Unlocking Green Deal Data: Innovative Approaches for Data Governance and Sharing in Europe


JRC Report: “Drawing upon the ambitious policy and legal framework outlined in the Europe Strategy for Data (2020) and the establishment of common European data spaces, this Science for Policy report explores innovative approaches for unlocking relevant data to achieve the objectives of the European Green Deal.

The report focuses on the governance and sharing of Green Deal data, analysing a variety of topics related to the implementation of new regulatory instruments, namely the Data Governance Act and the Data Act, as well as the roles of various actors in the data ecosystem. It provides an overview of the current incentives and disincentives for data sharing and explores the existing landscape of Data Intermediaries and Data Altruism Organizations. Additionally, it offers insights from a private sector perspective and outlines key data governance and sharing practices concerning Citizen-Generated Data (CGD).

The main conclusions build upon the concept of “Systemic Data Justice,” which emphasizes equity, accountability, and fair representation to foster stronger connections between the supply and demand of data for a more effective and sustainable data economy. Five policy recommendations outline a set of main implications and actionable points for the revision of the INSPIRE Directive (2007) within the context of the common European Green Deal data space, and toward a more sustainable and fair data ecosystem. However, the relevance of these recommendations spills over Green Deal data only, as they outline key elements to ensure that any data ecosystem is both just and impact-oriented…(More)”.

Conversational Swarms of Humans and AI Agents enable Hybrid Collaborative Decision-making


Paper by Louis Rosenberg et al: “Conversational Swarm Intelligence (CSI) is an AI-powered communication and collaboration technology that allows large, networked groups (of potentially unlimited size) to hold thoughtful conversational deliberations in real-time. Inspired by the efficient decision-making dynamics of fish schools, CSI divides a human population into a set of small subgroups connected by AI agents. This enables the full group to hold a unified conversation. In this study, groups of 25 participants were tasked with selecting a roster of players in a real Fantasy Baseball contest. A total of 10 trials were run using CSI. In half the trials, each subgroup was augmented with a fact-providing AI agent referred to herein as an Infobot. The Infobot was loaded with a wide range of MLB statistics. The human participants could query the Infobot the same way they would query other persons in their subgroup. Results show that when using CSI, the 25-person groups outperformed 72% of individually surveyed participants and showed significant intelligence amplification versus the mean score (p=0.016). The CSI-enabled groups also significantly outperformed the most popular picks across the collected surveys for each daily contest (p<0.001). The CSI sessions that used Infobots scored slightly higher than those that did not, but it was not statistically significant in this study. That said, 85% of participants agreed with the statement ‘Our decisions were stronger because of information provided by the Infobot’ and only 4% disagreed. In addition, deliberations that used Infobots showed significantly less variance (p=0.039) in conversational content across members. This suggests that Infobots promoted more balanced discussions in which fewer members dominated the dialog. This may be because the infobot enabled participants to confidently express opinions with the support of factual data…(More)”.

Effective Data Stewardship in Higher Education: Skills, Competences, and the Emerging Role of Open Data Stewards


Paper by Panos Fitsilis et al: “The significance of open data in higher education stems from the changing tendencies towards open science, and open research in higher education encourages new ways of making scientific inquiry more transparent, collaborative and accessible. This study focuses on the critical role of open data stewards in this transition, essential for managing and disseminating research data effectively in universities, while it also highlights the increasing demand for structured training and professional policies for data stewards in academic settings. Building upon this context, the paper investigates the essential skills and competences required for effective data stewardship in higher education institutions by elaborating on a critical literature review, coupled with practical engagement in open data stewardship at universities, provided insights into the roles and responsibilities of data stewards. In response to these identified needs, the paper proposes a structured training framework and comprehensive curriculum for data stewardship, a direct response to the gaps identified in the literature. It addresses five key competence categories for open data stewards, aligning them with current trends and essential skills and knowledge in the field. By advocating for a structured approach to data stewardship education, this work sets the foundation for improved data management in universities and serves as a critical step towards professionalizing the role of data stewards in higher education. The emphasis on the role of open data stewards is expected to advance data accessibility and sharing practices, fostering increased transparency, collaboration, and innovation in academic research. This approach contributes to the evolution of universities into open ecosystems, where there is free flow of data for global education and research advancement…(More)”.

Enabling Digital Innovation in Government


OECD Report: “…presents the OECD’s definition of GovTech (Chapter 2) and sets out the GovTech Policy Framework (Chapter 3). The framework is designed to guide governments on how to establish the conditions for successful, sustainable, and effective GovTech.

The framework consists of two parts: the GovTech Building Blocks and the GovTech Enablers. The building blocks (Chapter 3) represent the foundations at the micro-level needed to establish impactful GovTech practices within public sectors by introducing more agile practices, mitigating risks, and building meaningful collaboration with the GovTech ecosystem. These building blocks include:

  • Mature digital government infrastructure: including the necessary technology, infrastructure, tools, and data governance to enable both GovTech collaborations and the digital solutions they develop.
  • Capacities for collaboration and experimentation: within the public sector, including the digital skills and multidisciplinary teams; agile processes, tools, and methodologies; and a culture that encourages experimentation and accepts failure. 
  • Resources and implementation support: considering how to make funding available, how to evolve procurement approaches, and how to scale successful pilots across organisations and internationally.
  • Availability and maturity of GovTech partners: including acceleration programmes to support start-ups growth by facilitating access to capital, the scaling up of solutions, and minimising barriers to access procurement opportunities.

At the macro-level, the enablers (Chapter 4) instead create an environment that fosters the development of GovTech and facilitates good practices. This is done at the:

  • Strategic layer: where governments could use GovTech strategies and champions in senior leadership positions to mobilise support and set a clear direction for GovTech.
  • Institutional layer: where governments could seek collaboration and knowledge-sharing across institutions at the national, regional, or policy levels.
  • Network layer: where both governments and GovTech actors should seek to mobilise the network collectively to strengthen the GovTech practice and garner broader support from communities…(More)”

Exploring the Intersections of Open Data and Generative AI: Recent Additions to the Observatory


Blog by Roshni Singh, Hannah Chafetz, Andrew Zahuranec, Stefaan Verhulst: “The Open Data Policy Lab’s Observatory of Examples of How Open Data and Generative AI Intersect provides real-world use cases of where open data from official sources intersects with generative artificial intelligence (AI), building from the learnings from our report, “A Fourth Wave of Open Data? Exploring the Spectrum of Scenarios for Open Data and Generative AI.” 

The Observatory includes over 80 examples from several domains and geographies–ranging from supporting administrative work within the legal department of the Government of France to assisting researchers across the African continent in navigating cross-border data sharing laws. The examples include generative AI chatbots to improve access to services, conversational tools to help analyze data, datasets to improve the quality of the AI output, and more. A key feature of the Observatory is its categorization across our Spectrum of Scenarios framework, shown below. Through this effort, we aim to bring together the work already being done and identify ways to use generative AI for the public good.

Screenshot 2024 10 25 at 10.50.23 am

This Observatory is an attempt to grapple with the work currently being done to apply generative AI in conjunction with official open data. It does not make a value judgment on their efficacy or practices. Many of these examples have ethical implications, which merit further attention and study. 

From September through October, we added to the Observatory:

  • Bayaan Platform: A conversational tool by the Statistics Centre Abu Dhabi that provides decision makers with data analytics and visualization support.
  • Berufsinfomat: A generative AI tool for career coaching in Austria.
  • ChatTCU: A chatbot for Brazil’s Federal Court of Accounts.
  • City of Helsinki’s AI Register: An initiative aimed at leveraging open city data to enhance civic services and facilitate better engagement with residents.
  • Climate Q&A: A generative AI chatbot that provides information about climate change based on scientific reports.
  • DataLaw.Bot: A generative AI tool that disseminates data sharing regulations with researchers across several African countries…(More)”.

Unlocking data for climate action requires trusted marketplaces


Report by Digital Impact Alliance: “In 2024, the northern hemisphere recorded the hottest summer overall, the hottest day, and the hottest ever month of August. That same month – August 2024 – this warming fueled droughts in Italy and intensified typhoons that devastated parts of the Philippines, Taiwan, and China. The following month, new research calculated that warming is costing the global economy billions of dollars: an increase in extreme heat and severe drought costs about 0.2% of a country’s GDP. 

These are only the latest stories and statistics that illustrate the growing costs of climate change – data points that have emerged in the short time since we published our second Spotlight on unlocking climate data with open transaction networks.

This third paper in the series continues the work of the Joint Learning Network on Unlocking Data for Climate Action (Climate Data JLN). This multi-disciplinary network identified multiple promising models to explore in the context of unlocking data for climate action. This Spotlight paper examines the third of these models: data spaces. Through examination of data spaces in action, the paper analyzes the key elements that render them more or less applicable to specific climate-related data sets. Data spaces are relatively new and mostly conceptual, with only a handful of implementations in process and concentrated in a few geographic areas. While this model requires extensive up-front work to agree upon governance and technical standards, the result is an approach that overcomes trust and financing issues by maintaining data sovereignty and creating a marketplace for data exchange…(More)”.

Local Systems


Position Paper by USAID: “…describes the key approaches USAID will use to translate systems thinking into systems practice. It focuses on ways USAID can better understand and engage local systems to support them in producing more sustainable results. Systems thinking is a mindset and set of tools that we use to understand how systems behave and produce certain results or outcomes. Systems practice is the application of systems thinking to better understand challenges and strengthen the capacity of local systems to unlock locally led, sustained progress. The shift from systems thinking to systems practice is driven by a desire to integrate systems practice throughout the Program Cycle and increase our capacity to actively and adaptively manage programming in ways that recognize complexity and help make our programs more effective and sustainable.

These approaches will be utilized alongside and within the context of USAID’s policies and guidance, including technical guidance for specific sectors, as well as evidence and lessons learned from partners around the world. Systems thinking is a long-standing discipline that can serve as a powerful tool for understanding and working with local systems. It has been a consistent component of USAID’s decades-long commitment to locally led development and humanitarian assistance. USAID uses systems thinking to better understand the complex and interrelated challenges we confront – from climate change to migration to governance – and the perspectives of diverse stakeholders on these issues. When we understand challenges as complex systems – where outcomes emerge from the interactions and relationships between actors and elements in that system – we can leverage and help strengthen the local capacities and relationships that will ultimately drive sustainable progress…(More)”.

Commission launches public consultation on the rules for researchers to access online platform data under the Digital Services Act


Press Release: “Today, the Commission launched a public consultation on the draft delegated act on access to online platform data for vetted researchers under the Digital Services Act (DSA).

text Digital Services Act inside a white triangle against a blue background

With the Digital Services Act, researchers will for the first time have access to data to study systemic risks and to assess online platforms’ risk mitigation measures in the EU. It will allow the research community to play a vital role in scrutinising and safeguarding the online environment.

The draft delegated act clarifies the procedures on how researchers can access Very Large Operating Platforms’ and Search Engines’ data. It also sets out rules on data formats and data documentation requirements. Lastly, it establishes the DSA data access portal, a one-stop-shop for researchers, data providers, and DSCs to exchange information on data access requests. The consultation follows a first call for evidence.

The consultation will run until 26 November 2024. After gathering public feedback, the Commission plans to adopt the rules in the first quarter of 2025…(More)”.

Proactive Mapping to Manage Disaster


Article by Andrew Mambondiyani: “..In March 2019, Cyclone Idai ravaged Zimbabwe, killing hundreds of people and leaving a trail of destruction. The Global INFORM Risk Index data shows that Zimbabwe is highly vulnerable to extreme climate-related events like floods, cyclones, and droughts, which in turn destroy infrastructure, displace people, and result in loss of lives and livelihoods.

Severe weather events like Idai have exposed the shortcomings of Zimbabwe’s traditional disaster-management system, which was devised to respond to environmental disasters by providing relief and rehabilitation of infrastructure and communities. After Idai, a team of climate-change researchers from three Zimbabwean universities and the local NGO DanChurchAid (DCA) concluded that the nation must adopt a more proactive approach by establishing an early-warning system to better prepare for and thereby prevent significant damage and death from such disasters.

In response to these findings, the Open Mapping Hub—Eastern and Southern Africa (ESA Hub)—launched a program in 2022 to develop an anticipatory-response approach in Zimbabwe. The ESA Hub is a regional NGO based in Kenya created by the Humanitarian OpenStreetMap Team (HOT), an international nonprofit that uses open-mapping technology to reduce environmental disaster risk. One of HOT’s four global hubs and its first in Africa, the ESA Hub was created in 2021 to facilitate the aggregation, utilization, and dissemination of high-quality open-mapping data across 23 countries in Eastern and Southern Africa. Open-source expert Monica Nthiga leads the hub’s team of 13 experts in mapping, open data, and digital content. The team collaborates with community-based organizations, humanitarian organizations, governments, and UN agencies to meet their specific mapping needs to best anticipate future climate-related disasters.

“The ESA Hub’s [anticipatory-response] project demonstrates how preemptive mapping can enhance disaster preparedness and resilience planning,” says Wilson Munyaradzi, disaster-services manager at the ESA Hub.

Open-mapping tools and workflows enable the hub to collect geospatial data to be stored, edited, and reviewed for quality assurance prior to being shared with its partners. “Geospatial data has the potential to identify key features of the landscape that can help plan and prepare before disasters occur so that mitigation methods are put in place to protect lives and livelihoods,” Munyaradzi says…(More)”.

The Emerging Age of AI Diplomacy


Article by Sam Winter-Levy: “In a vast conference room, below chandeliers and flashing lights, dozens of dancers waved fluorescent bars in an intricately choreographed routine. Green Matrix code rained down in the background on a screen that displayed skyscrapers soaring from a desert landscape. The world was witnessing the emergence of “a sublime and transcendent entity,” a narrator declared: artificial intelligence. As if to highlight AI’s transformative potential, a digital avatar—Artificial Superintelligence One—approached a young boy and together they began to sing John Lennon’s “Imagine.” The audience applauded enthusiastically. With that, the final day dawned on what one government minister in attendance described as the “world’s largest AI thought leadership event.”

This surreal display took place not in Palo Alto or Menlo Park but in Riyadh, Saudi Arabia, at the third edition of the city’s Global AI Summit, in September of this year. In a cavernous exhibition center next to the Ritz Carlton, where Crown Prince Mohammed bin Salman imprisoned hundreds of wealthy Saudis on charges of corruption in 2017,robots poured tea and mixed drinks. Officials in ankle-length white robes hailed Saudi Arabia’s progress on AI. American and Chinese technology companies pitched their products and announced memorandums of understanding with the government. Attendantsdistributed stickers that declared, “Data is the new oil.”

For Saudi Arabia and its neighbor, the United Arab Emirates (UAE), AI plays an increasingly central role in their attempts to transform their oil wealth into new economic models before the world transitions away from fossil fuels. For American AI companies, hungry for capital and energy, the two Gulf states and their sovereign wealth funds are tantalizing partners. And some policymakers in Washington see a once-in-a-generation opportunity to promise access to American computing power in a bid to lure the Gulf states away from China and deepen an anti-Iranian coalition in the Middle East….The two Gulf states’ interest in AI is not new, but it has intensified in recent months. Saudi Arabia plans to create a $40 billion fund to invest in AI and has set up Silicon Valley–inspired startup accelerators to entice coders to Riyadh. In 2019, the UAE launched the world’s first university dedicated to AI, and since 2021, the number of AI workers in the country has quadrupled, according to government figures. The UAE has also released a series of open-source large language models that it claims rival those of Google and Meta, and earlier this year it launched an investment firm focused on AI and semiconductors that could surpass $100 billion in assets under management…(More)”.