Data physicalizations have the potential for more natural, intuitive and embodied interactions with data that can engage people with data in a playful way compared to traditional screen and mouse-based interactions. Such interactions are useful to make data understandable and interesting to interact with, especially for special user groups such as children. In this research, we explored how direct manipulation of physical tangibles as an interaction method affects children’s engagement with data, the understanding of data and the overall child-data experience. We compared two new tangible manipulation-based interaction methods: TM-E (Tangible Manipulation Emptying) and TM-F (Tangible Manipulation Filling) designed to create more natural interactions with air quality data and compared them with a slider-based interaction. A user study (N=36) with young adolescents revealed that the newly introduced interaction methods were effective in conveying and recalling air quality information and were positively received by the participants. We also observed that the interaction metaphor impacts the overall user experience. These lessons learned are relevant to the design of physicalizations fostering public awareness, for example, in the context of sustainable development.

Data Physicalizations have the potential to create interactive and more engaging data experiences and to make data more accessible to a broader range of users than those reached by visualizations alone. Tapping into this potential necessitates an understanding of the strengths/weaknesses of the different encoding variables available to designers, and when these variables can be employed to convey data. This work provides a preliminary investigation of two kinesthetic variables (resistance and friction) and their performance during the answering of minima/maxima/cluster questions. We evaluated both encoding modalities with users for their efficiency and effectiveness in a lab-based study. While neither modality was found to be significantly more efficient or accurate, most users preferred reading data through resistance.

Expressive interfaces that communicate human emotional state (e.g., level of arousal) are beneficial to many applications. In this work, we use a research-through-design approach to learn about the challenges and opportunities involved in physicalizing emotional data derived from biosignals in real-time. We present EmoClock, a physicalization that uses a clock as a metaphor to communicate arousal and valence derived from biosignal data and lessons learned from its evaluation.

Data physicalisations, or physical visualisations, represent data physically, using variable properties of physical media. As an emerging area, Data physicalisation research needs conceptual foundations to support thinking about and designing new physical representations of data and evaluating them. Yet, it remains unclear at the moment (i) what encoding variables are at the designer's disposal during the creation of physicalisations, (ii) what evaluation criteria could be useful, and (iii) what methods can be used to evaluate physicalisations. This article addresses these three questions through a narrative review and a systematic review. The narrative review draws on the literature from Information Visualisation, HCI and Cartography to provide a holistic view of encoding variables for data. The systematic review looks closely into the evaluation criteria and methods that can be used to evaluate data physicalisations. Both reviews offer a conceptual framework for researchers and designers interested in designing and evaluating data physicalisations. The framework can be used as a common vocabulary to describe physicalisations and to identify design opportunities. We also proposed a seven-stage model for designing and evaluating physical data representations. The model can be used to guide the design of physicalisations and ideate along the stages identified. The evaluation criteria and methods extracted during the work can inform the assessment of existing and future data physicalisation artefacts.

Hand hygiene became one of the key measures to prevent COVID-19 infection and the spread of the virus. This, however, is challenging with young children (e.g., primary school). Primary school teachers spend a lot of time supervising and helping children to wash their hands and making sure they wash their hands regularly and correctly. Educating children of the need for handwashing and training them to wash hands for 20 s alone does not motivate young children enough to wash their hands without supervision. We developed WashWall, an interactive smart mirror that uses gamification to motivate young children to wash their hands in an engaging way. We deployed WashWall in a primary school and conducted a user study (N = 14) to evaluate its practicality, effectiveness, and user experience. Results show that children engaged in the activity for a significantly longer duration, enjoyed playing WashWall, and learned the game easily and fast.

The global COVID-19 pandemic left few facets of our lives unchanged, including the possibility to play organised sports. Many gyms and sports clubs had to shut down due to social distancing measures, which resulted in reduced physical activity. Co-located group sports that promote social interaction and fun became almost impossible. This lack of physical interaction combined with social isolation and confinement have shown negative impacts on physical and mental well-being of people (for example, lack of motivation, anxiety, low immunity, low academic performance, negative mood and feelings) especially in children and young adults. Recent research therefore recommends exploring more creative approaches that allow physical activities during a pandemic, especially the ones that increase social interaction and engagement and allow users to share the same physical space. Towards this, we developed SixFeet, a novel digital-physical sports platform that allows its participants to play rigorous, collaborative sports – at a six feet distance. SixFeet ensures that the players are 1.5m away from each other at all times without them noticing it or without them having to worry about the social distancing measures. We developed a prototypical implementation of SixFeet and conducted a pilot study to evaluate its technical feasibility and practicality as well as obtain a first insight into user experience with the platform. Results show that participants never came within 1.5 meters of one another, felt connected nevertheless and were physically exerted. This paper presents the design and architecture of SixFeet, results of the preliminary user study, and a discussion on the versatility of SixFeet in accommodating training for different sports in times of a pandemic.

In 2015, all members of the United Nations adopted the 2030 agenda for Sustainable Development (SD). Seventeen (17) goals (SDGs) were formulated towards peace and prosperity for people and the planet. However, concerns have been raised about whether these sustainable goals can be achieved by 2030. Communicating advances regarding SDGs to citizens in an effective and engaging way is thus crucial, as it can reveal which goals need more attention and prompt them to think about what to do at an individual level to support SDG progress. Physicalizations present an opportunity in this context and the overall goal of this work is to empirically articulate the merits of different strategies to convey SDG data physically. We created a data physicalization that uses vibration and temperature as modalities to convey facts related to SDG 7 (Affordable and Clean Energy). Vibration and temperature was chosen to aim for reducing the metaphorical distance between the data and the representation (i.e. to align the quality of data with quality of representation). In a preliminary evaluation, both modalities were perceived as enjoyable by the participants. The two modalities were efficient, however, vibration as a modality was more effective. Temperature, despite presenting a lower metaphorical distance, did not appear to be an effective modality to convey SDG information.

Drivers and pedestrians use various culturally-based nonverbal cues such as head movements, hand gestures, and eye contact when crossing roads. With the absence of a human driver, this communication becomes challenging in autonomous vehicle (AV)- pedestrian interaction. External human-machine interfaces (eHMIs) for AV-pedestrian interaction are being developed based on the research conducted mainly in North America and Europe, where the traffic and pedestrian behavior are very structured and follow the rules. In other cultures (e.g., South Asia), this can be very unstructured (e.g., pedestrians spontaneously crossing the road at non-cross walks is not very uncommon). However, research on investigating cross-cultural differences in AV-Pedestrian interaction is scarce. This research focuses on investigating cross-cultural differences in AV-Pedestrian interaction to gain insights useful for designing better eHMIs. This paper details three cross-cultural studies designed for this purpose, and that will be deployed in two different cultural settings: Sri Lanka and Germany.

While lab-based approaches to evaluation of location-based services (LBSs) allow faster, cost-effective and less complicated evaluation of many aspects, they are limited in evaluating certain aspects, especially the ones related to usability and user experience (UX). Variations in the location information quality can negatively affect location-based UX. Lab-based evaluations are limited in factoring users' actual context, which includes location quality variations into the evaluation process. Therefore, to evaluate actual location-based UX, we need to evaluate LBSs in-the-wild with users under variations in the quality of location information. Currently, there is a lack of standard tools, methods, and frameworks for this purpose. Motivated by this factor, in this paper, we describe the Location Uncertainty Injection Framework (LUIF) for evaluating mobile LBSs in-the-wild with users under location quality variations. We also present the results of a study conducted to gain initial feedback on the potential use cases of the framework.

Degraded GPS signals can negatively affect users of mobile Pedestrian Navigation Applications. Visualization of location uncertainty has emerged as a solution to this problem that has proven beneficial to users. However, there are only a small number of different visualizations developed for this purpose. In addition, their actual impact on facilitating navigation in GPS degraded situations has not been studied well. We designed two new visualizations of location uncertainty and compared them to existing ones in terms of efficiency and user acceptance. A field-based user study(N=18) showed that the two new visualizations significantly reduced the number of wrong turns. Users preferred the landmark-based visualization most and ranked it as the most helpful visualization for judging their true location in the environment when faced with GPS degradations. Despite participants being unfamiliar with the new visualizations, the task completion time, subjective task load and user experience for them were not significantly different from the more familiar state-of-the-art visualization.

Mobile pedestrian navigation apps depend largely on position information, usually provided by a Global Position System (GPS). However, GPS information quality can vary due to several factors. In this paper, we thus investigate how this affects users via a field study (N=21) that exposed pedestrians to no GPS coverage, low accuracy and delayed GPS information during navigation. We found that their navigation performance, their trust in the apps and their experience were all negatively affected. We also identified user strategies to deal with GPS-deteriorated situations and user needs. Based on our findings, we derive several design implications for pedestrian navigation app to better deal with GPS-deteriorated situations. In particular, we propose four adaptation strategies that an app can use to support users in GPS-deteriorated situations. Our findings can benefit designers and developers of pedestrian navigation apps.

The quality of location information is an important factor for location-based services (LBSs). In the literature, the quality of location information has been defined in different ways based on varying sets of aspects. The objectives of this paper are to review existing literature discussing location information quality and to provide a consistent framework for describing and dealing with location information quality. In particular, we review existing literature on different aspects of location information quality and on factors that affect location sensing technologies (and thus location information quality). Based on this review, we also propose a simple model for describing location information quality and a classification of the strategies for dealing with variations in the quality of location information. Designers of location sensing systems can use this model as a standard vocabulary for describing the quality of location information. The classification of strategies can be used by developers of LBSs apps to design alternative strategies for dealing with location information quality on three levels: sensor-level, algorithm-level, and application-level, which are aligned with the Location Stack model.

Location uncertainty is often ignored but a key context parameter for location-based services. The standard way of visualizing location uncertainty on mobile devices is using a concentric circle. However, the impact of different visual variables (shape, size, boundary, middle dot, color) of this standard visualization on users is not well understood. There is a potential for misinterpretation, particularly across cultures. We ran a study that was previously conducted in Germany (N=32) in Sri Lanka (N=20) to investigate how users perceive different visualizations of location uncertainty on mobile devices. In particular, we investigated the impact of the four graphic dimensions, shape, boundary, middle dot and size. We identified consistencies and inconsistencies concerning perceptions of users regarding visualizations of location uncertainty across cultures. We also quantified the impact of different visualizations on the perception of users. Based on the consistencies between different visualizations and between the two cultures, we derived guidelines for visualizing location uncertainty that help developers in aligning location uncertainty with the perceptions of users. We also highlight the need for further research on cultural differences (and similarities) regarding how visualizations of location uncertainty impact the perceptions of users.

Location information is rarely perfectly accurate: usually it is subject to variations, errors and uncertainty, which may affect the quality of location-based services such as Pedestrian Navigation Systems (PNS). Visualizing location uncertainty is one option to address this issue. However, it is unclear how users interpret these visualizations. This paper investigated whether different types and styles of visualizing location uncertainty on mobile devices have an impact on user's perceptions, and which options they prefer. We also proposed a new visualization (cloud shape) to represent location uncertainty and compared it to the two existing shapes (circle and colored street segments-CSS). Results indicate that the design and the style of a visualization influence users' understanding of where they are located. More importantly, results indicated that the cloud could be a better option to visualize the uncertainty if the uncertainty of location information is very high. These findings can be used by the designers to modify/change the shape and style of the visualization to provide users with a more accurate picture of the quality of location information.