Abstract As data visualizations become increasingly central to communication, analysis, and decision-making across a variety of fields, the need to ensure their accessibility becomes critical. Visual representations, such as charts, graphs, and infographics, are effective tools for conveying complex information; however, they often present significant barriers for individuals with various types of impairments. This paper explores the potential of Machine Learning (ML) to enhance the accessibility of data visualizations. Specifically, we present a Systematic Literature Review (SLR) that investigates how ML techniques have been applied to make visual data more inclusive. The review considers both visualization-related aspects (such as visualization types and source, target user, and evaluation) and ML-related factors (including data formats, preprocessing, and model types and evaluation). Our findings reveal that only a limited number of studies directly address the use of ML for improving visualization accessibility, and there is a lack of standardized solutions or frameworks in this area. Our contribution focused on the identification of a conceptual framework based on nine key open challenges that highlight the lack of consideration for infographics, particular types of charts, printed chart, different kind of impairments, involvement of users, accurate interpretation of complex visual data, real-time support, standard benchmarking, the potential bias and, hence, the need for continued research and development at the intersection of data visualization and machine learning, with a strong focus on accessibility and inclusivity.

Figure 1: Kids by the Mar Menor sketched their hopes for the lagoon and its sea life.One jellyfish journeyed from paper to interactive visualization, bringing their creative vision to life and calling to protect the lagoon's ecosystem.

The COVID-19 pandemic has highlighted the urgent need for a stronger and more immediate connection between doctors and patients, with some scenarios requiring real-time communication. In this context, the design of intuitive and accessible healthcare systems becomes crucial in bridging the gap between medical professionals and patients. These systems must not only facilitate seamless interaction but also empower patients with clear and comprehensible data visualizations of their vital signs. By enabling individuals to better understand their health status, these solutions support more informed decision-making, ultimately fostering a more proactive and engaged approach to personal well-being. This study aims to analyze a case study in this field to assess whether simple and intuitive systems lead to higher usability and an improved user experience (UX), while also ensuring that patients maintain a high level of awareness of their medical data.

Educating children and teenagers on environmental issues is crucial, as they not only internalize the importance of ecological preservation but can also share this knowledge at home, spreading awareness within their families and communities about these delicate matters. In this work, we introduce an innovative approach to raising awareness of environmental challenges faced by the Mar Menor lagoon by blending children’s art with conversational artificial intelligence. We built an interactive narrative visualization where users can learn about the ecosystem while exploring related drawings created by children and engaging in voice conversations with a chatbot powered by generative AI. To validate our approach, we conducted a preliminary evaluation of the prototype during the European Researchers’ Night 2024 where we gathered positive feedback through user tests and questionnaires, proving the potential of combining children’s creativity and AI technology to foster environmental stewardship and raise awareness about fragile ecosystems.

Recent research has identified the detrimental consequences stemming from the pervasive and excessive use of digital devices, prompting the emergence of the concept of digital wellbeing. This workshop serves as a platform for both researchers and practitioners to convene and delve into discussions surrounding the imperative task of educating young generations on digital wellbeing. Participants will engage in a collaborative exploration of innovative strategies and tools aimed at fostering a more mindful and conscious engagement with digital platforms. Through shared insights and collective expertise, the workshop aims at paving the way for a healthier and more balanced relationship with technology among today’s teenagers.

Multimodal interfaces go beyond the traditional interaction through keyboard and mouse by incorporating multiple modes of interaction, such as touch, voice, gesture, and even gaze, to create more intuitive and immersive user experiences. This paper investigates how TinyML can be employed for multimodal interfaces in the context of games. An endless game in which the character has to avoid obstacles and fight monsters to advance has been developed. An Arduino Nano 33 BLE Sense is then used as the input device for the game by recognizing the hand gestures of the players.

As the world becomes increasingly interconnected, digital technologies impact the way humans experience places and spaces in (smart) cities. To some extent, these smart technologies are intertwined with the urban living enabling the augmentation of the city’s space and creating new opportunities for playful urban engagement. Moreover, touristic cities are becoming the arena of novel hospitality services, emerging from the widespread use of digital technologies and internet-based platforms. At the same time, visitors look for increasingly “authentic” travel experiences that provide meaningful interactions with locals. New business models, such as those emerging from the sharing economy, flourished in response to these fresh needs and opportunities. However, establishing points of dialogue that bring benefits to both residents and tourists is a complex task that still needs inquiry. Here we extend on previous efforts by proposing a playful immersive experience that focuses on creating an esthetically engaging environment for direct information exchange between locals and visitors. We investigate how technology can mediate and augment such information sharing, engaging tourists in a playful and immersive experience. Results of an experiment with 15 users are analyzed and presented to provide new insights to the HCI community.

Sharing economy and contemporary tourism are two emerging concepts that urge to be investigated together with new ubiquitous and immersive technologies, in the tourism and hospitality sector. In this rich scenario, we designed and implemented ShareCities, a platform to foster remote direct information exchange and meaningful interactions among tourists and locals. Exploiting ShareCities we here present an extended analysis on the opportunity to use people-to-people recommendation criteria based on proximity. We hence defined three criteria which drove our analysis: i) profile similarity, ii) geographical proximity, and iii) random exploration. Through an online questionnaire, we collect answers from 126 young-adult students, obtaining a general positive interest in the three criteria but also concerns in terms of privacy, trust, and feeling of disorientation.

Gamification has been widely and often successfully exploited in several educational environments at different levels. In this study, we detail the use of Gamification mechanisms within a university course about web technologies, with the aim of increasing the students’ involvement in the study of the course subject. We designed different Gamification strategies based on group or individual activities. The study has been carried out over five academic years. Based on our findings, we can conclude that, under the defined conditions, the employed Gamification mechanisms had a positive impact on the students learning experience.

As the world becomes increasingly interconnected, emerging and innovative sensing technologies are shaping the future of agriculture, with a special focus on sustainability-related issues. In this context, we envision the possibility to exploit Social Internet of Things for sensing of environmental conditions (solar radiation, humidity, air temperature, and soil moisture) and communications, deep learning for plant disease detection, and crowdsourcing for images collection and classification, engaging farmers and community garden owners and experts. Through, data fusion and deep learning, the designed system can exploit the collected data and predict when a plant would (or not) get a disease, with a specific degree of precision, with the final purpose to render agriculture more sustainable. We here present the architecture, the deep learning model, and the responsive Web app. Finally, some experimental evaluations and usability/engagement tests are reported and discussed, together with final remarks, limitations, and future work.

Humans generally spend more than 90% of their time in indoor environments. Such value can reach 100% due to the restrictions and limitations we are experiencing because of the current COVID-19 pandemic. Indeed, monitoring the indoor air quality (IAQ) becomes strategic to prevent and limit risks and adverse effects on building occupants’ health, comfort, and well-being. To reduce one of the variables impacting the IAQ, i.e. CO2, indoor plants can be exploited. In this paper, we present the low-cost prototype of a system we designed with the intent to foster user’s awareness about IAQ exploiting an IoT-enabled home gardening system, able to sense information about the ambient conditions and plant health.

In a world that is getting increasingly digital and interconnected, and where more and more physical objects are integrated into the information network (Internet of Things, IoT), Data Visualization can facilitate the understanding of huge volumes of data. In this paper, we present the design and implementation of a testbed where IoT and Data Visualization have been exploited to increase the sustainability and safety of the Cesena (Smart) Campus. In particular, we detail the overall system architecture and the interactive dashboard that facilitates the management of the campus premises and the timetabling. Exploiting our system, we show how we can improve the campus sustainability (in terms of energy saving) and safety (considering the COVID-19 restrictions and regulations).

This paper presents a mobile application designed in collaboration with an association devoted to facilitating the enjoyment of tourist services by visually impaired people (including low vision and blind users). In the design process, we performed a questionnaire to collect requirements and feedback from users. The outcome (100 answers) drove the design of mockups, and then, of the final application. Moreover, to make the application more appealing, we implemented gamification mechanism (to motivate the user in contributing to the application) and recommendation strategies (to assist users in choosing the tourist services). Some preliminary tests showed that the application results compliance with the most used screen readers and that users appreciated the provided functions.

In the context of wayfinding systems, this paper describes the design and development of an augmented smartphone-based navigation system where wearable output devices have been put to good use to improve the mobility experience of people with disabilities. In particular, we developed a system as a proof of concept, exploiting smart glasses and smart bracelets to covey information about the navigated path in an augmented way. We conducted a preliminary field study with a few users with mobility impairments to evaluate the feasibility of our system. Results are really encouraging considering the approach of using different ways to covey notifications related to the direction to follow. At the same time, the outcome reveals that the smart glasses we used in the prototype influenced negatively the perception of the experience.