostiantyn; Diehl, Alexandra; Gillmann, Christina
    Diffusion Processes are a widely researched topic of interest to different scientific domains. One of the most popular research directions is Information Diffusion, pertaining how information spreads over a tightly connected network. From the modeling perspective, many different approaches are known in the literature; however, in the visualization community, this still represents an under-investigated problem. In this work, we present a succinct overview of the current state-of-the-art in Visual Analytics techniques employed in representing and understanding diffusion processes happening over networks. We consider different application domains and introduce a taxonomy that categorizes and provides structure to our selection of papers, fostering further research in the field of Visual Analytics of Information Diffusion processes.
  • Item
    Personal Mobile Devices to Assist with Wrist Rehabilitation at Home
    (The Eurographics Association, 2024) Grioui, Fairouz; Antoniadis, Pantelis; Yu, Xingyao; Blascheck, Tanja; Kucher, Kostiantyn; Diehl, Alexandra; Gillmann, Christina
    We present two modalities using mobile devices to assist patients with home-based wrist rehabilitation exercises. The first modality is a standalone smartwatch application that tracks the wrist's Range of Motion (ROM) and visualizes real-time exercise data. The second modality uses a smartphone to mirror the visualizations displayed on the smartwatch to overcome screen invisibility while rotated. In this poster, we report on our pilot study and the qualitative results of the two solutions. Results show that in terms of usability, the smartwatch-only modality score surpassed the mirrored-display. However, participants preferred the mirrored-display modality more for home-based usage.
  • Item
    Supporting Astrophysical Visualization with Sonification
    (The Eurographics Association, 2024) Gorenko, Ivar; Besançon, Lonni; Forsell, Camilla; Rönnberg, Niklas; Kucher, Kostiantyn; Diehl, Alexandra; Gillmann, Christina
    This poster presents initial design steps exploring how sonification can be used to support visualization for comprehension of space and time in astronomical data. Radio signals travel at the speed of light. With a visualization of the universe, it is possible to travel faster than light and pass the radio waves leaving earth. We can then travel back in time. We propose to use sonification consisting of songs representing each year as a musical journey through space and time to create an engaging experience.
  • Item
    Towards a Visual Analytics System for Emotion Trajectories in Multiparty Conversations
    (The Eurographics Association, 2024) Huang, Zeyang; Kucher, Kostiantyn; Kerren, Andreas; Kucher, Kostiantyn; Diehl, Alexandra; Gillmann, Christina
    Visualizing sentiments in textual data has received growing interest; however, representing emotions within interlocutor relationships and associating them with the temporal progression of dialogues remains challenging. In this poster abstract, we describe the ongoing work on a visual analytics tool designed for analyzing emotion trajectories within dialogue collections composed of utterances from multiple speakers. The proposed tool provides exploration at different levels of detail to complex multigraphs, where edges represent direct responses between speakers through their utterances. Our approach includes several selection strategies for connecting different views: summaries of emotion transitions across dialogue groups, detailed analyses of individual utterances within specific dialogues of interest in interlocutor networks, and close reading. The tool aims to support model development in natural language processing by allowing users to explore text corpora interactively.
  • Item
    Towards Presenting Travel Times in a Bus Network as Immersive and Adaptive Data Stories
    (The Eurographics Association, 2024) Panzer, Lukas; Beck, Fabian; Kucher, Kostiantyn; Diehl, Alexandra; Gillmann, Christina
    Desirable increased usage of public transport is, to some extent, limited by people being unaware of their traveling options. To invite a broad audience to casually explore their local bus network, we present an approach for the interactive analysis of traveling times in an immersive, animated simulation of buses. A first prototype already implements the core travel time visualization for a personal starting point. Additionally, we outline specific plans to extend the system towards telling adaptive stories that summarize the data and guide the users to relevant insights.
  • Item
    Visplorify: Interactive Visual Analysis of Spotify Listening Histories
    (The Eurographics Association, 2024) Franzke, Louis; Meinecke, Christofer; Schebera, Jeremias; Wiegreffe, Daniel; Kucher, Kostiantyn; Diehl, Alexandra; Gillmann, Christina
    The audio streaming platform Spotify collects various personal data from its users, including an extensive streaming history. Despite providing this data, Spotify lacks tools for visualizing or analyzing it. This work introduces Visplorify, an application to analyze and visualize the extended streaming history. The main goal is to offer interested Spotify users a way to visually explore their listening behavior and gain deeper insights into their music data. Visplorify automatically processes users' streaming history, enriching it with detailed data presented in an interactive dashboard. Users can explore and gain insights from their data using filters and visualizations to examine patterns and trends. Users have found several use cases, such as identifying personal patterns, reflecting on life events, discovering old and new favorite songs, and creating playlists. The application also provides users with insight into potential analyses of their personal data, increasing transparency.
  • Item
    Visual Analysis of Power Plant Data for European Countries
    (The Eurographics Association, 2024) Wang, Jinyi; Kucher, Kostiantyn; Kerren, Andreas; Kucher, Kostiantyn; Diehl, Alexandra; Gillmann, Christina
    A power plant is a complex real-world system associated with rich multidimensional data relevant to its construction and activity. Thus, choosing an appropriate way to visualize power plant data is important for users to understand and explore more about such systems. Most of the approaches existing in this field support only a static representation of data from a small region. This makes it hard for the users to get an overview or explore specific power plants. In this poster abstract, we describe an interactive visualization tool designed for the analysis of power plant data in Europe. Our approach provides an overview and detail visualization approach for Global Power Plant Database entries. With this tool, users can easily find power plants, see details on demand, filter, compare, and explore the power plant outage scenarios from the nearest neighbor perspective.
  • Item
    Visual Exploration of Emotion Feelings Comparison in Tweet Data
    (The Eurographics Association, 2024) Nemtsov, Ilya; Jahan, Jasmine; Yan, Chuting; Humayoun, Shah Rukh; Kucher, Kostiantyn; Diehl, Alexandra; Gillmann, Christina
    Twitter (renamed as X) is one of the popular social media platforms where people share news or reactions towards an event or topic using short text messages called ''tweets''. Emotion analysis in these tweets can play a vital role in understanding peoples' feelings towards the underlying event or topic. In this work, we present our visual analytics tool, called TECVis, that focuses on providing comparison views of peoples' emotion feelings in tweets towards an event or topic. The comparison is done based on geolocations or timestamps. TECVis provides several interaction and filtering options for navigation and better exploration of underlying tweet data for emotion feelings comparison.
  • Item
    Visualizing Property Assessments and Taxation: A Danish Case Study
    (The Eurographics Association, 2024) Lund, Kim Nellemann; Rosenfjeld, Mette; Vendelsøe, Aksel Næraa Høeg; Sørensen, Esben Bay; Walsh, Gareth; Kusnick, Jakob; Jänicke, Stefan; Kucher, Kostiantyn; Diehl, Alexandra; Gillmann, Christina
    In recent years, the use of property assessments to establish a basis for implementing equitable property taxation has become commonplace. In Denmark, the Danish Property Assessment Agency calculates and determines valuations of all properties, forming the basis for property taxation. Each homeowner is obligated to pay taxes on their property, with these assessments serving as the foundation for determining the tax calculation. In this context, we present an interactive visualization tool to enhance understanding and awareness of these property assessments and associated features. Our visualization tool is composed of five interconnected plots with integrated and extensive options for filtering the data. Initial feedback has found the tool to be effective for data exploration within this context, with the Section for Process Optimization and Automation at the Danish Property Assessment Agency calculates evaluating the tool's potential implementation and scope for the future.
  • Item
    Weather Data and Representations: A Survey of Wear OS Apps
    (The Eurographics Association, 2024) Rohwer, Jakob; Grioui, Fairouz; Blascheck, Tanja; Kucher, Kostiantyn; Diehl, Alexandra; Gillmann, Christina
    In this poster, we inspect common weather applications developed for Android Wear OS Smartwatches. Our goal is to learn (1) which type of weather data is commonly depicted in weather applications, (2) how this data is represented, and (3) how smartwatch wearers can interact with these applications. Based on this survey, we plan to develop glanceable weather visualizations that contain appropriate interactions. The current state of weather applications depicts a large number (15) of different weather data types; however, few use visual representations like bar charts (1), radial bar charts (2), or maps (4).
  • Item
    Where Visualization Fails, Sonification Speaks
    (The Eurographics Association, 2024) Rönnberg, Niklas; Kucher, Kostiantyn; Diehl, Alexandra; Gillmann, Christina
    Traveling by public transport can be challenging for a visually impaired traveler. However, visual information can be supported by sonification, the use of non-speech sound to convey information about data. This research project aims to explore how sonification can be used to provide information to a traveler at a bus stop. Three situations are described together with different sonification design approaches that will later be further developed and evaluated.