The configuration of public open spaces plays a crucial role in shaping how different people use them. Nevertheless, our understanding of how the physical features of public open spaces influence the activities conducted within them, and the extent to which this impact differs across various individuals and population groups, is currently limited. In this study, we explore how the physical characteristics of public open spaces influence the likelihood of use among individuals, spanning different age and gender groups. By employing crowdsourcing, street-level imagery, statistical comparisons, and reflexive thematic analysis we uncover significant variations in the suitability of public open spaces for distinct activities, such as socializing or exercising. Greenspaces emerge as the preferred choice for almost all activities, whereas streets are consistently rated as the least suitable. Additionally, we identified various characteristics that influence the activities people are likely to engage in. These include the size of the space, the presence of seating, natural elements such as vegetation or water bodies, and the proximity to transport infrastructure. Surprisingly, we do not observe statistically significant differences in preferences among most age and gender groups. Overall, our study underscores the need for providing a diverse range of public open spaces tailored to accommodate different individuals, population groups, and activities.@en

Accessibility is a widely used concept across various disciplines to evaluate the degree to which individuals can reach desired destinations. Conventionally, accessibility is determined by the attractiveness of a destination and the associated travel cost to reach it. However, existing place-based accessibility measures do not differentiate between destinations accessible to individuals from a single demographic group and those accessible to individuals from diverse demographic groups. We propose a measure to assess the potential of distinct destinations to bring different individuals and demographic groups together, defining this property as co-accessibility. We demonstrate how measuring co-accessibility can enhance existing accessibility measures, describe its components, and provide a mathematical formulation for quantifying it. To illustrate the practical application of our measure, we conduct a case study in Amsterdam, the Netherlands, comparing the accessibility and co- accessibility of various destinations. This sample case study highlights the complexities and challenges inherent in measuring co-accessibility. Building on existing literature and our analysis results, we discuss the potential implications of co-accessibility, identify key challenges in its assessment, and recommend directions for future research.@en

Pre-trained deep learning (DL) models are increasingly accessible in public repositories, i.e., model zoos. Given a new prediction task, finding the best model to fine-tune can be computationally intensive and costly, especially when the number of pre-trained models is large. Selecting the right pre-trained models is crucial, yet complicated by the diversity of models from various model families (like ResNet, Vit, Swin) and the hidden relationships between models and datasets. Existing methods, which utilize basic information from models and datasets to compute scores indicating model performance on target datasets, overlook the intrinsic relationships, limiting their effectiveness in model selection. In this study, we introduce TransferGraph, a novel framework that reformulates model selection as a graph learning problem. TransferGraph constructs a graph using extensive metadata extracted from models and datasets, while capturing their inherent relationships. Through comprehensive experiments across 16 real datasets, both images and texts, we demonstrate TransferGraph's effectiveness in capturing essential model-dataset relationships, yielding up to a 32% improvement in correlation between predicted performance and the actual fine-tuning results compared to the state-of-the-art methods.

@en

In the shift towards human-centered manufacturing, our two-year longitudinal study investigates the real-world impact of deploying Cognitive Assistants (CAs) in factories. The CAs were designed to facilitate knowledge sharing among factory operators. Our investigation focused on smartphone-based voice assistants and LLM-powered chatbots, examining their usability and utility in a real-world factory setting. Based on the qualitative feedback we collected during the deployments of CAs at the factories, we conducted a thematic analysis to investigate the perceptions, challenges, and overall impact on workflow and knowledge sharing.

Our results indicate that while CAs have the potential to significantly improve efficiency through knowledge sharing and quicker resolution of production issues, they also introduce concerns around workplace surveillance, the types of knowledge that can be shared, and shortcomings compared to human-to-human knowledge sharing. Additionally, our findings stress the importance of addressing privacy, knowledge contribution burdens, and tensions between factory operators and their managers.@en

The study of urban greenspaces typically relies on three types of data: people’s subjective perceptions collected via questionnaires, vegetation indices derived from satellite imagery, such as the Normalized Difference Vegetation Index (NDVI), and Land Use or Land Cover maps, such as OpenStreetMap (OSM). Data on people’s perceptions are essential when researching human activities, yet they scale poorly. NDVI and OSM data, on the other hand, are freely available worldwide, thus valuable for assessing cities at scale or prioritizing locations for interventions. However, it is unclear how effectively NDVI and OSM data capture people’s visual perceptions of urban greenspaces. In this work, we collect people’s visual perceptions of public spaces in three major European cities through crowdsourcing, quantitatively compare them to NDVI and OSM data, and qualitatively investigate disparities. We found that NDVI moderately correlates with perceived greenness and that not only OSM greenspaces but also pocket parks and play spaces are often considered green. Furthermore, we found that people’s perceptions correspond best to OSM data in small radius distances and NDVI data in larger radius distances and that combining NDVI and OSM data can improve identification of places in OSM that are commonly considered green. Our qualitative analysis revealed that configuration and variety of vegetation, and presence of other natural or built-up features, influence people’s perceptions of greenspace. With our findings we aim to help researchers and practitioners make more informed decisions when collecting greenspace data for their specific context, ultimately contributing to green urban environments that reflect people’s perspectives.@en

Machine learning (ML) training data is often scattered across disparate collections of datasets, called <italic>data silos</italic>. This fragmentation poses a major challenge for data-intensive ML applications: integrating and transforming data residing in different sources demand a lot of manual work and computational resources. With data privacy constraints, data often cannot leave the premises of data silos; hence model training should proceed in a decentralized manner. In this work, we present a vision of bridging traditional data integration (DI) techniques with the requirements of modern machine learning systems. We explore the possibilities of utilizing metadata obtained from data integration processes for improving the effectiveness, efficiency, and privacy of ML models. Towards this direction, we analyze ML training and inference over data silos. Bringing data integration and machine learning together, we highlight new research opportunities from the aspects of systems, representations, factorized learning, and federated learning.

@en

Sustained adoption of automation is a problem for organizations, despite the promised benefits of automation and the propensity for organizations to expect it to transform their workplaces. To address this problem, previous work in HCI has mostly considered the perspectives and experiences of users interacting with automation technologies and has not considered the broader organizational context consisting of different stakeholders with varying needs and expectations around automation. Taking Amsterdam Airport Schiphol as a case study, we examine the challenges faced by practitioners responsible for integrating automation projects in its airside ecosystem, in an interview study conducted with 8 participants. Our findings reveal three challenges to the adoption of automation within the organization - the lack of consensus among different stakeholders, the need to adapt the technology to the specific context, and the undefined procedures required to maintain automation after implementation, that should be further addressed by the HCI community.@en

The exponentially growing digitisation of services that drive the transition from industry 4.0 to industry 5.0 has resulted in a rising materials demand for ICT hardware manufacturing. The environmental pressure, CO2 emissions (including
embodied energy) and delivery risks of our digital infrastructures are increasing. A solution is to transition from a linear to a circular economy (CE), through which materials that were previously disposed of as waste are re-entered back into product lifecycles through processes such as reuse, recycling, remanufacturing, repurposing. However, the adoption of the CE in the ICT sector is currently limited due to the lack of tools that support knowledge exchange between sustainability, ICT and technology experts in a standardised manner and the limited data availability, accessibility and interoperability needed to build such tools. Further, the already existing knowledge of the domain is fragmented into silos and the lack of a common terminology restricts its interoperability and usability. These also lead to transparency and responsibility issues along the supply chain. For many years now, the Semantic Web has been known to provide solutions to such issues in the form of ontologies and knowledge graphs. Several semantic models for the ICT, materials and CE domains have been build and successfully applied to solve complex problems such as predictive maintenance. However, there is a lack of a systematic analysis of the existing semantic models in these domains. Motivated by this, we present a literature survey of existing ontologies for ICT, materials and the CE, their possible applications, limitations and current CE standardisation efforts that can help guide its further implementation@en

Remote Patient Management systems (RPM) are crucial for addressing healthcare workforce shortages. These systems are often designed with a specified focus on clinical functionalities, without proper consideration for human-centric concerns. A care perspective is essential not only to acknowledge patients as people, but also to foster better quality of care and, ultimately, adoption. This highlights the gap of how RPM can embed caring. This work offers a systematic literature review aimed at developing "Caring RPM", a normative framework that integrates the philosophy of caring from nursing theory into RPMs. This framework underwrites the practical, moral, and relational aspects of patient care, including actionable recommendations to recalibrate RPM systems for more effective human-centric design. The framework can inspire new ways of embedding the caring dimension into HCI design practices.

@en

Digitally-supported participatory methods are often used in policy-making to develop inclusive policies by collecting and integrating citizen's opinions. However, these methods fail to capture the complexity and nuances in citizen's needs, i.e., citizens are generally unaware of other's needs, perspectives, and experiences. Consequently, policies developed with this underlying gap tend to overlook the alignment of multistakeholder perspectives, and design policies based on the optimization of high-level demographic features. In our contribution, we propose a method to enable citizens understand other's perspectives and calibrate their positions. First, we collected requirements and design principles to develop our approach by involving stakeholders and experts in policymaking in a series of workshops. Then, we conducted a crowdsourcing study with 420 participants to compare the effect of different text and images, on people's initial and final motivations and their willingness to change opinions. We observed that both influence participant's opinion change, however, the effect is more pronounced for textual modality. Finally, we discuss overarching implications of designing with empathy to mediate alignment of citizen's perspectives.@en

Domestic heating systems need to change to meet climate targets. We draw on practice theoretical concepts to understand what is needed to integrate heat pumps in Dutch households. From a design orientation, we view households as creative actors integrating technologies into daily life. We report on an ethnographic study of the disruptions and resulting reconfigurations that occur when heat pumps are introduced in Dutch households. Our findings reveal a variety of practice reconfigurations around heat pumps. We also find that these reconfigurations are related to and may influence other practices, including professional practices. We discuss our findings in relation to policy, technology development, and design, and conclude that the required reconfigurations in Dutch household practices could be supported, and that innovative practice reconfigurations emerging from internal household dynamics could contribute to sustainability transitions.

@en

Web search has evolved into a platform people rely on for opinion formation on debated topics. Yet, pursuing this search intent can carry serious consequences for individuals and society and involves a high risk of biases. We argue that web search can and should empower users to form opinions responsibly and that the information retrieval community is uniquely positioned to lead interdisciplinary efforts to this end. Building on digital humanism---a perspective focused on shaping technology to align with human values and needs---and through an extensive interdisciplinary literature review, we identify challenges and research opportunities that focus on the searcher, search engine, and their complex interplay. We outline a research agenda that provides a foundation for research efforts toward addressing these challenges.@en

Access to greenspace impacts children’s physical, social, and mental health. Numerous factors affect children’s access to urban greenspaces, often distinct from those affecting the general population, including parental restrictions, limited routine activity-space, and particular preferences. Most accessibility measures, however, employ the same principles for children and the general population, and a comprehensive exploration of factors and corresponding measures remains lacking. We conduct a scoping review and workshops with researchers and practitioners to identify factors affecting children’s access to greenspace, synthesize them into a conceptual model, and assess how existing accessibility measures address these factors. We focus on children aged 6–11 years old. Our analysis indicates children’s access involves a trade-off between reachability, determined by the route connecting the child’s starting setting to greenspace, and attractiveness, determined by how the greenspaces adhere to the child’s, and their companions’, preferences and motivations for visiting. Safety perceptions are important throughout. Existing accessibility measures predominantly emphasize reachability, neglecting personal characteristics and motivations. Based on our findings, we propose future directions for developing child-centered accessibility metrics. Our overview of metrics can facilitate decision-making in the selection of suitable measures, while our conceptual model can foster shared understanding of factors affecting children’s access to urban greenspace.@en

Learning to operate a complex system, such as an agile production line, can be a daunting task. The high variability in products and frequent reconfigurations make it difficult to keep documentation up-to-date and share new knowledge amongst factory workers. We introduce CLAICA, a Continuously Learning AI Cognitive Assistant that supports workers in the aforementioned scenario. CLAICA learns from (experienced) workers, formalizes new knowledge, stores it in a knowledge base, along with contextual information, and shares it when relevant. We conducted a user study with 83 participants who performed eight knowledge exchange tasks with CLAICA, completed a survey, and provided qualitative feedback. Our results provide a deeper understanding of how prior training, context expertise, and interaction modality affect the user experience of cognitive assistants. We draw on our results to elicit design and evaluation guidelines for cognitive assistants that support knowledge exchange in fast-paced and demanding environments, such as an agile production line.

@en

City streets that feel safe and attractive motivate active travel behaviour and promote people’s well-being. However, determining what makes a street safe and attractive is a challenging task because subjective qualities of the streetscape are difficult to quantify. Existing evidence typically focuses on how different street features influence perceived safety or attractiveness, but little is known about what influences both. To fill this knowledge gap, we developed a crowdsourcing tool and conducted a study with 403 participants, who were asked to virtually navigate city streets in Frankfurt, Germany, through a sequence of street-level images, rate locations based on perceived safety and attractiveness, and explain their ratings. Our results contribute new insights regarding the key similarities and differences between the factors influencing perceived safety and attractiveness. We show that the presence of human activity is strongly related to perceived safety, whereas attractiveness is influenced primarily by aesthetic qualities, as well as the number and type of amenities along a street. Moreover, we demonstrate that the presence of construction sites and underpasses has a disproportionately negative impact on perceived safety and attractiveness, outweighing the influence of any other features. We use the results to make evidence-informed recommendations for designing safer and more attractive streets that encourage active travel modes and promote well-being.@en

Machine learning (ML) researchers and practitioners are building repositories of pre-trained models, called model zoos. These model zoos contain metadata that detail various properties of the ML models and datasets, which are useful for reporting, auditing, reproducibility, and interpretability. Unfortunately, the existing metadata representations come with limited expressivity and lack of standardization. Meanwhile, an interoperable method to store and query model zoo metadata is missing. These two gaps hinder model search, reuse, comparison, and composition. In this demo paper, we advocate for standardized ML model metadata representation, proposing Macaroni, a metadata search engine with toolkits that support practitioners to obtain and enrich that metadata.@en

Automated and connected technologies are increasingly present in everyday life. The concept of co-performance offers a new perspective on artificial agency by understanding artifacts as capable of performing everyday practices next to people. In this pictorial we adopt a lens informed by co-performance, and propose the visual vocabulary of the screenplay as a novel way to represent and annotate co-performances. We highlight conflicts and how they are they are resolved through the enactment of new interfaces in-use. We visually represent and annotate scenes found in data from a study of households living with smart technologies. Using this visual vocabulary reveals the role of time, embodiment, character development and more, in the enactment of interfaces.@en

By 2027 more than 530 M homes will likely adopt at least one type of automated system. This means that a growing number of residents will be living with automated technology in the home, everyday. But living with smart homes is full of conflicts between what residents find appropriate and what technology does instead. Previous research, centering end-user needs, has often focused on smooth living experiences through graphical user interfaces and improved predictions. In this research, we take the more-than-human lens of co-performance to put crises in everyday practices in view, and to conceptualize a new notion of interface. Based on ethnographic data from 11 households, our findings illustrate how crises reveal conflicting ideas of appropriateness, how residents reconfigure their co-performances with technology in response to everyday crises, and how new interfaces are enacted as a result. We conclude by illuminating how researchers and designers should not look at the conflicts and crises emerging in the more-than-human home as something of which to get rid. Instead, they are opportunities for residents and buildings to respond to one another in the context of everyday life and to enact interfaces that were not pre-designed into the building.

@en

Recent evidence underscores the importance of greenspace exposure in promoting physical activity, and in having a positive impact on mental health and cognitive development. Accessibility has been identified to be the primary motivating factor when it comes to encouraging greenspace use and, correspondingly, exposure. Existing quantitative approaches to measuring greenspace accessibility predominantly focus on the areas surrounding home locations, often disregarding access from other settings such as schools or workplaces, exposures while on the move, and mobility differences among different population age groups. This article introduces a novel method to measure greenspace accessibility that considers access from different activity settings (i.e., homes, schools, and the commutes between them) for children and adolescents, while accounting for the dependency of human access on the road network. We use Amsterdam, Rotterdam, and The Hague in the Netherlands as case studies to illustrate the utility of our method. Compared to conventional measures of greenspace accessibility, we show that accounting for school and commuting settings, in addition to residences, captures previously untapped accessibility aspects for both children and adolescents. Our approach can be replicated in other cities worldwide, with the aspiration to provide planners and public health policy-makers with a methodological tool that can help in evaluating access and use of greenspaces when designing health-promoting interventions.

@en

Mental disorders among children and adolescents pose a significant global challenge. The exposome framework covering the totality of internal, social and physical exposures over a lifetime provides opportunities to better understand the causes of and processes related to mental health, and cognitive functioning. The paper presents a conceptual framework on exposome, mental health, and cognitive development in children and adolescents, with potential mediating pathways, providing a possibility for interventions along the life course. The paper underscores the significance of adopting a child perspective to the exposome, acknowledging children's specific vulnerability, including differential exposures, susceptibility of effects and capacity to respond; their susceptibility during development and growth, highlighting neurodevelopmental processes from conception to young adulthood that are highly sensitive to external exposures. Further, critical periods when exposures may have significant effects on a child's development and future health are addressed. The paper stresses that children's behaviour, physiology, activity pattern and place for activities make them differently vulnerable to environmental pollutants, and calls for child-specific assessment methods, currently lacking within today's health frameworks. The importance of understanding the interplay between structure and agency is emphasized, where agency is guided by social structures and practices and vice-versa. An intersectional approach that acknowledges the interplay of social and physical exposures as well as a global and rural perspective on exposome is further pointed out. To advance the exposome field, interdisciplinary efforts that involve multiple scientific disciplines are crucial. By adopting a child perspective and incorporating an exposome approach, we can gain a comprehensive understanding of how exposures impact children's mental health and cognitive development leading to better outcomes.@en