Need for Co-creating Urban Data Collaborative

Curated on Posted on by Stefaan Verhulst

Blog by Gaurav Godhwani: “…The Government of India has initiated various urban reforms for our cities like — Atal Mission for Rejuvenation and Urban Transformation 2.0 (AMRUT 2.0), Smart Cities Mission (SCM), Swachh Bharat Mission 2.0 (SBM-Urban 2.0) and development of Urban & Industrial Corridors. To help empower cities with data, the Ministry of Housing & Urban Affairs(MoHUA) has also launched various data initiatives including — DataSmart Cities Strategy, Data Maturity Assessment Framework, Smart Cities Open Data Portal, City Innovation Exchange, India Urban Data Exchange and the India Urban Observatory.

Unfortunately, most of the urban data remains in silos and capacities for our cities to harness urban data to improve decision-making, strengthen citizen participation continues to be limited. As per the last Data Maturity Assessment Framework (DMAF) assessment conducted in November 2020 by MoHUA, among 100 smart cities only 45 cities have drafted/ approved their City Data Policies with just 32 cities having a dedicated data budget in 2020–21 for data-related activities. Moreover, in-terms of fostering data collaborations, only 12 cities formed data alliances to achieve tangible outcomes. We hope smart cities continue this practice by conducting a yearly self-assessment to progress in their journey to harness data for improving their urban planning.

Seeding Urban Data Collaborative to advance City-level Data Engagements

There is a need to bring together a diverse set of stakeholders including governments, civil societies, academia, businesses and startups, volunteer groups and more to share and exchange urban data in a secure, standardised and interoperable manner, deriving more value from re-using data for participatory urban development. Along with improving data sharing among these stakeholders, it is necessary to regularly convene, ideate and conduct capacity building sessions and institutionalise data practices.

Urban Data Collaborative can bring together such diverse stakeholders who could address some of these perennial challenges in the ecosystem while spurring innovation…(More)”

Mapping AI Narratives at the Local Level

Curated on Posted on by Stefaan Verhulst

Article for Urban AI: “In May 2024, Nantes Métropole (France) launched a pioneering initiative titled “Nantes Débat de l’IA” (meaning “Nantes is Debating AI”). This year-long project is designed to curate the organization of events dedicated to artificial intelligence (AI) across the territory. The primary aim of this initiative is to foster dialogue among local stakeholders, enabling them to engage in meaningful discussions, exchange ideas, and develop a shared understanding of AI’s impact on the region.

Over the course of one year, the Nantes metropolitan area will host around sixty events focused on AI, bringing together a wide range of participants, including policymakers, businesses, researchers, and civil society. These events provide a platform for these diverse actors to share their perspectives, debate critical issues, and explore the potential opportunities and challenges AI presents. Through this collaborative process, the goal is to cultivate a common culture around AI, ensuring that all relevant voices are heard as the city navigates to integrate this transformative technology…(More)”.

AI Localism Repository: A Tool for Local AI Governance

Curated on Posted on by Stefaan Verhulst

About: “In a world where AI continues to be ever more entangled with our communities, cities, and decision-making processes, local governments are stepping up to address the challenges of AI governance. Today, we’re excited to announce the launch of the newly updated AI Localism Repository—a curated resource designed to help local governments, researchers, and citizens understand how AI is being governed at the state, city, or community level.

What is AI Localism?

AI Localism refers to the actions taken by local decision-makers to address AI governance in their communities. Unlike national or global policies, AI Localism offers immediate solutions tailored to specific local conditions, creating opportunities for greater effectiveness and accountability in the governance of AI.

What’s the AI Localism Repository?

The AI Localism Repository is a collection of examples of AI governance measures from around the world, focusing on how local governments are navigating the evolving landscape of AI. This resource is more than just a list of laws—it highlights innovative methods of AI governance, from the creation of expert advisory groups to the implementation of AI pilot programs.

Why AI Localism Matters

Local governments often face unique challenges in regulating AI, from ethical considerations to the social impact of AI in areas like law enforcement, housing, and employment. Yet, local initiatives are frequently overlooked by national and global AI policy observatories. The AI Localism Repository fills this gap, offering a platform for local policymakers to share their experiences and learn from one another…(More)”

Reviving the commons: A scoping review of urban and digital commoning

Curated on Posted on by Stefaan Verhulst

Report by James Henderson and Oliver Escobar: “The review aims to contribute to the growing discourse on the commons, highlighting its significance in contemporary societies and its potential as an alternative to traditional forms of socioeconomic and political organisation via the state and/or the market. Practitioners in the field argue that we are witnessing a revival of the commons in the 21st century. This report interrogates the nature of that revival and explores key concepts, examples, trends and debates in theory and practice, while outlining an emerging research agenda…(More)”.

Place identity: a generative AI’s perspective

Curated on Posted on by Stefaan Verhulst

Paper by Kee Moon Jang et al: “Do cities have a collective identity? The latest advancements in generative artificial intelligence (AI) models have enabled the creation of realistic representations learned from vast amounts of data. In this study, we test the potential of generative AI as the source of textual and visual information in capturing the place identity of cities assessed by filtered descriptions and images. We asked questions on the place identity of 64 global cities to two generative AI models, ChatGPT and DALL·E2. Furthermore, given the ethical concerns surrounding the trustworthiness of generative AI, we examined whether the results were consistent with real urban settings. In particular, we measured similarity between text and image outputs with Wikipedia data and images searched from Google, respectively, and compared across cases to identify how unique the generated outputs were for each city. Our results indicate that generative models have the potential to capture the salient characteristics of cities that make them distinguishable. This study is among the first attempts to explore the capabilities of generative AI in simulating the built environment in regard to place-specific meanings. It contributes to urban design and geography literature by fostering research opportunities with generative AI and discussing potential limitations for future studies…(More)”.

Atlas of Intangibles

Curated on Posted on by Stefaan Verhulst

About: “Atlas of Intangibles is a data experience designed to highlight the rich, interconnected web of sensory information that lies beneath our everyday encounters. Showcasing sensory data collected by me around the city of London through score-based data walks, the digital experience allows viewers to choose specific themes and explore related data as views — journeys, connections, and typologies. Each data point is rich in context, encompassing images and audio recordings…(More)”.

Data sovereignty for local governments. Considerations and enablers

Curated on Posted on by Stefaan Verhulst

Report by JRC Data sovereignty for local governments refers to a capacity to control and/or access data, and to foster a digital transformation aligned with societal values and EU Commission political priorities. Data sovereignty clauses are an instrument that local governments may use to compel companies to share data of public interest. Albeit promising, little is known about the peculiarities of this instrument and how it has been implemented so far. This policy brief aims at filling the gap by systematising existing knowledge and providing policy-relevant recommendations for its wider implementation…(More)”.

Modeling Cities and Regions as Complex Systems

Curated on Posted on by Stefaan Verhulst

Book by Roger White, Guy Engelen and Inge Uljee: “Cities and regions grow (or occasionally decline), and continuously transform themselves as they do so. This book describes the theory and practice of modeling the spatial dynamics of urban growth and transformation. As cities are complex, adaptive, self-organizing systems, the most appropriate modeling framework is one based on the theory of self-organizing systems—an approach already used in such fields as physics and ecology. The book presents a series of models, most of them developed using cellular automata (CA), which are inherently spatial and computationally efficient. It also provides discussions of the theoretical, methodological, and philosophical issues that arise from the models. A case study illustrates the use of these models in urban and regional planning. Finally, the book presents a new, dynamic theory of urban spatial structure that emerges from the models and their applications.

The models are primarily land use models, but the more advanced ones also show the dynamics of population and economic activities, and are integrated with models in other domains such as economics, demography, and transportation. The result is a rich and realistic representation of the spatial dynamics of a variety of urban phenomena. The book is unique in its coverage of both the general issues associated with complex self-organizing systems and the specifics of designing and implementing models of such systems…(More)”.

Using AI to Map Urban Change

Curated on Posted on by Stefaan Verhulst

Brief by Tianyuan Huang, Zejia Wu, Jiajun Wu, Jackelyn Hwang, Ram Rajagopal: “Cities are constantly evolving, and better understanding those changes facilitates better urban planning and infrastructure assessments and leads to more sustainable social and environmental interventions. Researchers currently use data such as satellite imagery to study changing urban environments and what those changes mean for public policy and urban design. But flaws in the current approaches, such as inadequately granular data, limit their scalability and their potential to inform public policy across social, political, economic, and environmental issues.

Street-level images offer an alternative source of insights. These images are frequently updated and high-resolution. They also directly capture what’s happening on a street level in a neighborhood or across a city. Analyzing street-level images has already proven useful to researchers studying socioeconomic attributes and neighborhood gentrification, both of which are essential pieces of information in urban design, sustainability efforts, and public policy decision-making for cities. Yet, much like other data sources, street-level images present challenges: accessibility limits, shadow and lighting issues, and difficulties scaling up analysis.

To address these challenges, our paper “CityPulse: Fine-Grained Assessment of Urban Change with Street View Time Series” introduces a multicity dataset of labeled street-view images and proposes a novel artificial intelligence (AI) model to detect urban changes such as gentrification. We demonstrate the change-detection model’s effectiveness by testing it on images from Seattle, Washington, and show that it can provide important insights into urban changes over time and at scale. Our data-driven approach has the potential to allow researchers and public policy analysts to automate and scale up their analysis of neighborhood and citywide socioeconomic change…(More)”.

Governments Empower Citizens by Promoting Digital Rights

Curated on Posted on by Stefaan Verhulst

Article by Julia Edinger: “The rapid rise of digital services and smart city technology has elevated concerns about privacy in the digital age and government’s role, even as cities from California to Texas take steps to make constituents aware of their digital rights.

Earlier this month, Long Beach, Calif., launched an improved version of its Digital Rights Platform, which shows constituents their data privacy and digital rights and information about how the city uses technologies while protecting digital rights.

“People’s digital rights are no different from their human or civil rights, except that they’re applied to how they interact with digital technologies — when you’re online, you’re still entitled to every right you enjoy offline,” said Will Greenberg, staff technologist at the Electronic Frontier Foundation (EFF), in a written statement. The nonprofit organization defends civil liberties in the digital world.


Long Beach’s platform initially launched several years ago, to mitigate privacy concerns that came out of the 2020 launch of a smart city initiative, according to Long Beach CIO Lea Eriksen. When that initiative debuted, the Department of Innovation and Technology requested the City Council approve a set of data privacy guidelines to ensure digital rights would be protected, setting the stage for the initial platform launch. Its 2021 beta version has now been enhanced to offer information on 22 city technology uses, up from two, and an enhanced feedback module enabling continued engagement and platform improvements…(More)”.