EuroVisPosters2023

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

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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.
Visualizing Pairwise Feature Interactions in Neural Additive Models
(The Eurographics Association, 2023) Steinparz, Christian; Hinterreiter, Andreas; Streit, Marc; Gillmann, Christina; Krone, Michael; Lenti, Simone
We present an approach for incorporating feature interactions into Neural Additive Models (NAMs), building upon existing work in this area, to enhance their predictive capabilities while maintaining interpretability. Our contribution focuses on the visual exploration and management of the increased number of feature maps resulting from the addition of pairwise feature combinations to NAMs. This method allows for effectively visualizing individual and pairwise feature interactions using line plots and heatmaps, respectively. To address the potential explosion in the number of feature maps, we apply different scoring functions to compute the importance of a feature map and then filter and sort them based on their importance. The proposed interactive dashboard effectively manages large sets of feature maps, while preserving the white-box properties of NAMs.
WebGPU for Scalable Client-Side Aggregate Visualization
(The Eurographics Association, 2023) Kimmersdorfer, Gerald; Wolf, Dominik; Waldner, Manuela; Gillmann, Christina; Krone, Michael; Lenti, Simone
WebGPU is a new graphics API, which now provides compute shaders for general purpose GPU operations in web browsers.We demonstrate the potential of this new technology for scalable information visualization by showing how to filter and aggregate a spatio-temporal dataset with millions of temperature measurements for real-time interactive exploration of climate change.
Unveiling the Dispersal of Historical Books from Religious Orders
(The Eurographics Association, 2023) Xing, Yiwen; Yan, Dengyi; Dondi, Cristina; Borgo, Rita; Abdul-Rahman, Alfie; Gillmann, Christina; Krone, Michael; Lenti, Simone
In this paper, we introduce a visualization prototype designed to assist historians in exploring the dispersal of books from religious orders throughout Europe during the sixteenth century and beyond. The prototype is the result of a collaboration between visualization researchers and a historical book researcher, aiming to apply visualization techniques to address realworld domain challenges. Over two months, we engaged in an intensive collaboration with the domain expert to analyze domain issues and requirements and subsequently developed a prototype featuring two interfaces. Weekly discussions with the domain expert guided design and ongoing prototype evaluation. In its infancy, the prototype shows promise for enhancement and scalability. Future efforts will target systematic usability and practicality evaluations.
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.
Visualizing Sunlight Radiation in the Arctic Ocean
(The Eurographics Association, 2023) Sørensen, Esben Bay; Attard, Karl; Gattuso, Jean-Pierre; Kusnick, Jakob; Jänicke, Stefan; Gillmann, Christina; Krone, Michael; Lenti, Simone
The Arctic is experiencing dramatic environmental transformation due to rising temperatures and melting ice, which are affecting its environment, wildlife, and human communities. Remote sensing technologies (e.g. satellites) are increasingly being used to understand environmental change in the remote and understudied Arctic Ocean across broad spatial and temporal scales, generating vast data sets that require interactive visualization to be dynamically explored. We present a prototype visualization that uses aggregation means on different zoom levels to allow exploring a 200GB data set on sunlight in the Arctic Ocean, which consists of monthly time series of coastal pixels, photosynthetically available radiation (PAR), light attenuation coefficient (KPAR), and PAR estimated at the seafloor (PARBOTTOM) from 1998 to 2018. Our main example-the analysis of trends in sunlight radiation levels along the west coast of Greenland-exemplifies our tool's value for marine biologists to getting a concise and interactive overview of sunlight radiation levels, which allows studying potential impacts on the Arctic ecosystem.
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.
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.
Towards Visualisation Specifications from Multilingual Natural Language Queries using Large Language Models
(The Eurographics Association, 2023) Hutchinson, Maeve; Slingsby, Aidan; Jianu, Radu; Madhyastha, Pranava; Gillmann, Christina; Krone, Michael; Lenti, Simone
In this paper, we present an empirical demonstration of a prompt-based learning approach, which utilizes pre-trained Large Language Models to generate visualization specifications from user queries expressed in natural language. We showcase the approach's flexibility in generating valid specifications in languages other than English (e.g., Spanish) despite lacking access to any training samples. Our findings represent the first steps towards the development of multilingual interfaces for data visualization that transcend English-centric systems, making them more accessible to a wider range of users.
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.
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.
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.
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.
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.
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/.
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.
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.
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.
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.
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.

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