While Personal Data Stores (PDSs) aim to support personal data management and enable data portability across applications, user interest remains limited. This study explores the factors influencing user adoption and willingness to share data across four PDS use case scenarios—HR, Media, Finance, and Health—through an iterative research-through-design approach. The study combined a large-scale survey (n = 2,335), prototype development, expert reviews (n = 10), and user testing (n = 17). Findings reveal that although security concerns persist, participants responded positively to the PDS concept, particularly for use cases that reduce administrative burdens. Notably, users who engaged with the prototype reported higher intentions to use and greater willingness to share data than those evaluating written scenarios. These findings highlight the importance of tangible user experiences in shaping perceptions of PDSs. The study concludes with actionable recommendations and an illustrative prototype to inform effective user-centred PDS implementation.

This study explores users’ perceptions of integrating a personal data store to enhance personalized recommendations within a streaming service. Using a research-through-design approach and guided by Human Data Interaction principles (legibility, agency, and negotiability), we developed an enhanced streaming service prototype. This prototype was evaluated by experts (n=5), refined, and then used in two focus groups (n=19) to gauge participants’ reactions to the personal data store integration and their willingness to share different data types for enhanced personalized streaming recommendations. The focus groups revealed mixed reactions to the personal data store, with users weighing curiosity against concerns. However, many of the implemented data transparency and control features helped to mitigate these doubts. By linking our findings to existing literature, we developed a set of design recommendations to help businesses and guide future research in building personal data store applications, further advancing the field of Human Data Interaction.

Abstract The continuing decline of trust in the processing and fair use of personal data has been well documented. A web standard called Solid (SOcial LInked Data) is being developed to halt and mitigate the decline. It puts users in control of their data by enabling them to securely store their data in decentralized personal online data stores (pods). However, little is known about the impact of such pods. Therefore, we measured the effects of the use of a Solid pod on users’ perceived transparency, understanding, control and trust, as well as on usability and behavioural intention. We set up an experiment that compares the perceptions of users about how their data is being processed and stored on a cookies-enabled news recommendation website with a similar Solid-pod-enabled news recommendation website. Although our findings do not provide evidence that this has significantly impacted users’ trust, perceived usability, or intention to use the system, it has been found to significantly impact users’ perceived transparency and control.

One key concept of Tangible User Interaction is interactive surfaces, in which we transform a surface into an active interface between the physical and virtual world. In this paper we describe the design process of a novel interactive surface that can be used for movement therapy for children with Developmental Coordination Disorder (DCD). Children with DCD suffer from impairment in motor development which influences their overall movement quality and affects their daily life. Traditionally, the rehabilitation techniques and tools are often static, non-interactive, monotonous and unappealing to children. The purpose of this study is to design an interactive surface that combines physical motor exercises with digital games. Through an iterative co-creation process with patients and physiotherapists, we developed "Matti" as an interactive gaming mat to increase the motivation of the children during their rehabilitation, by linking the therapy exercises with digital games thus providing more engagement and better results.

Knee arthroplasty is a surgical procedure that replaces severely arthritic or damaged knee joints. After undergoing this commonly performed procedure, there are still some patients who never fully recover. One of the reasons is the lack of patient compliance to the prescribed rehabilitation schedule. This paper describes the development of SEKO, a smart system which has the goal of improving the compliance of patients to the rehabilitation schedule after a knee arthroplasty. This is done by providing a system which connects a smart brace to a patient and his/her physiotherapist. The system exists out of three parts: the smart brace which uses multiple sensors that gather data of the movements and exercises performed by the patient, the mobile application which uses the gathered data to give feedback to the patient, and the web application which uses the data to keep the patient's physiotherapist up to date on the rehabilitation performance and progress of the patient. The result is a proof of concept in the form of a fully functioning prototype, which was preliminary evaluated on the technical aspects and the usage scenario.

In the paper we present our Range-IT prototype, which is a 3D depth camera based electronic travel aid (ETA) to assist visually impaired people in finding out detailed information of surrounding objects. In addition to detecting indoor obstacles and identifying several objects of interest (e.g., walls, open doors and stairs) up to 7 meters, the Range-IT system employs a multimodal audio-vibrotactile user interface to present this spatial information.

The role of the physical embodiment of a social robot is of key importance during the interaction with humans. If we want to study the interactions we need to be able to change the robot's embodiment to the nature of the experiment. Nowadays, researchers build one-off robots from scratch or choose to use a commercially available platform. This is justified by the time and budget constraints and the lack of design tools for social robots. In this work, we introduce an affordable open source platform to accelerate the design and production of novel social robot embodiments, with a focus on face-to-face communication. We describe an experiment where Industrial Design students created physical embodiments for 10 new social robots using our platform, detailing the design methodology followed during the different steps of the process. The paper gives an overview of the platform modules used by each of the robots, the skinning techniques employed, as well as the perceived usability of the platform. In summary, we show that our platform (1) enables non-experts to design new social robot embodiments, (2) allows a wide variety of different robots to be built with the same building blocks, and (3) affords itself to being adapted and extended.

One of the major obstacles in the study of human-robot interaction with social robots is the lack of platforms to allow for tests with large user groups. Often, the price of these robots prohibits using more than a handful of robots. Another factor is that with commercial platforms, the robots do not possess all the necessary features to perform an experiment and due to the closed nature of the platform, extensive modifications are nearly impossible. To address this problem, a new social robotics platform, OPSORO, is presented. The platform uses an innovative modular system design that enables the creation of different embodiments to represent anthropomorphic robots focusing on face-to-face communication. Our goal is to offer a platform for the development of robotic characters, typically within the context of therapeutics or entertainment. OPSORO is a unique system that provides real personalization of social robots.

For some time now, robotics research has shifted its attention from robots that function within their own predefined space to robots that coexist with humans in the human's natural habitats. This evolution has not only driven interest in robot safety and compliance, it has also resulted in the subdomain of Social Robotics, which is concerned with natural interaction between robots and humans. In this studio, we will offer participants the chance to create their own animatronic creature using modular building blocks derived from Ono, our low-cost Do-It-Yourself social robot. In the first part, we will help participants to conceptualize a context and scenario for their social robot. Then, using craft materials (e.g. cardboard, glue, fabrics, foam, etc.) in combination with custom connectors and our animatronic modules, participants will build the physical embodiment of their creature. Finally, they are brought to life by connecting the modules to our electronics platform (Raspberry PI), which is then programmed using an easy to use library.

Skweezees are soft, deformable objects that recognize their shape deformation. Typically, a Skweezee has a fabric 'skin' and is filled with conductive padding. Several fabric electrodes are dispersed over the shape, and a small electronic circuit measures the resistance between each possible pair of electrodes. As the shape is deformed as a result of a squeeze gesture, the resistance patterns between electrode pairs change. A machine learning algorithm allows to differentiate between the different shape deformations. In addition, user-friendly open source software allows defining and recording squeeze gestures. Consequently, Skweezees enable rich gestural squeeze interaction for the DIY community. In this Skweezee Studio, participants are invited to bring their own plush toy (or another soft object) and to transform it into a Skweezee. Moreover, participants will be introduced to the mechanical, electrical and digital properties of Skweezees and participants will be able to explore and discuss the potential of e-textile, and of soft, tangible and haptic interactions in general.

In this paper, we describe the first results of using the robot Probo as a facilitator in Social Story Intervention for children with autism spectrum disorders (ASD). Four preschoolers diagnosed with ASD participated in this research. For each of them, a specific social skill deficit was identified, like sharing toys, saying Thank you, saying Hello, and an individualized Social Story was developed. The stories were told by both the therapist and the robot in different intervention phases. Afterwards an experimental task was created where the child needed to exercise the ability targeted by the story. The results of this study showed that the participant needed a decreased level of prompt to perform the targeted behavior, when the story was told by the robot compared to the intervention with the human storyteller. Therefore, this preliminary study created great expectancies about the potential of Robot Assisted Therapy as an added value for ASD interventions.

The concept of the huggable robot Probo is a result of the desire to improve the living conditions of children in hospital environment. These children need distraction and lots of information. In this paper the concept of a new social robot is presented. This robot can be used in hospitals, as a tele-interface for entertainment, communication and medical assistance.