Stakeholder participation and risk communication in the monitoring activities to improve the quay walls and bridges of Amsterdam. The municipality of Amsterdam presented the program Quay Walls and Bridges in Amsterdam (QWBA), which aims to provide a framework to improve the current conditions of the QWBA. Among their activities are monitoring actions to measure the state of QWBA. The program has an open attitude from decision-makers to adapt existing rules and include social participation as one of the main conditions for a successful program. However, social participation is a key element that requires exploration, particularly on how risk communication of the monitoring activities of the QWBA can affect the perception of risk of different stakeholders and the values attached, as there is inexistent literature on the topic. Therefore, this study aims to understand how to enhance the effectiveness of risk communication practices related to the monitoring activities of Amsterdam's quay walls and bridges. To do so, this research adopts a citizen science approach. It uses an explorative case study method inside the Amsterdam Canal district, a UNESCO World Heritage site. On it, we plan to conduct a qualitative data collection process through a survey applied to local residents and other relevant stakeholders who live and work around the QWBA. The data collected will allow us to have a broader understanding of how current risk communication is perceived regarding the monitoring activities of the QWBA, what values can be considered to improve risk communication and which strategies can enhance risk communication and social participation.

Today’s cities are datafied smart cities. Data - and the more visible manifestations of data in the form of apps, platforms, and urban interfaces - shape how people interact in a range of social domains and with various institutions. The nature of datafied systems, the power relations and the values embedded in various urban systems have a major impact on the inclusiveness of citired. The amplification of infrastructural inequities happens for instance through biased algorithms that unjustly target and harm specific groups and individuals, by smart tech being designed for able-bodied and media literate people while ignoring intersectionality, or via automated tech that supports a depoliticized and frictionless urban management instead of civic participation and just urban governance rooted in frictions, struggles and ongoing dialogue. A key challenge of inclusive smart cities therefore is to make sure that the datafication of urban life does not promote the interests of the few but that it benefits (at least not impedes or harms) peoples’ collective interests to fully participate in (urban) society. In the burgeoning transdisciplinary field of smart city research, increasing attention is being paid to this relationship between data, local governance and inclusion. However, the ways in which inclusion is conceptualized varies across different disciplines, with labels such as equity, social justice, fairness, responsibility, and others in use. In this contribution, we expand on what “inclusion in the datafied city” means from our own disciplinary perspectives in Media Studies, Public Governance and Law, and Urban Studies. This contribution aims 1) to conceptualize inclusion in the datafied smart city by bringing different disciplinary perspectives together; 2) to illustrate hands-on approaches for addressing inclusive datafied smart cities by means of two case studies; 3) to reflect on ways in which transdisciplinary insights contribute to understanding and shaping inclusive smart urbanism. We do so by looking at three framings of inclusion: an institutional perspective that emphasizes technological access; a culturally-sensitive conceptualization of inclusion in intersectional terms; and, more recently, and a multidimensional understanding of inclusion that highlights negotiation and co-creation.

Building upon the insightful work of Cobham (2020), which underscores the significance of what we count, this paper contends that the methods employed in counting are equally critical. As demonstrated by Cobham (2020), policies and decisions are underpinned by evidential data; thus, being excluded from these datasets equates to being overlooked. This paper delves into the analysis of homelessness counts and considerations in Ireland, aiming to illustrate how counting methodologies lead to significant underestimations of the homeless population. Existing literature has predominantly focused on the methodological foundations of homelessness counts (Bush et al., 2016; Kuzmanovski, 2020), revealing not only their failure to provide a comprehensive view of the population (Schneider et al., 2018) but also their inadequacy in acquiring pertinent information to address homelessness effectively (Bairéad and Norris, 2023). Accurately enumerating the homeless remains a complex challenge, driven by various factors that contribute to an often incomplete understanding of the true extent of the problem (Andrews et al., 2020). Utilizing a critical data approach combined with interviews of state and NGO stakeholders, this paper seeks to document and reconsider the political, social and spatial implications of homelessness data flows and what their implications for homelessness and housing policies. In the context of digitization, it highlights on the data politics of administering homeless services, inaccessibility of census services, the lack of coordination among data-collecting organizations, and financial and resource constraints that contribute to fragmented efforts and the underrepresentation of the most marginalized populations. The paper contends that achieving a more comprehensive understanding of homelessness is essential for informing effective policies and interventions to address this humanitarian crisis. By exploring the intricacies of counting methodologies and their impact, it aims to contribute to the ongoing discourse on the importance of robust data collection in shaping policies that truly reflect the realities of homelessness.

Studies of accessibility have advanced our understanding of social and spatial inequalities in the distribution of jobs and other resources in cities worldwide. In response, prominent discourse has shifted to embedding justice in urban planning. In this work, we take a step towards developing specific indicators that quantify spatial justice based on ethical principles of Egalitarianism, Utilitarianism and Rawls’ Egalitarianism. Subsequently, we show how these can be leveraged to steer accessibility planning toward socially just outcomes. We utilise these indicators to evaluate neighbourhood reach opportunities to places of employment through cumulative accessibility metrics. These metrics are based on applying the Dijkstra algorithm to integrated urban network models of transportation, land use and street configuration, created from open-access data in the Netherlands, Mexico and South Africa. We find that shorter commuting times reveal local centres, highlighting the role of local mixed land use. Whereas increased access to global centres and mass transportation play more of a role in longer commuting times. The results highlight how spatial justice to places of employment is both scale and value-reliant, depending on the applied commuting time and ethical principle. The methodological innovation presented here is based on principles of reproducibility and allows the opportunity to bring moral clarity to strategic planning decisions across urban contexts that could serve as a valuable baseline to develop policy.