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Ynnerman, Anders, ProfessorORCID iD iconorcid.org/0000-0002-9466-9826
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Publications (10 of 160) Show all publications
Fujiwara, T., Kucher, K., Wang, J., Martins, R. M., Kerren, A. & Ynnerman, A. (2025). Adversarial Attacks on Machine Learning-Aided Visualizations. Journal of Visualization, 28(1), 133-151
Open this publication in new window or tab >>Adversarial Attacks on Machine Learning-Aided Visualizations
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2025 (English)In: Journal of Visualization, ISSN 1343-8875, E-ISSN 1875-8975, Vol. 28, no 1, p. 133-151Article in journal (Refereed) Published
Abstract [en]

Research in ML4VIS investigates how to use machine learning (ML) techniques to generate visualizations, and the field is rapidly growing with high societal impact. However, as with any computational pipeline that employs ML processes, ML4VIS approaches are susceptible to a range of ML-specific adversarial attacks. These attacks can manipulate visualization generations, causing analysts to be tricked and their judgments to be impaired. Due to a lack of synthesis from both visualization and ML perspectives, this security aspect is largely overlooked by the current ML4VIS literature. To bridge this gap, we investigate the potential vulnerabilities of ML-aided visualizations from adversarial attacks using a holistic lens of both visualization and ML perspectives. We first identify the attack surface (i.e., attack entry points) that is unique in ML-aided visualizations. We then exemplify five different adversarial attacks. These examples highlight the range of possible attacks when considering the attack surface and multiple different adversary capabilities. Our results show that adversaries can induce various attacks, such as creating arbitrary and deceptive visualizations, by systematically identifying input attributes that are influential in ML inferences. Based on our observations of the attack surface characteristics and the attack examples, we underline the importance of comprehensive studies of security issues and defense mechanisms as a call of urgency for the ML4VIS community.

Place, publisher, year, edition, pages
Springer, 2025
Keywords
ML4VIS, AI4VIS, Visualization, Cybersecurity, Neural networks, Parametric dimensionality reduction, Chart recommendation
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:liu:diva-207771 (URN)10.1007/s12650-024-01029-2 (DOI)001316813100001 ()
Funder
Knut and Alice Wallenberg Foundation, 2019.0024ELLIIT - The Linköping‐Lund Initiative on IT and Mobile Communications
Note

Funding Agencies: Knut and Alice Wallenberg Foundation [KAW 2019.0024]; ELLIIT environment for strategic research in Sweden

Available from: 2024-09-21 Created: 2024-09-21 Last updated: 2025-04-22
Falk, M., Tobiasson, V., Bock, A., Hansen, C. & Ynnerman, A. (2024). A Visual Environment for Data Driven Protein Modeling and Validation. IEEE Transactions on Visualization and Computer Graphics, 30(8), 5063-5073
Open this publication in new window or tab >>A Visual Environment for Data Driven Protein Modeling and Validation
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2024 (English)In: IEEE Transactions on Visualization and Computer Graphics, ISSN 1077-2626, E-ISSN 1941-0506, Vol. 30, no 8, p. 5063-5073Article in journal (Refereed) Published
Abstract [en]

In structural biology, validation and verification of new atomic models are crucial and necessary steps which limit the production of reliable molecular models for publications and databases. An atomic model is the result of meticulous modeling and matching and is evaluated using a variety of metrics that provide clues to improve and refine the model so it fits our understanding of molecules and physical constraints. In cryo electron microscopy (cryo-EM) the validation is also part of an iterative modeling process in which there is a need to judge the quality of the model during the creation phase. A shortcoming is that the process and results of the validation are rarely communicated using visual metaphors.

This work presents a visual framework for molecular validation. The framework was developed in close collaboration with domain experts in a participatory design process. Its core is a novel visual representation based on 2D heatmaps that shows all available validation metrics in a linear fashion, presenting a global overview of the atomic model and provide domain experts with interactive analysis tools. Additional information stemming from the underlying data, such as a variety of local quality measures, is used to guide the user's attention toward regions of higher relevance. Linked with the heatmap is a three-dimensional molecular visualization providing the spatial context of the structures and chosen metrics. Additional views of statistical properties of the structure are included in the visual framework. We demonstrate the utility of the framework and its visual guidance with examples from cryo-EM.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2024
Keywords
molecular visualization, cryo-EM, model validation, verification
National Category
Computer Sciences
Identifiers
urn:nbn:se:liu:diva-195458 (URN)10.1109/tvcg.2023.3286582 (DOI)001262914400069 ()37327104 (PubMedID)
Funder
ELLIIT - The Linköping‐Lund Initiative on IT and Mobile CommunicationsSwedish Research Council, 2015-05462Knut and Alice Wallenberg Foundation, KAW 2019.0024NIH (National Institutes of Health), R01EB023947NIH (National Institutes of Health), R01EB031872
Note

The supplemental material is available under https://osf.io/pqymt/ (DOI: 10.17605/OSF.IO/PQYMT).

Funding Agencies|Excellence Center at Link#x00F6; ping and Lund in Information Technology; Swedish e-Science Research Centre (SeRC); Swedish Research Council (VR) [2015-05462]; NIH [R01EB023947, R01EB031872]; Knut and Alice Wallenberg Foundation [KAW 2019.0024]

Available from: 2023-06-20 Created: 2023-06-20 Last updated: 2024-08-20Bibliographically approved
Elmquist, E., Ejdbo, M., Bock, A., Thaler, D. S., Ynnerman, A. & Rönnberg, N. (2024). Birdsongification: Contextual and Complementary Sonification for Biology Visualization. Paper presented at 29th International Conference on Auditory Display. Proceedings of the International Conference on Auditory Display, 34-41
Open this publication in new window or tab >>Birdsongification: Contextual and Complementary Sonification for Biology Visualization
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2024 (English)In: Proceedings of the International Conference on Auditory Display, ISSN 1093-9547, E-ISSN 2168-5126, p. 34-41Article in journal (Refereed) Published
Abstract [en]

Choosing whether to represent data in an abstract or concrete manner through sonification is generally dependent on the applicability of the dataset and personal preference of the designer. For supporting a visualization with a high level of abstraction, a sonification can purposefully act as a complement by giving concrete contextual cues to the data representation with the use of auditory icons. This paper presents a case study of using bird songs as auditory icons to give context to a biology visualization, and explores how additional information of the bird species can be conveyed together with the auditory icons with parameter mapping sonification. The auditory icons are used as a foundation to convey additional information of the dataset, either by creating a parametric auditory icon, or by adding an additional sonification that accompanies the auditory icon. A user evaluation was conducted to validate and compare the different sonification mappings. The results show that there is a subjective difference of how participants perceived the sonifications, where the participants preferred sonifications that had a concrete mapping design. The sonification approaches that are explored in this study have the potential to be applied to more general sonification designs.

National Category
Other Engineering and Technologies
Identifiers
urn:nbn:se:liu:diva-208608 (URN)10.21785/icad2024.006 (DOI)
Conference
29th International Conference on Auditory Display
Funder
Knut and Alice Wallenberg Foundation, 2019.0024
Available from: 2024-10-17 Created: 2024-10-17 Last updated: 2025-05-05Bibliographically approved
Zohrevandi, E., Vrotsou, K., Westin, C., Lundberg, J. & Ynnerman, A. (2024). Design of a Real-Time Visual Analytics Decision Support Interface to Manage Air Traffic Complexity. In: Johanna Beyer, Takayuki Itoh, Charles Perin, and Hongfeng Yu (Ed.), 2024 IEEE VISUALIZATION AND VISUAL ANALYTICS, VIS: . Paper presented at 2024 IEEE Visualization Conference, Tampa Bay, FL, USA (Virtual), 13-18 October 2024 (pp. 301-305). IEEE
Open this publication in new window or tab >>Design of a Real-Time Visual Analytics Decision Support Interface to Manage Air Traffic Complexity
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2024 (English)In: 2024 IEEE VISUALIZATION AND VISUAL ANALYTICS, VIS / [ed] Johanna Beyer, Takayuki Itoh, Charles Perin, and Hongfeng Yu, IEEE, 2024, p. 301-305Conference paper, Published paper (Refereed)
Abstract [en]

An essential task of an air traffic controller is to manage the traffic flow by predicting future trajectories. Complex traffic patterns are difficult to predict and manage and impose cognitive load on the air traffic controllers. In this work we present an interactive visual analytics interface which facilitates detection and resolution of complex traffic patterns for air traffic controllers. The interface supports air traffic controllers in detecting complex clusters of aircraft and further enables them to visualize and simultaneously compare how different re-routing strategies for each individual aircraft yield reduction of complexity in the entire sector for the next hour. The development of the concepts was supported by the domain-specific feedback we received from six fully licensed and operational air traffic controllers in an iterative design process over a period of 14 months.

Place, publisher, year, edition, pages
IEEE, 2024
Series
IEEE Visualization Conference, ISSN 2771-9537, E-ISSN 2771-9553
Keywords
Visual analytics; Visualization design; Safety-critical systems; Design study; Focus+context techniques
National Category
Computer and Information Sciences Human Computer Interaction Computer and Information Sciences
Identifiers
urn:nbn:se:liu:diva-210012 (URN)10.1109/vis55277.2024.00068 (DOI)001447839700061 ()2-s2.0-85215289334 (Scopus ID)9798350354867 (ISBN)9798350354850 (ISBN)
Conference
2024 IEEE Visualization Conference, Tampa Bay, FL, USA (Virtual), 13-18 October 2024
Funder
Swedish Research Council, 2015-04706Swedish Transport Administration, 2022/108265Knut and Alice Wallenberg Foundation, 2019.0024
Note

Funding Agencies|Swedish Transport Administration (Trafikverket) under the project KOMPLEX [TRV 2022/108265]; Swedish Research Council (Vetenskapsradet) [2015-04706]; Knut and Alice Wallenberg Foundation [KAW 2019.0024]

Available from: 2024-11-25 Created: 2024-11-25 Last updated: 2025-05-21
Eilertsen, G., Jönsson, D., Unger, J. & Ynnerman, A. (2024). Model-invariant Weight Distribution Descriptors for Visual Exploration of Neural Networks en Masse. In: Christian Tominski, Manuela Waldner, and Bei Wang (Ed.), EuroVis 2024 - Short Papers: . Paper presented at EuroVis. Eurographics - European Association for Computer Graphics
Open this publication in new window or tab >>Model-invariant Weight Distribution Descriptors for Visual Exploration of Neural Networks en Masse
2024 (English)In: EuroVis 2024 - Short Papers / [ed] Christian Tominski, Manuela Waldner, and Bei Wang, Eurographics - European Association for Computer Graphics, 2024Conference paper, Published paper (Refereed)
Abstract [en]

We present a neural network representation which can be used for visually analyzing the similarities and differences in a large corpus of trained neural networks. The focus is on architecture-invariant comparisons based on network weights, estimating similarities of the statistical footprints encoded by the training setups and stochastic optimization procedures. To make this possible, we propose a novel visual descriptor of neural network weights. The visual descriptor considers local weight statistics in a model-agnostic manner by encoding the distribution of weights over different model depths. We show how such a representation can extract descriptive information, is robust to different parameterizations of a model, and is applicable to different architecture specifications. The descriptor is used to create a model atlas by projecting a model library to a 2D representation, where clusters can be found based on similar weight properties. A cluster analysis strategy makes it possible to understand the weight properties of clusters and how these connect to the different datasets and hyper-parameters used to train the models.

Place, publisher, year, edition, pages
Eurographics - European Association for Computer Graphics, 2024
Keywords
machine learning, deep learning, visualization
National Category
Computer and Information Sciences Computer and Information Sciences
Identifiers
urn:nbn:se:liu:diva-205660 (URN)10.2312/evs.20241068 (DOI)978-3-03868-251-6 (ISBN)
Conference
EuroVis
Funder
Wallenberg AI, Autonomous Systems and Software Program (WASP)
Available from: 2024-06-28 Created: 2024-06-28 Last updated: 2025-02-18
Elmquist, E., Enge, K., Rind, A., Navarra, C., Höldrich, R., Iber, M., . . . Rönnberg, N. (2024). Parallel Chords: an audio-visual analytics design for parallel coordinates. Personal and Ubiquitous Computing, 28(5), 657-676
Open this publication in new window or tab >>Parallel Chords: an audio-visual analytics design for parallel coordinates
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2024 (English)In: Personal and Ubiquitous Computing, ISSN 1617-4909, E-ISSN 1617-4917, Vol. 28, no 5, p. 657-676Article in journal (Refereed) Published
Abstract [en]

One of the commonly used visualization techniques for multivariate data is the parallel coordinates plot. It provides users with a visual overview of multivariate data and the possibility to interactively explore it. While pattern recognition is a strength of the human visual system, it is also a strength of the auditory system. Inspired by the integration of the visual and auditory perception in everyday life, we introduce an audio-visual analytics design named Parallel Chords combining both visual and auditory displays. Parallel Chords lets users explore multivariate data using both visualization and sonification through the interaction with the axes of a parallel coordinates plot. To illustrate the potential of the design, we present (1) prototypical data patterns where the sonification helps with the identification of correlations, clusters, and outliers, (2) a usage scenario showing the sonification of data from non-adjacent axes, and (3) a controlled experiment on the sensitivity thresholds of participants when distinguishing the strength of correlations. During this controlled experiment, 35 participants used three different display types, the visualization, the sonification, and the combination of these, to identify the strongest out of three correlations. The results show that all three display types enabled the participants to identify the strongest correlation — with visualization resulting in the best sensitivity. The sonification resulted in sensitivities that were independent from the type of displayed correlation, and the combination resulted in increased enjoyability during usage.

Place, publisher, year, edition, pages
Springer, 2024
National Category
Other Engineering and Technologies
Identifiers
urn:nbn:se:liu:diva-203454 (URN)10.1007/s00779-024-01795-8 (DOI)2-s2.0-85191992877 (Scopus ID)
Funder
Knut and Alice Wallenberg Foundation, 2019.0024
Available from: 2024-05-13 Created: 2024-05-13 Last updated: 2025-04-24
Ståhlbom, E., Molin, J., Ynnerman, A. & Lundström, C. (2024). Should I make it round? Suitability of circular and linear layouts for comparative tasks with matrix and connective data. Computer graphics forum (Print), 43(3), Article ID e15102.
Open this publication in new window or tab >>Should I make it round? Suitability of circular and linear layouts for comparative tasks with matrix and connective data
2024 (English)In: Computer graphics forum (Print), ISSN 0167-7055, E-ISSN 1467-8659, Vol. 43, no 3, article id e15102Article in journal (Refereed) Published
Abstract [en]

Visual representations based on circular shapes are frequently used in visualization applications. One example are circos plots within bioinformatics, which bend graphs into a wheel of information with connective lines running through the center like spokes. The results are aesthetically appealing and impressive visualizations that fit long data sequences into a small quadratic space. However, the authors' experiences are that when asked, a visualization researcher would generally advise against making visualizations with radial layouts. Upon reviewing the literature we found that there is evidence that circular layouts are preferable in some cases, but we found no clear evidence for what layout is preferable for matrices and connective data in particular, which both are common data types in circos plots. In this work, we thus performed a user study to compare circular and linear layouts. The tasks are inspired by genomics data, but our results generalize to many other application areas, involving comparison and connective data. To build the prototype we utilized Gosling, a grammar for visualizing genomics data. We contribute empirical evidence on the suitedness of linear versus circular layouts, adding to the specific and general knowledge concerning perception of circular graphs. In addition, we contribute a case study evaluation of the grammar Gosling as a rapid prototyping language, confirming its utility and providing guidance on suitable areas for future development.

Place, publisher, year, edition, pages
WILEY, 2024
Keywords
-> Genomics
National Category
Computer graphics and computer vision
Identifiers
urn:nbn:se:liu:diva-205158 (URN)10.1111/cgf.15102 (DOI)001243045800001 ()
Note

Funding Agencies|Knut and Alice Wallenberg Foundation

Available from: 2024-06-20 Created: 2024-06-20 Last updated: 2025-02-07Bibliographically approved
Elmquist, E., Bock, A., Ynnerman, A. & Rönnberg, N. (2024). Towards a Systematic Scene Analysis Framework for Audiovisual Data Representations. In: Audiovisual Symposium notes: . Paper presented at Audiovisual Symposium. Falun
Open this publication in new window or tab >>Towards a Systematic Scene Analysis Framework for Audiovisual Data Representations
2024 (English)In: Audiovisual Symposium notes, Falun, 2024Conference paper, Oral presentation with published abstract (Refereed)
Place, publisher, year, edition, pages
Falun: , 2024
Keywords
Audiovisual integration, Visualization, Sonification, Scene graph, Scene analysis
National Category
Other Engineering and Technologies
Identifiers
urn:nbn:se:liu:diva-210422 (URN)
Conference
Audiovisual Symposium
Funder
Knut and Alice Wallenberg Foundation, 2019.0024
Available from: 2024-12-13 Created: 2024-12-13 Last updated: 2025-03-21
Zohrevandi, E., Brorsson, E., Darnell, A., Bång, M., Lundberg, J. & Ynnerman, A. (2023). Design of an Ecological Visual Analytics Interface for Operators of Time-Constant Processes. In: 2023 IEEE Visualization and Visual Analytics (VIS): . Paper presented at 2023 IEEE Visualization Conference, Melbourne, Australia (Hybrid), 22-27 October 2023 (pp. 131-135). IEEE
Open this publication in new window or tab >>Design of an Ecological Visual Analytics Interface for Operators of Time-Constant Processes
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2023 (English)In: 2023 IEEE Visualization and Visual Analytics (VIS), IEEE, 2023, p. 131-135Conference paper, Published paper (Refereed)
Abstract [en]

In industrial applications where the physical parameters are highly interconnected, keeping the process flow steady is a major concern for the operators. This is caused by the sensitivity of system to the process dynamics. As a result, a slight adjustment to a control parameter can significantly affect the efficiency of the system and thus impact the financial gain. Paper pulp production is an example of such a process, where operators continuously investigate the potential of changes in the process and predict the consequences of an adjustment before making a decision. Process parameter adjustments prescribed by simulated control models cannot be fully trusted as the external disturbances and the process inherent variabilities cannot be fully incorporated into the simulations. Therefore, to assess the viability of a strategy, operators often compare the situation with the historical records and trends during which the processes in the plant ran steadily. While previous research has mostly focused on developing advanced control models to simulate complex pulp production process, this work aims to support operators analytical reasoning by provision of effective data visualization. The contributions of our design study include a domain problem characterization and a linked-view visual encoding design, which aims to enhance operator's mental models independent of particular users or scenarios. Finally, by reflecting on the advantages of our choice of task abstraction technique, inherited from the ecological interface design framework [5], we reason for the generalizability of our approach to similar industrial applications.

Place, publisher, year, edition, pages
IEEE, 2023
Series
IEEE Visualization Conference, ISSN 2771-9537, E-ISSN 2771-9553
Keywords
Visual analytics interfaces; Design study; Focus+context techniques; Linked-view interfaces; Time-constant processes
National Category
Production Engineering, Human Work Science and Ergonomics Computer Systems
Identifiers
urn:nbn:se:liu:diva-199828 (URN)10.1109/VIS54172.2023.00035 (DOI)001137142800027 ()9798350325577 (ISBN)9798350325584 (ISBN)
Conference
2023 IEEE Visualization Conference, Melbourne, Australia (Hybrid), 22-27 October 2023
Note

Funding agencies: The Sweden’s Innovation Agency (Vinnova) under the project EXPLAIN (2021-04336) and the Knutand Alice Wallenberg Foundation (grant KAW 2019.0024).

Available from: 2023-12-22 Created: 2023-12-22 Last updated: 2024-11-25
Elmquist, E., Bock, A., Lundberg, J., Ynnerman, A. & Rönnberg, N. (2023). SonAir: the design of a sonification of radar data for air traffic control. Journal on Multimodal User Interfaces, 17(3), 137-149
Open this publication in new window or tab >>SonAir: the design of a sonification of radar data for air traffic control
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2023 (English)In: Journal on Multimodal User Interfaces, ISSN 1783-7677, E-ISSN 1783-8738, Vol. 17, no 3, p. 137-149Article in journal (Refereed) Published
Abstract [en]

Along with the increase of digitalization and automation, a new kind of working environment is emerging in the field of air traffic control. Instead of situating the control tower at the airport, it is now possible to remotely control the airport at any given location, i.e. in a remote tower center (RTC). However, by controlling the airport remotely, the situational awareness and sense of presence might be compromised. By using directional sound, a higher situational awareness could potentially be achieved while also offloading the visual perception which is heavily used in air traffic control. Suitable use cases for sonification in air traffic control were found through workshops with air traffic controllers. A sonification design named SonAir was developed based on the outcome of the workshops, and was integrated with an RTC simulator for evaluating to what degree SonAir could support air traffic controllers in their work. The results suggest that certain aspects of SonAir could be useful for air traffic controllers. A continuous sonification where the spatial positioning of aircraft were conveyed was experienced to be partially useful, but the intrusiveness of SonAir should be further considered to fit the air traffic controllers’ needs. An earcon that conveyed when an aircraft enters the airspace and from which direction was considered useful to support situational awareness.

Place, publisher, year, edition, pages
SPRINGER, 2023
Keywords
Sonification; Air traffic control; Situational awareness; User evaluation
National Category
Other Engineering and Technologies
Identifiers
urn:nbn:se:liu:diva-196256 (URN)10.1007/s12193-023-00404-x (DOI)001021523300001 ()
Note

Funding: Swedish Transport Authority [TRV-2019/53555]; Knut and Alice Wallenberg Foundation [KAW 2019.0024]

Available from: 2023-07-08 Created: 2023-07-08 Last updated: 2025-03-21
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ORCID iD: ORCID iD iconorcid.org/0000-0002-9466-9826

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