The Gulf of Interpretation: From Chart to Message and Back AgainCharts are used to communicate data visually, but often, we do not know whether a chart's intended message aligns with the message readers perceive. In this mixed-methods study, we investigate how data journalists encode data and how members of a broad audience engage with, experience, and understand these visualizations. We conducted workshops and interviews with school and university students, job seekers, designers, and senior citizens to collect perceived messages and feedback on eight real-world charts. We analyzed these messages and compared them to the intended message. Our results help to understand the gulf that can exist between messages (that producers encode) and viewer interpretations. In particular, we find that consumers are often overwhelmed with the amount of data provided and are easily confused with terms that are not well known. Chart producers tend to follow strong conventions on how to visually encode particular information that might not always benefit consumers.2025CKChristian Knoll et al.University of Vienna, Faculty of Computer Science, Doctoral School Computer ScienceInteractive Data VisualizationVisualization Perception & CognitionCHI
Exploring the Fit: Analysing Material Selection for Interactive Markers in MAR Games through Co-DesignUnderstanding how different user groups interact and perceive material selection for interactive markers in mobile augmented reality (MAR) games is essential for effective design. This study uses a qualitative approach, incorporating interviews and workshops to examine the preferences and behaviours of designers (N=6) and children (N=8). Designers highlighted the importance of using versatile and environmentally sustainable materials that can be customised for various games. Meanwhile, children’s interactions with these materials revealed challenges such as decision-making pressure and reliance on peer collaboration to navigate unfamiliar materials. The study identified five critical considerations for selecting materials: simplification, customisation, sustainability, balanced creativity, and collaboration. Our results show that while designers prioritise creative potential, user engagement is influenced by material ease and collaboration. This study provides key insights into the design considerations for MAR games, suggesting aligning designer expectations with actual user behaviour for creating successful and immersive MAR experiences.2025VTVinaya Tawde et al.Masaryk UniversityInteractive Narrative & Immersive StorytellingCHI
Embodied Measurement: Tangible Interactions to Enhance the Validity of Self-Report MeasuresThis work introduces the concept of Embodied Measurement (EM), designed to improve the validity and inclusivity of cognitive load assessments by incorporating physical interactions that mirror mental effort. We implemented a haptic force-feedback turning knob as an alternative to traditional Likert-scale ratings and compared it with visual (mouse-based) and combined (haptic and visual) modalities. Participants completed a cognitive load task with varying difficulty levels using each modality, while biosignals such as heart rate variability, skin conductance, and pupil size were recorded to objectively assess cognitive load. In addition, qualitative feedback was gathered to explore participants' experiences with each input method. Our findings highlight the potential of EM to offer more tangible and intuitive ways of measuring cognitive load, with the combined modality providing the most comprehensive feedback. This study contributes to human-computer interaction (HCI) research by proposing new approaches for measuring cognitive and emotional effort through physical interaction.2025JUJakob Carl Uhl et al.Austrian Institute of Technology; Paris Lodron University of SalzburgForce Feedback & Pseudo-Haptic WeightVisualization Perception & CognitionComputational Methods in HCICHI
Encountering Friction, Understanding Crises: How Do Digital Natives Make Sense of Crisis Maps?Crisis maps are regarded as crucial tools in crisis communication, as demonstrated during the COVID-19 pandemic and climate change crises. However, there is limited understanding of how public audiences engage with these maps and extract essential information. Our study investigates the sensemaking of young, digitally native viewers as they interact with crisis maps. We integrate frameworks from the learning sciences and human-data interaction to explore sensemaking through two empirical studies: a thematic analysis of online comments from a New York Times series on graph comprehension, and interviews with 18 participants from German-speaking regions. Our analysis categorizes sensemaking activities into established clusters: inspecting, engaging with content, and placing, and introduces responding personally to capture the affective dimension. We identify friction points connected to these clusters, including struggles with color concepts, responses to missing context, lack of personal connection, and distrust, offering insights for improving crisis communication to public audiences.2025LKLaura Koesten et al.|University of Vienna, Faculty of Computer ScienceGeospatial & Map VisualizationSmart Cities & Urban SensingClimate Change Communication ToolsCHI
Chatting About Data - Interacting with Voice Interfaces to Engage with Election Panel DataThe importance of data is increasing and so is the use of voice-interface-chatbots. While tasks that can be handled by chatbots are still relatively simple, analysing data can be a difficult task for non-experts. The aim of the research was to show how an interaction with a voice-interface-chatbot to explore data can work. In a preliminary study we investigated what questions are asked by people when looking at tabular data. We then conducted a Wizard of Oz study with a voice-interface-chatbot that can answer questions about the National Council elections with text or graphs. In 15 interviews 1235 messages were exchanged, of which 159 were categorized as information requests. Our study shows that conversational interfaces should have the ability to include past conversation history in the evaluation of questions in order to encourage user engagement. We present a typology of questions and provide in-depth insights to inform the development of chatbots for human data interaction.2023BJBernhard Jordan et al.Conversational ChatbotsInteractive Data VisualizationCUI
What Players Want: Information Needs of Players on Post-GameVisualizationsWith the rise of competitive online gaming and esports, players ability to review, reflect upon, and improve their in-game performance has become important. Post-play visualizations are key for such improvements. Despite the increased interest in visualizations of gameplay, research specifically informing the design of player-centric visualizations is currently limited. As with all visualizations, their design should, however, be guided by a thorough understanding of the goals to be achieved and which information is important and why. This paper reports on a mixed-methods study exploring the information demands posed by players on post-play visualizations and the goals they pursue with such visualizations. We focused on three genres that enjoy great popularity within the competitive gaming scene. Our results provide useful guideposts on which data to focus on by offering an overview of the relevance of different in-game metrics across genres. Lastly, we outline high-level implications for the design of post-play visualizations.2021GWGünter Wallner et al.Eindhoven University of Technology, Johannes Kepler University LinzInteractive Data VisualizationGame UX & Player BehaviorCHI
CorpSum: Towards an Enabling Tool-Design for Language Researchers to Explore, Analyze and Visualize CorporaLinguists use annotated text collections to validate, refute and refine a hypothesis about the written language. This research requires the creation and analysis of complex queries which are often above the technical expertise of the domain users. In this paper, we present a tool-design which enables language researchers to easily query annotated text corpora and conduct a comparative multi-faceted analysis on a single screen. The results of the iterative design process, including requirement analysis, multiple prototyping and user evaluation sessions, and expert reviews, are documented in detail. Our tool, called CorpSum, shows a 43.12 point increase in the mean SUS score in a randomized within-subjects test and an improvement of 3.18 times in mean task completion duration compared to a conventional solution. Two detailed case studies with linguists demonstrate a significant improvement for solving the real-world problems of the domain users.2021AÇAsil Çetin et al.Austrian Academy of SciencesInteractive Data VisualizationData StorytellingComputational Methods in HCICHI
MYND: Unsupervised Evaluation of Novel BCI Control Strategies on Consumer HardwareNeurophysiological laboratory studies are often constraint to immediate geographical surroundings and access to equipment may be temporally restricted. Limitations of ecological validity, scalability, and generalizability of findings pose a significant challenge for the development of brain-computer interfaces (BCIs), which ultimately need to function in any context, on consumer-grade hardware. We introduce MYND: An open-source framework that couples consumer-grade recording hardware with an easy-to-use application for the unsupervised evaluation of BCI control strategies. Subjects are guided through experiment selection, hardware fitting, recording, and data upload in order to self-administer multi-day studies that include neurophysiological recordings and questionnaires at home. As a use case, thirty subjects evaluated two BCI control strategies (“Positive memories” and “Music imagery”) by using a four-channel electroencephalogram (EEG) with MYND. Neural activity in both control strategies could be decoded with an average offline accuracy of 68.5% and 64.0% across all days.2020MHMatthias R. Hohmann et al.Brain-Computer Interface (BCI) & NeurofeedbackComputational Methods in HCIUIST
See, Feel, Move: Player Behaviour Analysis through Combined Visualization of Gaze, Emotions, and MovementPlaytesting of games often relies on a mixed-methods approach to obtain more holistic insights about and, in turn, improve the player experience. However, triangulating the different data sources and visualizing them in an integrated manner such that they contextualize each other still proves challenging. Despite its potential value for gauging player behaviour, this area of research continues to be underexplored. In this paper, we propose a visualization approach that combines commonly tracked movement data with - from a visualization perspective rarely considered - gaze behaviour and emotional responses. We evaluated our approach through a qualitative expert study with five professional game developers. Our results show that both the individual visualization of gaze, emotions, and movement but especially their combination are valuable to understand and form hypotheses about player behaviour. At the same time, our results stress that careful attention needs to be paid to ensure that the visualization remains legible and does not obfuscate information.2020DKDaniel Kepplinger et al.University of Applied Sciences Upper AustriaHuman Pose & Activity RecognitionVisualization Perception & CognitionGame UX & Player BehaviorCHI