Search

While face-based glyphs have known advantages for certain visualization tasks, they suffer from mixing two rather different visual properties of faces: individual traits and emotion expressions. This paper proposes a set of actions on stylized face glyphs that are compatible with psychological evidence embodied in the facial action coding system [EFH02]. It shows how this set can be employed for distinguishing emotion expressions from other facial expressions, and derives an emotion-based glyph space to exploit the pre-attentive processing of emotion expressions. Finally, we report the results of an empirical user study comparing Chernoff-like glyphs with our emotion glyphs in a typical visualization task., Evaluation and Representation, Antonia Schlieder, Philipp Wimmer, and Filip Sadlo

We present an analysis of the results of a full-day context-specific ideation exercise for smartwatch visualizations. Participants of the exercise created 34 sketches during a sightseeing activity. Our analysis of these sketches showed where visualizations could be applied and shown, what information needs they could target, and how data could be represented in the sightseeing context., Posters, Alaul Islam, Tanja Blascheck, and Petra Isenberg

In this paper, we present the results of an intervention designed to introduce parallel coordinates to students. The intervention contains six new modules inspired by Bloom's taxonomy that featured a combination of videos, tests, and tasks. We studied the impact of our modules with a corrective feedback mechanism inspired by Mastery Learning. Based on analyzing the data of our students, we found that students in the Corrective Immediate Feedback (CIF) group performed better on average on all the modules as compared to the students in the No Feedback (NF) group. In the tasks where students were required to construct parallel coordinates plots, students in the Corrective Immediate Feedback group produced plots with appropriate use of color, labels, legends, etc. Overall, students in both groups grew more confident in their ability to recognize parallel coordinates plots and expressed high confidence in their ability to interpret, create, and use parallel coordinates plots for data exploration and presentation in the future., Visualization and Curricula, Ilena Peng, Elif E. Firat, Robert S. Laramee, and Alark Joshi

Data are often subject to some degree of uncertainty, whether aleatory or epistemic. This applies both to experimental data acquired with sensors as well as to simulation data. Displaying these data and their uncertainty faithfully is crucial for gaining knowledge. Specifically, the effective communication of the uncertainty can influence the interpretation of the data and the users' trust in the visualization. However, uncertainty-aware visualization has gotten little attention in molecular visualization. When using the established molecular representations, the physicochemical attributes of the molecular data usually already occupy the common visual channels like shape, size, and color. Consequently, to encode uncertainty information, we need to open up another channel by using feature lines. Even though various line variables have been proposed for uncertainty visualizations, they have so far been primarily used for two-dimensional data and there has been little perceptual evaluation. Therefore, we conducted a perceptual study to determine the suitability of the line variables sketchiness, dashing, grayscale, and width for distinguishing several uncertainty values on molecular surfaces., Uncertainties, Ensembles, and Comparisons, Anna Sterzik, Nils Lichtenberg, Michael Krone, Douglas W. Cunningham, and Kai Lawonn

The visual representation of a graph is crucial in understanding and analyzing its properties. In this empirical study, we examine the effect of different drawing layouts on our perception of graph density. We treat density as an absolute property of the graph and use a Yes-No design, where participants have to decide whether a graph has a given density or not. We compare a simple grid layout with well-known planar and spring layouts. We also introduce an alternative 'improved' grid layout, which reduces the number of crossings while keeping most of the simplicity of the original grid layout. Results show that our 'improved' version of the grid layout facilitated performance on the task, compared to the original one. Moreover, participants were biased into judging graphs as denser when drawn with the original grid layout, while tended to perceive graphs as less dense when drawn with the planar and grid layouts. In contrast to previous studies on graph density perception, this is the first indication that the chosen layout can influence our perception of the graph's density., Graphs and Trees, Elektra Kypridemou, Michele Zito, and Marco Bertamini

Presentations are the most successful and popular form of communication in business. However, the formats of presentations in business have not changed much for past few decades. The emergent and disruptive technologies such as Augmented Reality and Animated Infographics have provided potential for enhancing communications in businesses to increase engagement and therefore increasing the effectiveness of such communications. This paper focuses on the impact and effectiveness of using interactive AR in business presentations. The paper presents the design and development of our AR presentation application. Followed by a presentation of an empirical study into the usability and effectiveness of using Augmented Reality and Animated Infographics in business presentation and compares the results against the traditional slideware slides presentation approach. The results of the experiment with 94 participants are presented and analysed. The results demonstrate that the AR approach out performs the traditional methods in terms of usability, audience engagement and effectiveness of communication.

We present a case study in the use of machine+human mixed intelligence for visualization quality assessment, applying automated visualization quality metrics to support the human assessment of data visualizations produced as coursework by students taking higher education courses. A set of image informatics algorithms including edge congestion, visual saliency and colour analysis generate machine analysis of student visualizations. The insight from the image informatics outputs has proved helpful for the marker in assessing the work and is also provided to the students as part of a written report on their work. Student and external reviewer comments suggest that the addition of the image informatics outputs to the standard feedback document was a positive step. We review the ethical challenges of working with assessment data and of automating assessment processes., Computer Graphics and Visual Computing (CGVC), Education, 49, 57, Nicolas S. Holliman, CCS Concepts: Human-centered computing --> Visualization design and evaluation methods; Empirical studies in visualization

Techniques for presenting objects spatially via density maps have been thoroughly studied, but there is lack of research on how to display this information in the presence of several classes, i.e., multiclass density maps. Moreover, there is even less research on how to design an interactive visualization for comparison tasks on multiclass density maps. One application domain which requires this type of visualization for comparison tasks is crime analytics, and the lack of research in this area results in ineffective visual designs. To fill this gap, we study four types of techniques to compare multiclass density maps, using car theft data. The interactive techniques studied are swipe, translucent overlay, magic lens, and juxtaposition. The results of a user study (N=32) indicate that juxtaposition yields the worst performance to compare distributions, whereas swipe and magic lens perform the best in terms of time needed to complete the experiment. Our research provides empirical evidence on how to design interactive idioms for multiclass density spatial data, and it opens a line of research for other domains and visual tasks., EuroVis 2021 - Short Papers, Analytics and Applications, 79, 83, Lukas Svicarovic, Denis Parra, and María Jesús Lobo, CCS Concepts: Human-centered computing--> Empirical studies in visualization; Visual analytics

Current blood vessel rendering usually depicts solely the surface of vascular structures and does not visualize any interior structures. While this approach is suitable for most applications, certain cardiovascular diseases, such as aortic dissection would benefit from a more comprehensive visualization. In this work, we investigate different shading styles for the visualization of the aortic inner and outer wall, including the dissection flap. Finding suitable shading algorithms, techniques, and appropriate parameters is time-consuming when practitioners fine-tune them manually. Therefore, we build a shading pipeline using wellknown shading algorithms such as Blinn-Phong, Oren-Nayar, Cook-Torrance, Toon, and extended Lit-Sphere shading with techniques such as the Fresnel effect and screen space ambient occlusion. We interviewed six experts from various domains to find the best combination of shadings for preset combinations that maximize user experience and the applicability in clinical settings., Eurographics Workshop on Visual Computing for Biology and Medicine, The path that blood takes, 107, 111, Kai Ostendorf, Domenico Mastrodicasa, Kathrin Bäumler, Marina Codari, Valery Turner, Martin J. Willemink, Dominik Fleischmann, Bernhard Preim, and Gabriel Mistelbauer, CCS Concepts: Human-centered computing --> Empirical studies in visualization; Applied computing --> Health informatics; Computing methodologies --> Non-photorealistic rendering; Visibility; Reflectance modeling

This paper provides an empirical, comparative exploration of the role of analytic frameworks in interpreting and modelling visual analytics behavior through data gathered in observational studies. The crucial research on understanding the complex and multi-faceted interplay between visual analytics tools and their users is often done through controlled or naturalistic observations of analysts engaging in the visual analytic process, followed by the interpretation of the observation data. The researchers in Human Computer Interaction and Cognitive Sciences have long used structured analytic frameworks for such analyses, where a guiding set of principles and questions direct attention to relevant aspects of the studied behavior, eventually leading to more complete and consistent analyses. Such frameworks are rarely applied in the visualization domain however, and information about how to apply them and their benefits is scarce. With this paper, we contribute a comparative account, grounded in empirical data collected in a user study with 10 participants using Tableau to analyze domain-specific data, of the types of insights we can glean from interpreting observational data using three different frameworks: Joint Action Theory, Distributed Cognition, and Situated Cognition., EuroVis 2020 - Short Papers, Analytics and Evaluation, 37, 41, Vanessa Brown, Cagatay Turkay, and Radu Jianu, CCS Concepts: Human-centered computing --> Empirical studies in visualization; Visualization theory, concepts and paradigms

International audience; Geographical propagation phenomena occur in multiple domains , such as in epidemiology and social media. Propagation dynamics are often complex, and visualizations play a key role in helping subject-matter experts understand and analyze them. However, there is little empirical data about the effectiveness of the various strategies used to visualize geographical propagation. To fill this gap, we conduct an experiment to evaluate the effectiveness of three strategies: an animated map, small-multiple maps, and a single map with glyphs. We compare them under five tasks that vary in one of the following dimensions: propagation scope, direction, speed, peaks, and spatial jumps. Our results show that small-multiple maps perform best overall, but that the effectiveness of each visualization varies depending on the task considered.

Mechanisms for guiding a user's visual attention to a particular point of interest play a crucial role in areas such as collaborative VR and AR, cinematic VR, and automated or live guided tour experiences in xR-based education. The attention guiding mechanism serves as a communication tool that helps users find entities currently not visible in their view, referenced for instance by another user or in some accompanying audio commentary. We report on a user study in which we compared three different visual guiding mechanisms (arrow, butterfly guide, and radar) in the context of 360° image-based educational VR tour applications of real-world sites. A fourth condition with no guidance tool available was added as a baseline. We investigate the question: How do the different approaches compare in terms of target finding performance and participants' assessments of the experiences. While all three mechanisms were perceived as improvements over the no-guidance condition and resulted in significantly improved target finding times, the arrow mechanism stands out as the most generally accepted and favored approach, whereas the other two (butterfly guide and radar) received a more polarized assessment due to their specific strengths and drawbacks.

Decades of research in psychology on the formal measurement of emotions led to the concept of affective states. Visualizing the measured affective state can be useful in education, as it allows teachers to adapt lessons based on the affective state of students. In the entertainment industry, game mechanics can be adapted based on the boredom and frustration levels of a player. Visualizing the affective state can also increase emotional self-awareness of the user whose state is being measured, which can have an impact on well-being. However, graphical user interfaces seldom visualize the user's affective state, but rather focus on the purely objective interaction between the system and the user. This paper proposes two graphical user interface widgets that visualize the user's affective state, ensuring a compact and unobtrusive visualization. In a user study with 644 participants, the widgets were evaluated in relation to a baseline widget and were tested on intuitiveness and understandability. Particularly in terms of understandability, the baseline was outperformed by our two widgets., EuroVis 2020 - Short Papers, Representation, Perception, and ML, 121, 125, Nikola Kovacevic, Rafael Wampfler, Barbara Solenthaler, Markus Gross, and Tobias Günther, CCS Concepts: Human-centered computing --> Empirical studies in visualization; User studies; Information visualization

Visualization literacy, the ability to interpret and understand visual designs, has gained momentum in the educational and information visualization communities. The goal of this research is to identify and address barriers to treemap literacy - a popular visual design, with a view to improve a non-expert user's treemap visualization literacy skills. In this paper we present the results of two years of an information visualization assignment, which are used to identify the barriers to and challenges of understanding and creating treemaps. From this, we develop a treemap visualization literacy test. Then, we propose a pedagogical tool that facilitates both teaching and learning of treemaps and advances treemap visualization literacy. To investigate the efficiency of this educational software, we then conduct a classroom-based study with 25 participants. We identify the properties of treemaps that can hinder literacy and cognition based on the results from the treemap visualization literacy test. Results also provide further support for the use of our tool that had a positive effect on treemap literacy skills of university students., Eurographics 2020 - Education Papers, Session 3, 29, 38, Elif E. Firat, Alena Denisova, and Robert S. Laramee, CCS Concepts: Human-centered computing --> Visualization systems and tools; Empirical studies in visualization

The way in which a graph is described visually is crucial for the understanding and analysis of its structure. In this study we explore how different drawing layouts affect our perception of the graph's properties. We study the perception of connectedness, tree-ness and density using four different layouts: the Circular, Grid, Planar and Spring layouts. Results show that some layouts are better than others when we need to decide whether a graph is a tree or is connected. More sophisticated algorithms, like Planar and Spring, facilitate our perception, while Circular and Grid layouts lead to performance not better than chance. However, when perceiving the density of a graph, no layout was found to be better than the others., EuroVis 2020 - Short Papers, Analytics and Evaluation, 1, 5, Elektra Kypridemou, Michele Zito, and Marco Bertamini, CCS Concepts: Human-centered computing --> Graph drawings; Empirical studies in visualization; Computing methodologies --> Perception

Mechanisms for guiding a user's visual attention to a particular point of interest play a crucial role in areas such as collaborative VR and AR, cinematic VR, and automated or live guided tour experiences in xR-based education. The attention guiding mechanism serves as a communication tool that helps users find entities currently not visible in their view, referenced for instance by another user or in some accompanying audio commentary. We report on a user study in which we compared three different visual guiding mechanisms (arrow, butterfly guide, and radar) in the context of 360° image-based educational VR tour applications of real-world sites. A fourth condition with no guidance tool available was added as a baseline. We investigate the question: How do the different approaches compare in terms of target finding performance and participants' assessments of the experiences. While all three mechanisms were perceived as improvements over the no-guidance condition and resulted in significantly improved target finding times, the arrow mechanism stands out as the most generally accepted and favored approach, whereas the other two (butterfly guide and radar) received a more polarized assessment due to their specific strengths and drawbacks.

Practitioners working to understand, combat, and inform the public about disinformation operations need tools to analyse these complex social phenomena, and communicate their findings to stakeholders. Temporal network visualization presents a means of analysing and communicating this dynamic socio-technical phenomenon, but comes with visualization design challenges that can be addressed through judicious iterative design and empirical evaluation. We present a path towards tailoring temporal network visualizations for DisInfoVis through qualitative evaluation, and outline a design for representing disinformation operations in social media networks informed by this process and used in public communication., EuroVis 2020 - Posters, Posters, 17, 19, Alexandra Melania Pavliuc and Jason Dykes, CCS Concepts: Information systems -->Social networks; Human-centered computing -->Information visualization; Empirical studies in visualization; Graph drawings; Visualization techniques; Security and privacy -->Social engineering attacks

Data from comments on social media platforms offer valuable information about trends and market changes. Aiming at the music industry, we propose SAMBAVis: a visual analytics tool to handle user-generated content from comments left on YouTube music videos. SAMBAVis displays main key performance indexes, video lifecycle, and engagement with comments. It also performs sentiment analysis and extracts the main keywords from the comments, expanding YouTube capabilities. In this paper, we contribute with a design study, explaining the development of SAMBAVis and the rationale of our design. We present a usage scenario and reflect on our methods and results when creating a visualization tool for experts in the music business., EuroVis 2020 - Short Papers, Analytics and Evaluation, 13, 17, Victor Adriel de Jesus Oliveira, Christina Stoiber, Johanna Grüblbauer, Christoph Musik, Alexis Ringot, and Andreas Gebesmair, CCS Concepts: Human-centered computing --> Visual analytics; Empirical studies in visualization

International audience; This paper presents a position paper on subspace projection evaluation methods in interactive visual systems. We focus on how to evaluate real information rendered through the visual data projection for the mining of high dimensional data sets. To do this, we investigate automatic techniques that select the best visual projection and we discuss how they evaluate the projections to help the user before interactivity. When we deal with high dimensional data sets, the number of potential projections exceeds the limit of human interpretation. To find the optimal subspace representation, there are two possibilities, the first one is to find the optimal subspace which reproduces what really exists in the original data: getting the existing clusters and/or outliers in the projection. The second possibility consists in researching subspaces according to the knowledge discovery process: discovering novel, but meaningful information, such as clusters and/or outliers from the projection. The problem is that visual projection cannot be in adequation with the subspaces. In some cases, the visual projection can show some things that do not really exist in the original data space (which can be considered as an artifact). The mapping between the visual structure and the real data structure is as important as the efficiency and accuracy of the visualization. We examine and discuss the literature of Information visualization, Visual analytic, High dimensional data visualization, and interactive data mining and machine learning communities, on how to evaluate the faithfulness of the visual projection information.

We contribute the results of an exploratory study and a survey on visualizations for fitness trackers. Fitness trackers are becoming ubiquitous trackers of personal data. They often come with small attached displays that show micro visualizations of data such as heart rate, step counts, sleep duration, or number of floors climbed. Unfortunately, little is known about how wearers of fitness trackers use and perceive these micro visualizations. To collect data on the use of fitness visualizations, we conducted ten personal interviews with regular wearers of fitness trackers. Inspired by frequent responses regarding sleep tracking, we deployed an online questionnaire specifically on sleep visualizations for fitness trackers. Our results show that most participants were interested particularly in seeing previous night's sleep data on their fitness trackers and preferred visualizations that were easy to read like the hypnogram and bar as well as donut charts for sleep phases and duration., EuroVis 2019 - Posters, Posters, 85, 87, Ranjini Aravind, Tanja Blascheck, and Petra Isenberg, CCS Concepts: Human-centered computing --> Empirical studies in visualization; Visualization design and evaluation methods

Traffic congestion causes major economic, environmental and social problems in modern cities. We present an interactive visualization tool to assist domain experts on the identification and analysis of traffic patterns at a city scale making use of multivariate empirical urban data and fundamental diagrams. The proposed method combines visualization techniques with an improved local principle curves method to model traffic dynamics and facilitate comparison of traffic patterns - resorting to the fitted curve with a confidence interval - between different road segments and for different external conditions. We demonstrate the proposed technique in an illustrative real-world case study in the city of Porto, Portugal., Machine Learning Methods in Visualisation for Big Data, Papers, 13, 17, Carla Silva, Pedro M. d'Orey, and Ana Aguiar, CCS Concepts: Human-centered computing --> Visual analytics; Empirical studies in visualization; Computing methodologies --> Machine learning approaches; Modeling and simulation; Shape modeling"

Cognitive bias is a systematic error that introduces drifts and distortions in the human judgment in terms of visual decomposition in the direction of the dominant instance. It has a significant role in decision-making process by means of evaluation of data visualizations. This paper elaborates on the experimental depiction of two cognitive bias types, namely Distinction Bias and Confirmation Bias, through the examination of cognate visual experimentations. The main goal of this implementation is to indicate the existence of cognitive bias in visual analytics systems through the adjustment of data visualization and crowdsourcing in terms of confirmation and distinction biases. Two distinct surveys that include biased and unbiased data visualizations which are related to a given data set were established in order to detect and measure the level of existence of introduced bias types. Practice of crowdsourcing which is provided by Amazon Mechanical Turk have been used for experimentation purposes through prepared surveys. Results statistically indicate that both distinction and confirmation biases has substantial effect and prominent significance on decision-making process., EuroVis Workshop on Trustworthy Visualization (TrustVis), Papers, 13, 17, Atilla Alpay Nalcaci, Dilara Girgin, Semih Balki, Fatih Talay, Hasan Alp Boz, and Selim Balcisoy, CCS Concepts: Human-centered computing --> Empirical studies in visualization; Visualization design and evaluation methods

Experts in different domains rely increasingly on simulation models of complex processes to reach insights, make decisions, and plan future projects. These models are often used to study possible trade-offs, as experts try to optimise multiple conflicting objectives in a single investigation. Understanding all the model intricacies, however, is challenging for a single domain expert. We propose a simple approach to support multiple experts when exploring complex model results. First, we reduce the model exploration space, then present the results on a shared interactive surface, in the form of a scatterplot matrix and linked views. To explore how multiple experts analyse trade-offs using this setup, we carried out an observational study focusing on the link between expertise and insight generation during the analysis process. Our results reveal the different exploration strategies and multi-storyline approaches that domain experts adopt during trade-off analysis, and inform our recommendations for collaborative model exploration systems., Comment: This paper will be published in Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI 2019)

Reflectance Transformation Imaging (RTI) is widely used to produce relightable models from multi-light image collections.These models are used for a variety of tasks in the Cultural Heritage field. In this work, we carry out an objective and sub-jective evaluation of RTI data visualization. We start from the acquisition of a series of objects with different geometry andappearance characteristics using a common dome-based configuration. We then transform the acquired data into relightablerepresentations using different approaches: PTM, HSH, and RBF. We then perform an objective error estimation by comparingground truth images with relighted ones in a leave-one-out framework using PSNR and SSIM error metrics. Moreover, we carryout a subjective investigation through perceptual experiments involving end users with a variety of backgrounds. Objective andsubjective tests are shown to behave consistently, and significant differences are found between the various methods. While theproposed analysis has been performed on three common and state-of-the-art RTI visualization methods, our approach is gen-eral enough to be extended and applied in the future to new developed multi-light processing pipelines and rendering solutions,to assess their numerical precision and accuracy, and their perceptual visual quality. Terms: "European Union (EU)" & "Horizon 2020" / Action: H2020-EU.3.6.3. - Reflective societies - cultural heritage and European identity / Acronym: Scan4Reco / Grant number: 665091

Visual differencing, or visual discrimination, is the ability to differentiate between two or more objects in a scene depending on the values of certain attributes. Focusing on multivariate maps visualization, this work examined human’s predictable bias in interpreting visual-spatial information and inference making. Moreover, this study seeks to develop and evaluate new techniques to mitigate the trade-off between proximity and occlusion and to enable analysts to explore multivariate maps. Therefore, we developed a multi-criteria decision-making technique for land suitability using multivariate maps, and we carried out a user study where users are tasked to choose the most suitable piece of land to plant grapes. We designed the user study to evaluate mapping a map’s layers (variables) to visual channels (Transparency, Hue, Saturation and Brightness/Lightness); two color spaces were used Hue Saturation Value (HSV)and Hue Saturation Lightness (HSL). The categorical variables were mapped to the Hue channel and the quantitative/ordinal variables were mapped to either Saturation, Brightness/lightness, or Transparency channels. Our online user study was taken by 85 participants to test the users’ perception of different map visualizations. The statistical analysis of survey responses showed that mapping quantitative layers to the Transparency channel outperformed the other channels, and the use of HSV color space showed a more efficient mapping than HSL, especially for the extreme values in the dataset.

International audience; Many households share the objective of reducing electricity consumption for either economic or ecological motivations. Eco-feedback technologies support this objective by providing users with a visualization of their consumption. However as pointed out by several studies, users encounter difficulties in finding concrete actions to reduce their consumption. To overcome this limitation, we introduce in this paper Activelec, a system based on the visualization and interaction with user's behavior rather than raw consumption data. The user's behavior is modeled as the set of actions modifying the state of appliances over time. A key novelty of our solution is its focus on the What if approach applied to eco-feedback. Users can analyze and experiment scenarios by selecting and modifying their usage of electrical appliances over time and visualize the impact on the consumption. We conduct two user studies that evaluate the usability of Activelec and the relevance of the What if approach for electricity consumption. Our results show that users understand the interaction paradigm and can easily find relevant modifications in their usage of appliances. Moreover participants judge these changes of behavior would require little effort to be adopted. Therefore our work opens new perspectives on using the What if approach in the context of eco-feedback technology.

Reflectance Transformation Imaging (RTI) is widely used to produce relightable models from multi-light image collections. These models are used for a variety of tasks in the Cultural Heritage field. In this work, we carry out an objective and subjective evaluation of RTI data visualization. We start from the acquisition of a series of objects with different geometry and appearance characteristics using a common dome-based configuration. We then transform the acquired data into relightable representations using different approaches: PTM, HSH, and RBF. We then perform an objective error estimation by comparing ground truth images with relighted ones in a leave-one-out framework using PSNR and SSIM error metrics. Moreover, we carry out a subjective investigation through perceptual experiments involving end users with a variety of backgrounds. Objective and subjective tests are shown to behave consistently, and significant differences are found between the various methods. While the proposed analysis has been performed on three common and state-of-the-art RTI visualization methods, our approach is general enough to be extended and applied in the future to new developed multi-light processing pipelines and rendering solutions, to assess their numerical precision and accuracy, and their perceptual visual quality., Eurographics Workshop on Graphics and Cultural Heritage, 3D Reconstruction for CH, 87, 96, Ruggero Pintus, Tinsae Dulecha, Alberto Jaspe, Andrea Giachetti, Irina Ciortan, and Enrico Gobbetti, CCS Concepts: Human-centered computing --> Empirical studies in visualization; Computing methodologies --> Visual inspection; Image representations