EuroVisPosters2023

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https://diglib.eg.org/handle/10.2312/2633341

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The Challenge of Branch-Aware Data Manifold Exploration
(The Eurographics Association, 2023) Bot, Daniël M.; Peeters, Jannes; Aerts, Jan; Gillmann, Christina; Krone, Michael; Lenti, Simone
Branches within clusters can represent meaningful subgroups that should be explored. In general, automatically detecting branching structures within clusters requires analysing the distances between data points and a centrality metric, resulting in a complex two-dimensional hierarchy. This poster describes abstractions for this data and formulates requirements for a visualisation, building towards a comprehensive branch-aware cluster exploration interface.
CitadelPolice: An Interactive Visualization Environment for Scenario Testing on Criminal Networks
(The Eurographics Association, 2023) Roelofsen, Liza A. S.; Oetker, Frederike; Lely, Miles van der; Belleman, Robert G.; Quax, Rick; Gillmann, Christina; Krone, Michael; Lenti, Simone
Criminal networks have proven to be highly resilient against law enforcement interventions. This resiliency has driven researchers to investigate these networks further. However, the obtained insights reaching law enforcement agencies are generally highly case-dependent or extremely general. Therefore, CitadelPolice aims to provide an environment for visualizing criminal network models on a comprehensive and interactive dashboard. The main advantage of CitadelPolice is that it allows law enforcement to independently test specific scenarios and discover the most effective disruption strategy before deploying it. To achieve this, we used a computational network model based on collaboration with and data from the Dutch Police Force, named the Criminal Cocaine Replacement Model and implemented this on a web-based graph visualization and simulation tool named Citadel. Using this, we can interactively visualize the network while running simulations. To test the effectiveness of the network visualization and implementation of the model, we performed sequential usability testing and compared the results over time.
CohExplore: Visually Supporting Students in Exploring Text Cohesion
(The Eurographics Association, 2023) Liebers, Carina; Agarwal, Shivam; Beck, Fabian; Gillmann, Christina; Krone, Michael; Lenti, Simone
A cohesive text allows readers to follow the described ideas and events. Exploring cohesion in text might aid students enhancing their academic writing. We introduce CohExplore, which promotes exploring and reflecting on cohesion of a given text by visualizing computed cohesion-related metrics on an overview and detailed level. Detected topics are color-coded, semantic similarity is shown via lines, while connectives and co-references in a paragraph are encoded using text decoration. Demonstrating the system, we share insights about a student-authored text.
Comparative Visualization of Longitudinal 24-hour Ambulatory Blood Pressure Measurements in Pediatric Patients with Chronic Kidney Disease
(The Eurographics Association, 2023) Özmen, Mahmut; Jabarulla, Mohamed Yaseen; Grabitz, Carl Robert; Melk, Anette; Wühl, Elke; Oeltze-Jafra, Steffen; Gillmann, Christina; Krone, Michael; Lenti, Simone
Pediatric chronic kidney disease (CKD) increases the risk of cardiovascular disease, stroke and other life-threatening conditions. Monitoring blood pressure in CKD patients is crucial to managing these risks. 24-hour ambulatory blood pressure monitoring (ABPM) is recommended for its comprehensive and accurate assessment of blood pressure over 24 hours. Analyzing and comparing 24-hour ABPM data of multiple diagnostic visits is a challenging task. Traditional methods involve comparing individual visits using paper printouts, which can be time-consuming and lacks a systematic overview of deviations over time. In this work, we present a dashboard visualization that allows clinicians (i) to assess the evolution of ABPM data over multiple diagnostic visits, (ii) to compare ABPM data of CKD patients with reference data of a healthy cohort, and (iii) to perform a detailed intra-individual comparison of the ABPM data acquired at two subsequent diagnostic visits. We demonstrate the dashboard in a case study of a patient with mild-to-moderate-stage CKD.
Constructing Hierarchical Continuity in Hilbert & Moore Treemaps
(The Eurographics Association, 2023) Scheibel, Willy; Döllner, Jürgen; Gillmann, Christina; Krone, Michael; Lenti, Simone
The Hilbert and Moore treemap layout algorithms are based on the space-filling Hilbert and Moore curves, respectively, to map tree-structured datasets to a 2D treemap layout. Considering multiple snapshots of a time-variant dataset, one of the design goals for Hilbert and Moore treemaps is layout stability, i.e., low changes in the layout for low changes in the underlying tree-structured data. For this, their underlying space-filling curve is expected to be continuous across all nodes and hierarchy levels, which has to be considered throughout the layouting process. We propose optimizations to subdivision templates, their orientation, and discuss the continuity of the underlying space-filling curve. We show real-world examples of Hilbert and Moore treemaps for small and large datasets with continuous space-filling curves, allowing for improved layout stability.
A Conversational Data Visualisation Platform for Hierarchical Multivariate Data
(The Eurographics Association, 2023) Kavaz, Ecem; Rodríguez, Inmaculada; Puig, Anna; Vives, Eduard; Gillmann, Christina; Krone, Michael; Lenti, Simone
This paper presents a novel data visualisation platform that integrates both direct manipulation and conversational interaction styles for analysing hierarchical multivariate data. The proposed architecture is based on the Rasa conversational AI framework. We show its full potential in a real-life case study for analysing hate speech in online news.
A Dashboard for Interactive Convolutional Neural Network Training And Validation Through Saliency Maps
(The Eurographics Association, 2023) Cech, Tim; Simsek, Furkan; Scheibel, Willy; Döllner, Jürgen; Gillmann, Christina; Krone, Michael; Lenti, Simone
Quali-quantitative methods provide ways for interrogating Convolutional Neural Networks (CNN). For it, we propose a dashboard using a quali-quantitative method based on quantitative metrics and saliency maps. By those means, a user can discover patterns during the training of a CNN. With this, they can adapt the training hyperparameters of the model, obtaining a CNN that learned patterns desired by the user. Furthermore, they neglect CNNs which learned undesirable patterns. This improves users' agency over the model training process.
EuroVis 2023 Posters: Frontmatter
(The Eurographics Association, 2023) Gillmann, Christina; Krone, Michael; Lenti, Simone; Gillmann, Christina; Krone, Michael; Lenti, Simone
Explorative Study on Semantically Resonant Colors for Combinations of Categories with Application to Meteorological Data
(The Eurographics Association, 2023) Pelchmann, Laura; Bremm, Sebastian; Ebell, Kerstin; Landesberger, Tatiana von; Gillmann, Christina; Krone, Michael; Lenti, Simone
We present an exploratory study of semantically resonant colors for combinations of categories. The goal is to support color selection of multi-labeled classes of classified data. We asked participants to assign colors to different categories in the meteorological domain and then to their combinations. Our results show that the colors chosen for the combinations are related to the colors for the individual categories. We also found indications that people tend to prefer darker color values for combinations of categories. Our results can be used to color code meteorological data.
An Initial Visual Analysis of German City Dashboards
(The Eurographics Association, 2023) Huber, Christoph; Nagel, Till; Stuckenschmidt, Heiner; Gillmann, Christina; Krone, Michael; Lenti, Simone
City dashboards are powerful tools for quickly understanding various urban phenomena through visualizing urban data using various techniques. In this paper, we investigate the common data sets used, and the most frequently employed visualization techniques in city dashboards. We reviewed 16 publicly available dashboards from 42 cities that are part of German smart city programs and have a high level of digitization. Through analysis of the visualization techniques used, we present our results visually and discuss our findings.
Interaction Tasks for Explainable Recommender Systems
(The Eurographics Association, 2023) Al-Hazwani, Ibrahim; Alahmadi, Turki; Wardatzky, Kathrin; Inel, Oana; El-Assady, Mennatallah; Bernard, Jürgen; Gillmann, Christina; Krone, Michael; Lenti, Simone
In the modern web experience, users interact with various types of recommender systems. In this literature study, we investigate the role of interaction in explainable recommender systems using 27 relevant papers from recommender systems, humancomputer interaction, and visualization fields. We structure interaction approaches into 1) the task, 2) the interaction intent, 3) the interaction technique, and 4) the interaction effect on explainable recommender systems. We present a preliminary interaction taxonomy for designers and developers to improve the interaction design of explainable recommender systems. Findings based on exploiting the descriptive power of the taxonomy emphasize the importance of interaction in creating effective and user-friendly explainable recommender systems.
MILADY (Matrix+Linear Diagram): Visual Exploration and Edition of Multivariate Graphs for Computer Networks Management
(The Eurographics Association, 2023) Guglielmino, Mathieu; Bronzino, Francesco; Sallaberry, Arnaud; Monnet, Sébastien; Gillmann, Christina; Krone, Michael; Lenti, Simone
This poster introduces MILADY (Matrix+Linear Diagram), a visual method for exploring and editing multivariate graphs from a computer networks perspective. Existing methods usually require multiple views, but our integrated approach enables users to visualize and edit both aspects with drag gestures and in a single view. We demonstrate the usefulness of our method for computer networks management.
Multi-Criteria Optimization for Automatic Dashboard Design
(The Eurographics Association, 2023) Choi, Jiwon; Jo, Jaemin; Gillmann, Christina; Krone, Michael; Lenti, Simone
We present Gleaner, an automatic dashboard design system that optimizes the design in terms of four design criteria, namely Specificity, Interestingness, Diversity, and Coverage. With these criteria, Gleaner not only optimizes for the expressiveness and interestingness of a single visualization but also improves the diversity and coverage of the dashboard as a whole. Users are able to express their intent for desired dashboard design to Gleaner, including specifying preferred or constrained attributes and adjusting the weight of each criterion. This flexibility in expressing intent enables Gleaner to design dashboards that are well-aligned with the user's own analytic goals leading to more efficient data exploration.
ORD-Xplore: Bridging Open Research Data Collections through Modality Abstractions
(The Eurographics Association, 2023) Sachdeva, Madhav; Blum, Michael; Stricker, Yann; Schreck, Tobias; Mumenthaler, Rudolf; Bernard, Jürgen; Gillmann, Christina; Krone, Michael; Lenti, Simone
We present ORD-Xplore, an approach to bridge gaps between digital editions, which represent valuable collections of multiple digitized research artifacts. However, digital editions often co-exist isolated, making it difficult for researchers to access, find, and re-use open research data from multiple digital editions. An ultimate goal is to unify library services across editions, even for editions with heterogeneity. In ORD-Xplore, we utilize abstraction methods from visualization research to help digital librarians identify unifying data modalities, as one important step towards standardization of heterogeneous digital editions.
Project iMuse: an Interactive Visualizer of Lyrical Sentiment
(The Eurographics Association, 2023) Lu, Anna; Anstey, Jack; Zhang, Zack; Wang, Ruohe; Gillmann, Christina; Krone, Michael; Lenti, Simone
Our interactive visualization, Project iMuse [SA22a], provides the unique ability to view the most used words in popular music over the past 50+ years in conjunction with how they were used in songs through sentiment analysis. To aid in more detailed analyses, Project iMuse has the ability to dynamically consider a variety of user defined subsets. These subsets are created through the user interaction, which includes changing the range of years considered and selecting particular word types.
PTMVision: An Interactive Visualization Platform for Post-Translational Modifications of Proteins
(The Eurographics Association, 2023) Hackl, Simon; Jachmann, Caroline; Harbig, Theresa; Witte Paz, Mathias; Nieselt, Kay; Gillmann, Christina; Krone, Michael; Lenti, Simone
In recent years, proteins have been shown to carry many more post-translational modifications (PTMs) than originally thought. The visualization of proteins along with their PTMs facilitates exploration and understanding of the effects of these PTMs on the protein structure, function, and interactions with other proteins. Therefore, we developed PTMVision, an interactive webbased visualization. We combine information about PTMs in the primary sequence with a two-dimensional representation of the protein's tertiary structure using a presence-absence map and a modified contact map that relates PTMs with the spatial arrangement of proteins without the need of a 3D structure. The prototype of PTMVision is part of the TueVis Visualization Server and is available at https://ptmvision-tuevis.cs.uni-tuebingen.de/.
Putting Annotations to the Test
(The Eurographics Association, 2023) Becker, Franziska; Ertl, Thomas; Gillmann, Christina; Krone, Michael; Lenti, Simone
When users work with interactive visualization systems, they get to see more accessible representations of raw data and interact with these, e.g. by filtering the data or modifying the visualization parameters like color. Internal representations such as hunches about trends, outliers or data points of interest, relationships and more are usually not visualized and integrated in systems, i.e. they are not externalized. In addition, how externalizations in visualization systems can affect users in terms of memory, post-analysis recall, speed or analysis quality is not yet completely understood. We present a visualization-agnostic externalization framework that lets users annotate visualizations, automatically connect them to related data and store them for later retrieval. In addition, we conducted a pilot study to test the framework's usability and users' recall of exploratory analysis results. In two tasks, one without and one with annotation features available, we asked participants to answer a question with the help of visualizations and report their findings with concrete examples afterwards. Qualitative analysis of the summaries showed that there are only minor differences in terms of detail or completeness, which we suspect is due to the short task time and consequently more shallow analyses made by participants. We discuss how to improve our framework's usability and modify our study design for future research to gain more insight into externalization effects on post-analysis recall.
Supporting Medical Personnel at Analyzing Chronic Lung Diseases with Interactive Visualizations
(The Eurographics Association, 2023) Warnking, Rene P.; Scheer, Jan; Trinkmann, Frederik; Siegel, Fabian; Nagel, Till; Gillmann, Christina; Krone, Michael; Lenti, Simone
We present a visualization system for medical practitioners to analyze lung function data collected at different points in time. In particular, our approach aims to solve the problems practitioners encounter in their daily work life when they have to consult different text-based documents to get access to the same data we provide in a single interface. To test the suitability of our system, we conducted a formative study where participants used our system to answer both simple and complex questions previously designed in collaboration with a domain expert. Our results indicate that our target users can easily work with our system and use it to answer both types of questions.
Symbolic Event Visualization for Analyzing User Input and Behavior of Augmented Reality Sessions
(The Eurographics Association, 2023) Rabsahl, Solveig; Satzger, Thomas; Kalamkar, Snehanjali; Grubert, Jens; Beck, Fabian; Gillmann, Christina; Krone, Michael; Lenti, Simone
Interacting with augmented reality (AR) systems involves different domains and is more complex than interacting with traditional user interfaces. To analyze AR interactions, we suggest an event visualization approach that discerns different event layers on a timeline. It is based on symbolic event representations of typical user actions, such as physical movement or interaction with scene objects. Although focusing on the Microsoft HoloLens 2, the approach can generalize to similar environments and provide a basis for developing a more comprehensive visual analytics and annotation solution for AR usage sessions.
A Tour Through the Zoo of Scented Widgets
(The Eurographics Association, 2023) Ciorna, Vasile; Médoc, Nicolas; Melançon, Guy; Petry, Frank; Ghoniem, Mohammad; Gillmann, Christina; Krone, Michael; Lenti, Simone
Software developers can choose among many popular widget toolkits to build graphical user interfaces quickly. Widgets like sliders, buttons and scrollbars are widespread and well-understood by the public. They allow users to interact with the software, to trigger operations or to set parameters. It is also recognized that widgets could be enhanced to provide a better user experience. Embedded visualizations, also known as scents, could be added to standard widgets to enhance their capabilities. In this work, we survey the literature concerning scented widgets. We propose a two-level taxonomy structured around four main dimensions: Purpose, Widget Type, Number of Scents and Scent Type, with examples of scented widgets. We also discuss our current thoughts about the scope of this survey, and call for feedback to further improve and extend the proposed taxonomy.

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