Stefaan Verhulst

NASA Harvest: “Have you ever thought about how scientists keep track of what is happening all over the Earth? Thanks to satellites orbiting high above us, we have eyes in the sky that capture vast amounts of information every day. These satellites monitor everything from sprawling forests and melting glaciers to tiny fishing boats and fields of crops. But turning this endless stream of satellite data into meaningful insights is a big challenge. That is why a team of researchers from NASA Harvest, the Allen Institute for AI (Ai2) and partner organizations set out to create a smarter solution.

Their new study, titled “Galileo: Learning Global & Local Features of Many Remote Sensing Modalities,” was recently published and brought together experts from across the globe. The team aimed to build a tool that could make better sense of all the different types of satellite data we collect so we can make more informed decisions to protect our world.

Why is this research so important? Because satellites do far more than take pictures from space. They help farmers decide when to plant and harvest crops, track how fast glaciers are disappearing, monitor floods, and even detect marine debris floating in the ocean. However, satellite data comes in many forms, like optical images, radar scans, and climate measurements. Until now, most computer models could only handle one type of data at a time. This meant scientists needed separate systems for each problem.

Enter Galileo. This new artificial intelligence (AI) model was designed to process many kinds of satellite data all at once. Even more impressively, Galileo can detect both large-scale patterns, like glaciers retreating over decades, and tiny, short-lived details, like a fishing boat appearing for just a day. By learning to recognize these patterns across multiple scales and data types, Galileo gives researchers a more complete view of what is happening on Earth.

The team found that Galileo outperformed older models that were specialized for just one kind of data. With Galileo, scientists can now use a single model to tackle a wide range of challenges. These include mapping agricultural land, detecting floods, and monitoring marine pollution. It is a powerful step toward making satellite data more versatile and accessible…(More)”

Editorial to Special Issue by Saeid Pourroostaei Ardakani et al: “Data Analytics in Sustainable City PlanningPredictive analytics play an increasingly central role in sustainable city planning. By applying machine learning algorithms to large-scale and multi-source datasets, cities are able to forecast dynamic phenomena such as traffic congestion, crime incidents, and flood risk. These anticipatory insights are crucial for proactive urban management, allowing for early interventions and resource optimisation. Alongside this, the emergence of Digital Twins marks a shift from reactive to real-time urban governance. As a result, cities such as Singapore, Los Angeles, and Amsterdam improve these models to manage infrastructure across sectors including transportation, water supply, energy distribution, and public space usage. These digital ecosystems enable planners to test policy scenarios, monitor service performance, and respond adaptively to changing conditions.

The integration of socio-demographic data into geospatial models enables researchers to identify and analyse disparities in urban vulnerability. For instance, spatial mapping of heat exposure in Indian cities such as Delhi and Bengaluru has informed the more equitable allocation of cooling infrastructure. These equity-oriented approaches ensure that sustainability initiatives are not only technically robust but also socially inclusive. Indeed, they support policymakers in targeting resources toward the most vulnerable populations and thereby addressing persistent inequalities in urban service delivery.

The role of participatory digital platforms is a critical dimension of the sustainable planning discourse. Cities are increasingly turning to the use of GIS tools and e-planning applications to facilitate community involvement in the urban design process. These tools democratise access to data and decision-making and enable citizens to co-create solutions for their neighbourhoods. Such participation enhances the legitimacy and responsiveness of urban policy especially in contexts where historically marginalised groups have been excluded from formal planning mechanisms…(More)”.

Book by Ronald Bradfield: “Organizations today face an increasingly complex contextual environment. The intensity of what is recognized as a VUCA world has changed how they view the world, interact with each other, and respond to this environment.

Understanding the Future shows individuals and organizations how to develop scenario planning, using the Intuitive Logics (IL) model, to perceive what is happening in the business environment and how to improve strategic decision-making to plan for uncertainty.

Ronald Bradfield, a renowned scenario planning practitioner, traces the origins of scenario planning from its evolution to associated techniques and details the IL development process from Stage 1 to Stage 5. He includes an insightful chapter on how people think, describing the role of heuristics and biases, reviewing some of the commonly known ones, and concludes with the pros and cons of the IL model.

This book includes extensive reference material: appendices, a list of Foresight and Scenario organizations, Futures journals and magazines, published scenarios, select readings and guides, and the author’s unique case material directly from his world-leading consulting work of the past 30 years.

Understanding the Future is an exceptional, comprehensive guide for postgrads, practitioners, leaders, policymakers and anyone involved in organizational development or management risk who needs to understand the IL scenario framework and its value in addressing organizational challenges amidst complexity…(More)”.

Book by Luca Mora et al: “…explores how to govern the planning, implementation, and maintenance operations in smart city projects and transitions, and the urban digitalization processes that may potentially trigger. It provides readers with the evidence-based knowledge they need to approach the complexity of smart city governance, responding to the United Nations’ call for more advanced strategic and technical support on urban digital transformations to national, regional, and local governments. The book uses a comprehensive framework that details what configuration of multi-level components should be considered in the governance of smart city transitions…(More)”.

Book by Mark Findlay,: “This prescient book examines social ordering and governance in the digital universe. It demonstrates how attempts to enact regulations in virtual spaces cannot replicate laws and market arrangements in the real world, advocating for an alternative ‘new law’ to enable safe, sustainable and beneficial digital communities.

Mark Findlay discusses how this ‘new law’ could be achieved and the challenges it might face, addressing ideas of inclusive and collaborative governance, digital self-determination and communal bonding in virtual spaces. He outlines the differences between the metaverse and ‘realspace’ which call into question conventional legal reasoning and appreciations, rethinking current reductive paradigms of the virtual universe as an outpost for private property and exchange markets. Governing the Metaverse ultimately explores the notion of law as an enabler of change rather than an enforcer of the status quo and emphasises the potential of this more adaptable interpretation of the law to create an empowering digital world.

Students and scholars of constitutional and administrative law, law and politics and internet and technology law will greatly benefit from this thought-provoking book. It is also a vital resource for policymakers and practitioners in the fields of public policy, regulation and governance and technology and IT…(More)”.

Essay by Marthe Smedinga, Angela Ballantyne and Owen Schaefer: “Advancing the public interest’ is a criterion for de-identified data use for research via several national data platforms and biobanks. This may be referred to via cognate terms such as public benefit, public good or social value. The criterion is often adopted without it being a legal requirement. It is a legal requirement in some jurisdictions for sharing identifiable data without consent, which does not apply to de-identified data. We argue that, even in circumstances where there are few or no legal restrictions on the sharing of de-identified data, there is a sound ethical reason for platforms to nevertheless impose a public interest criterion on data sharing. We argue that a public interest test is ethically essential for justifying research use of de-identified data via government-funded platforms because (1) it allows to promote public good and to minimise potential harmful consequences of research for both individuals and groups, for example, by offering grounds to reject research that could lead to stigmatisation of marginalised populations; (2) national data platforms hold public data and are made possible by government funds, and therefore should be used to support public interests and (3) it can demonstrate trustworthiness and contribute to promoting the social licence for data platforms to operate, which is especially important for efforts to align data governance policies with public norms and expectations…(More)”.

Press Release: “On Saturday, 9 August, National Women’s Day, the Department of Planning, Monitoring and Evaluation (DPME), together with the Pan African Collective for Evidence (PACE), unveiled South Africa’s first AI-driven Living Evidence Map aimed at tackling Gender-Based Violence and Femicide (GBVF).

Minister Maropene Ramokgopa emphasised that the launch goes beyond mere technology—it’s about taking action. “It is a tool for action, a tool for justice, and a tool that puts survivors first. We will not end GBVF with words alone. We need evidence, accountability, and the courage to act.

The cutting-edge digital platform was developed to bolster Pillar 6 of the National Strategic Plan on Gender-Based Violence and Femicide (NSP GBVF), which focuses on improving research and information management.

With this initiative, South Africa now boasts the country’s largest centralised and regularly updated gender evidence database, consolidating academic research, community insights, evaluations, and government data into a single platform.

“To end GBVF, we need to understand what works, for whom, and why. This platform gives us the power to base decisions on evidence rather than assumptions,” stated the department.

The Living Evidence Map is a collaborative effort involving researchers, civil society, and government departments. It is powered by ChatEIDM, an AI engine that enables real-time interaction with the data.

The platform is designed to assist:

• Policymakers in creating targeted interventions
• Civil society organisations in developing evidence-based strategies
• Researchers and evaluators in spotting gaps and trends
• The general public in gaining insight into the scale of GBVF and potential solutions…(More)”

Article by Haishan Fu, Aivin Solatorio, Olivier Dupriez and Craig Hammer: “AI, particularly large language models (LLMs), is completely transforming the way people interact with data. Data users at all levels of experience and expertise—from first-timers to power users—are now able to pose complex questions in natural language to chatbots, to which they expect to promptly find, interpret, and present data-driven insights packaged as pithy, accurate responses.

For this evolution to be successful, AI systems need to get it right. This means the data being accessed and interpreted by AI systems must first be evaluated, validated, structured, governed, and shared in ways that support the responsible and effective use of AI. In short, the data must be “AI-ready.” 

AI-ready data does not supplant earlier advancements, foundational concepts, or standards—such as the Fundamental Principles of Official Statistics, open data frameworks, or the FAIR (Findable, Accessible, Interoperable, and Reusable) principles—but rather it builds on them. By extending established foundations and standards, AI-ready data means that development data is continuously open, discoverable, and reusable, while ensuring that it is systematically organized and well-documented, to facilitate seamless use by both people and AI systems. Ensuring AI-readiness can thus shorten the distance between development data and decision-making for better policies and faster innovation, democratizing development insights. The World Bank, in its efforts to become a bigger, better “Data Bank,” is already working to make this happen, in partnership with country partners and the global development community…(More)” See also: Moving Toward the FAIR-R principles: Advancing AI-Ready Data.

Paper by Alisha Suhag, Romana Burgess and Anya Skatova: “The growing ubiquity of digital footprint data presents new opportunities for behavioral epidemiology and public health research. Among these, supermarket loyalty card data—passively collected records of consumer purchases—offer objective, high-frequency insights into health-related behaviors at both individual and population levels. This paper explores the potential of loyalty card data to strengthen public health surveillance across 4 key behavioral risk domains: diet, alcohol, tobacco, and over-the-counter medication use. Drawing on recent empirical studies, we outline how these data can complement traditional epidemiological data sources by improving exposure assessment, enabling real-time trend monitoring, and supporting intervention evaluation. We also discuss critical methodological challenges, including issues of representativeness, data integration, and privacy, as well as the need for robust validation strategies. By synthesizing the current evidence base and offering practical recommendations for researchers, this paper highlights how loyalty card data can be responsibly leveraged to advance behavioral risk monitoring and support the adaptation of epidemiological practice to contemporary digital data environments…(More)”.

Paper by Elena Murray, Moiz Raja Shaikh, Stefaan Verhulst, Hinali Dosh, Romeo Leapciuc, Perizat Mamutalieva, and Mahadia Tunga: “As data-driven service delivery expands, data reuse holds significant potential to improve access to and quality of essential services for young people. However, limited youth involvement in decisions about how their data is reused risks perpetuating mistrust and deepening the inequalities that these services seek to address, particularly if young people choose to avoid seeking services or withhold critical information out of fear of misuse. Responsible data reuse to enhance service delivery must therefore be grounded in methodologies that meaningfully engage youth and reflect their preferences and expectations. This paper presents findings from the NextGenData project, which developed and piloted a scalable methodology for engaging young people aged 19-24 in co-designing responsible data reuse strategies. Conducted as a year-long participatory action research initiative across India, Tanzania, Moldova, and Kyrgyzstan, the approach implemented youth assemblies, deliberative methods, and localized facilitation by national partners to engage young people. The study emphasizes the importance of context-specific, culturally responsive facilitation, and sustained, multi-phase engagement as the foundation for establishing a social license for data reuse. We present recommendations for practitioners to embed youth-centered approaches in data governance and offer a publicly available toolkit for replication. By centering young people in data decisions, this methodology advances ethical, inclusive, and effective service delivery and digital self-determination for young generations…(More)”.