Key lessons from the DECODE pilots and tips on how other cities and governments can apply the technologies and methods.
Reclaiming the Smart City: Personal Data, Trust and the New Commons
Why and how city governments are taking a more responsible approach to the collection and use of personal data.
A City Is Not a Computer: Other Urban Intelligences
<strong>A bold reassessment of "smart cities" that reveals what is lost when we conceive of our urban spaces as computers</strong> Computational models of urbanism—smart cities that use data-driven planning and algorithmic administration—promise to deliver new urban efficiencies and conveniences. Yet these models limit our understanding of what we can know about a city. <i>A City Is Not a Computer</i> reveals how cities encompass myriad forms of local and indigenous intelligences and knowledge institutions, arguing that these resources are a vital supplement and corrective to increasingly prevalent algorithmic models. Shannon Mattern begins by examining the ethical and ontological implications of urban technologies and computational models, discussing how they shape and in many cases profoundly limit our engagement with cities. She looks at the methods and underlying assumptions of data-driven urbanism, and demonstrates how the "city-as-computer" metaphor, which undergirds much of today's urban policy and design, reduces place-based knowledge to information processing. Mattern then imagines how we might sustain institutions and infrastructures that constitute more diverse, open, inclusive urban forms. She shows how the public library functions as a steward of urban intelligence, and describes the scales of upkeep needed to sustain a city's many moving parts, from spinning hard drives to bridge repairs. Incorporating insights from urban studies, data science, and media and information studies, <i>A City Is Not a Computer</i> offers a visionary new approach to urban planning and design.
A Polycentric Governance Lens on Data Infrastructures
Funding policies for data infrastructure promote open data sharing to drive positive social impact. However, concerns regarding the long-term management of data within and across distributed infrastructures can hinder data sharing. We draw upon the concept of polycentric governance to demonstrate how collaborative practices of data curation, in preparing and maintaining data for (future) sharing, provide a solid foundation for understanding data governance within data infrastructures. Based on a qualitative case study of a distributed ecological network, we investigate the conditions under which data are managed as a shared resource by local actors to ensure the long-term (re)usability of data. We contribute to CSCW by conceptualising data curation as a complex form of governance practice with multiple centres of decision-making, each of which operates with some degree of autonomy in data infrastructures. A polycentric governance lens on data infrastructures advances the CSCW conception of data curation as a collective governance practice that can cultivate a data democracy culture within and across organisations, empower individuals to be accountable for their data, and foster a mindset shift toward decentralised data governance.
Better Deal for Data - Practical Data Governance for the Social Sector
Better Deal for Data - practical data governance for the social sector.
Computational Public Space
Governing by dismantling: tech oligarchy and the stifling of public data infrastructure
Published in Science as Culture (Ahead of Print, 2026)
A City in Common: A Framework to Orchestrate Large-scale Citizen Engagement around Urban Issues
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Democratizing Data
Democratizing Data builds a community-driven data ecosystem by identifying how datasets are used and reducing barriers to accessing high-quality public data. The initiative enhances the discoverability, usability, and relevance of data for researchers, policymakers, and stakeholder communities. A suite of tools and strategic partnerships supports this work by connecting users to the data, insights, and networks needed to inform decisions and generate impact.
The Limits of Data
Policymakers want to make decisions based on clear data, but important factors are lost when we rely solely on data. A philosopher writes:
City AI: a strategic framework for urban artificial intelligence application and development
Given the potentially large economic and social impact of AI technological advancement like LLMs, further in-depth thinking is demanded about the ways in which AI exists in cities. In addition to discussions on ethical regulation, there are relatively few cross-cutting studies on how to realize the synergistic development of AI innovation and city, especially taking AI as a complete industry and governance object, under a broader urban and social context. Based on the policy practice of AI development in Shenzhen, this paper proposes a comprehensive framework for the integrated development of AI and the city, which involves the comprehensive consideration of technology systems, application scenarios, educational literacy and governance schemes. Meanwhile, the transformative trend of urban governance triggered by potential general artificial intelligence at a deeper level is further discussed in terms of planning concepts, digital architecture and governance decision-makings. By city AI integration, AI is expected to be better spread into general social activities and, through the driving effect of industrial economy, contribute to the competitiveness and sustainable development of cities.
Fractured reality
The report examines the evolving impact of digital technologies on European democracy. In an era of a global struggle to control the information space, this report offers critical insights into the fracturing of perceived realities, the rise of the ‘fantasy-industrial complex’, and the systemic risks posed by the attention economy. It exposes how platforms algorithmically prioritise engagement over accuracy, reinforcing ideological echo chambers and amplifying mis- and disinformation that erode democratic resilience. The report highlights how structural incentives and foreign control of the most important players in the information space undermine information integrity, collective knowledge and civic discourse. In response, the report presents a number of recommendations from fostering alternative public spaces and crowd-sourced knowledge systems to reforming business models, restoring user agency, and advancing EU digital sovereignty through decentralised infrastructure
A City Is Not a Computer
This seems an obvious truth, but we need to say it loud and clear. Urban intelligence is more than information processing.
Democratic Governance of AI Is the Real Solution
The potential for catastrophic effects from the AI boom demands robust deliberation and real democratic governance. Localized initiatives like data center moratoria won't get us there.
Citizen science in environmental and ecological sciences
Citizen science is an increasingly acknowledged approach applied in many scientific domains, and particularly within the environmental and ecological sciences, in which non-professional participants contribute to data collection to advance scientific research. We present contributory citizen science as a valuable method to scientists and practitioners within the environmental and ecological sciences, focusing on the full life cycle of citizen science practice, from design to implementation, evaluation and data management. We highlight key issues in citizen science and how to address them, such as participant engagement and retention, data quality assurance and bias correction, as well as ethical considerations regarding data sharing. We also provide a range of examples to illustrate the diversity of applications, from biodiversity research and land cover assessment to forest health monitoring and marine pollution. The aspects of reproducibility and data sharing are considered, placing citizen science within an encompassing open science perspective. Finally, we discuss its limitations and challenges and present an outlook for the application of citizen science in multiple science domains.
A Practical Framework for Applying Ostrom’s Principles to Data Commons Governance
How do stakeholders govern themselves? What drives their endeavour? How do they make decisions? How do they make sure conflict does not tear them apart? The answers to these questions will look different for every data commons. Learn more in this week's data governance blog.
JamiiAfrica
Deploying Africa’s Civic OS—a decentralized, secure, and AI-driven digital infrastructure that enables citizens to hold authorities accountable while giving institutions credible, data-backed incentives to respond