Blockchain applications for sustainable development in the EU public sector: an AI-based mapping of alignment with the Sustainable Development Goals

1 Introduction

Across the EU, governments are exploring how emerging technologies like blockchain technology (BCT) can support their efforts to achieve the United Nations Sustainable Development Goals (SDGs) (Thanasi Boçe and Hoxha, 2024). These goals, which include targets such as reducing inequality, promoting clean energy, and ensuring responsible consumption, require innovative solutions that can bring more transparency, efficiency, and accountability to public services (Thanasi Boçe and Hoxha, 2024; United Nations Conference on Trade and Development, 2021). In this context, BCT has attracted growing attention as a potential enabler of secure, auditable and decentralised data infrastructures capable of supporting more trustworthy and resilient public sector processes.

Despite increasing experimentation with BCT in public service delivery, there is limited empirical research systematically analysing whether and how these initiatives support the SDGs (Medaglia and Damsgaard, 2020; Riyoldi et al., 2023; Tan et al., 2022). This study addresses this gap by examining 306 public sector BCT-based use cases in the EU and assessing their alignment with SDG objectives through an AI-supported text analytics approach. By adopting a large-scale classification pipeline grounded in Large Language Models (LLMs), this study provides one of the first EU-wide empirical overviews of how BCT-based deployments connect to individual SDGs and how this alignment varies across policy domains.

BCT is commonly characterised by properties such as immutability, decentralisation, and transparency, which collectively offer new opportunities to strengthen trust in digital public services and data-driven decision-making (Martin-Bosch et al., 2022). These features are particularly useful in areas like public procurement, land registry, or supply chain monitoring, where clear, tamper-proof records can reduce corruption and improve fairness (Martin-Bosch et al., 2022). For example, some EU cities are testing BCT for tracking renewable energy generation and sharing ¹ . Others are using it to increase transparency in welfare payments, ensure authenticity in educational certificates ² , or manage digital identities for refugees ³ . These cases show how BCT can help address social, environmental, and economic challenges that align with several SDGs, including Goal 16 (Peace, Justice and Strong Institutions), Goal 7 (Affordable and Clean Energy), and Goal 4 (Quality Education). Yet, despite these promising examples, the systemic contribution of BCT to the SDGs across the EU public sector remains largely undocumented.

While the use of BCT in the public sector is still in an experimental phase (Martin-Bosch et al., 2022), the early results have stimulated relevant conversations about the sustainable use of this technology (Mulligan et al., 2024; Patel, 2024; Thanasi Boçe and Hoxha, 2024; Thanasi-Boçe and Hoxha, 2025). As governments continue to test its potential, it is crucial to explore both the benefits and risks and to understand the conditions under which BCT can be responsibly integrated into public services in ways that meaningfully advance the SDGs. This includes assessing not only where BCT deployments align with sustainability objectives, but also where blind spots, trade-offs and sectoral imbalances may limit their impact.

The present study offers a systematic, EU-wide analysis of BCT-based use cases in public administration and their alignment with the SDGs. Rather than explaining the causal drivers of this alignment, the study maps how these use cases are positioned in relation to the SDGs across policy domains, application types, and administrative contexts. In this way, it provides an empirical overview of current alignment patterns and identifies areas where stronger or weaker associations are observed.

The study is therefore guided by two core research questions. First: how do BCT-based use cases piloted or implemented by EU public administrations align with the Sustainable Development Goals? Second: how does this alignment vary across sectors, application types, and administrative contexts? Addressing these questions contributes empirical evidence to a domain where systematic, large-scale analysis has been largely absent and demonstrates the viability of AI-assisted classification as a scalable tool for sustainability-oriented research on public sector innovation.

The remainder of the article is structured as follows. Section 2 presents the conceptual and empirical background. Section 3 describes the dataset and methodology, including the LLM-based classification pipeline. Section 4 presents the results. Section 5 discusses the findings in light of EU digital and sustainability policy priorities. Section 6 outlines the limitations of this study and future research directions. Section 7 concludes with contributions, implications, and overall reflections.

2 Background

2.1 Blockchain technology in the public sector

BCT, as defined by Allessie et al. (2019), is based on a distributed ledger system that records and validates transactions across a peer-to-peer (P2P) network through consensus, stores them immutably in sequentially linked blocks, and can incorporate programmable behaviours via smart contracts, providing a foundation for diverse applications in digital government and beyond. In government settings, these characteristics support core public sector objectives, including trustworthy record-keeping, auditable decision processes, secure data exchange and cross-border interoperability (Ølnes et al., 2017).

European public administrations have been experimenting with BCT across a wide range of domains, such as public procurement, land registration, digital identity, supply-chain monitoring and regulatory reporting (Martin-Bosch et al., 2022). These initiatives seek to address persistent governance challenges such as information asymmetries, fraud risks, limited auditability and fragmented administrative data infrastructures. For instance, BCT-based identity solutions have been piloted to strengthen citizen verification processes, while notarisation services have been explored to guarantee the authenticity of certificates or official documents. Such applications align closely with public value objectives of transparency, accountability and integrity (Rodriguez Müller et al., 2025).

In this context, EU public sector experimentation has also been shaped by a broader policy ecosystem aimed at strengthening the Union’s digital capacity and interoperability. The Digital Europe Programme (DEP) ⁴ provides targeted funding to accelerate the deployment of advanced digital technologies, including AI, cybersecurity, cloud infrastructures and BCT, across public administrations. Complementing this, the Interoperable Europe Act (IEA) ⁵ establishes a common governance and cooperation framework to ensure cross-border interoperability of public services, promoting shared standards, reusable solutions and coordinated digital governance. Moreover, the European Blockchain Services Infrastructure (EBSI) ⁶ represents a flagship initiative: a cross-border, public sector BCT network designed to deliver secure, verifiable and interoperable digital public services, such as trusted credentials and notarisation. Furthermore, ongoing efforts under the European Digital Identity (eIDAS2) ⁷ framework aim to introduce a European Digital Identity Wallet ⁸ to enable citizens and businesses to securely access public and private services across the EU through trusted digital identities and verifiable credentials. Together, these initiatives provide a strategic and regulatory foundation that shapes how EU administrations experiment with and deploy BCT for public value creation.

At the same time, the public sector BCT literature emphasises that its effective use depends not only on its technical properties but also on organisational, institutional and governance arrangements (Schulz et al., 2020). Research highlights challenges such as the need for new governance models for distributed infrastructures, the reconfiguration of administrative roles, coordination among multiple agencies, integration with legacy systems and questions around accountability, data protection and long-term sustainability (Janssen et al., 2020; Ølnes et al., 2017). These considerations underscore that BCT adoption in the public sector is inherently socio-technical, requiring alignment of technological affordances with administrative capacities, regulatory requirements and institutional logics.

Overall, the public sector literature converges on the view that BCT functions primarily as an enabling infrastructure for trusted data management and cross-organisational coordination, rather than as a standalone technical innovation (Ølnes et al., 2017; Wirtz, 2022). This perspective provides an important foundation for understanding how BCT is being integrated into public administration and how its uses may align with broader strategic objectives. At the same time, its practical value remains contingent on broader socio-technical conditions, including organisational readiness, governance frameworks, interoperability and regulatory safeguards. This understanding informs the assessment of how BCT may contribute to broader public value goals and how real-world implementations relate to sustainability frameworks such as the SDGs.

2.2 Blockchain technology and sustainable development

In the context of sustainable development, BCT is increasingly adopted by the public sector (Riyoldi et al., 2023) as a tool to enhance environmental protection, social inclusion and responsible governance. Its potential contribution stems from its ability to facilitate secure and verifiable data sharing, thereby strengthening information trust across multi-stakeholder projects and potentially supporting transparent monitoring of processes with sustainability relevance (Karaszewski et al., 2021; Parmentola et al., 2022; Tafuro et al., 2023). These capabilities have been highlighted as particularly valuable for applications such as supply-chain transparency, renewable energy trading, and public accountability systems, all of which relate to multiple SDGs. This broader landscape also includes token-based and tokenised applications, although empirical evidence on their specific role in advancing public sector sustainability objectives remains limited.

While these examples illustrate BCT’s potential to support sustainability objectives, the extent to which such benefits are realised in public sector deployments across the EU remains insufficiently documented. Recent studies have also observed that the field remains fragmented (Thanasi-Boçe and Hoxha, 2025) and that it insufficiently addresses its policy implications (Mulligan et al., 2024).

A growing body of scholarship has examined how BCT can contribute to sustainable development (Parmentola et al., 2022; Thanasi-Boçe and Hoxha, 2025). Systematic reviews identify BCT’s contributions across several thematic areas, including resource efficiency, provenance verification, decentralised energy systems, and financial inclusion. Thanasi-Boçe and Hoxha (2025), reviewing 131 publications between 2015 and 2025, conclude that BCT-based applications cluster around supply-chain management, energy systems and social-service provision, but that the landscape remains fragmented and dominated by single-sector or conceptual analyses. At the same time, the review highlights persistent challenges that constrain large-scale impact, such as trade-offs between scalability and energy consumption, fragmented regulatory environments across jurisdictions, and organisational capability gaps.

Similar conclusions are drawn by Mulligan et al. (2024), who highlight that current research on BCT and sustainability remains largely concentrated in three domains: energy systems, supply chains, and IoT-enabled solutions such as smart cities. Parikshit et al. (2023) further identify four major research gaps: theoretical grounding, methodological limitations, research themes, and technology implementation challenges. Furthermore, according to Parmentola et al.’s (2022) systematic review, while BCT may support sustainability objectives, several challenges persist, including governance complexity, interoperability constraints and potential environmental trade-offs related to certain consensus mechanisms.

Despite this growing interest, the sustainability literature remains heavily oriented towards private-sector use cases and theoretical discussions and provides limited empirical insight into how BCT adopted by public administrations contributes to SDG-related objectives. Studies examining government-driven BCT initiatives tend to offer single-case analyses, conceptual assessments or sector-specific explorations, leaving a significant gap in understanding the broader pattern of public sector BCT adoption in relation to sustainable development (Parikshit et al., 2023; Parmentola et al., 2022; Thanasi-Boçe and Hoxha, 2025). Recent analyses focusing on business applications and supply chains (e.g., Di Salvo, 2025) further confirm that the empirical literature remains concentrated outside the public sector, where governance mandates, institutional constraints, and multi-level coordination dynamics differ substantially from market-driven settings.

Against this background, three interrelated gaps motivate the present study. First, no existing research systematically maps real-world public sector BCT deployments to the SDGs across multiple countries or policy domains. Second, existing reviews rely predominantly on manual or keyword-based classification approaches (Mulligan et al., 2024; Parikshit et al., 2023; Parmentola et al., 2022; Thanasi-Boçe and Hoxha, 2025), which struggle to scale across large corpora and lack the contextual sensitivity needed to detect cross-cutting SDG themes. Third, the policy implications of BCT-SDG alignment in the public sector remain insufficiently addressed (Mulligan et al., 2024), limiting the evidence base available to practitioners and policymakers.

To address these gaps, the present study examines a large corpus of public sector BCT-based use cases and analyses how their stated objectives align with the SDGs across governmental functions and application domains.

3 Data and methods

3.1 Dataset description

This study builds on a dataset of 306 BCT use cases implemented by national, regional, and local government entities across the EU, extracted from the case collection of the Public Sector Tech Watch (PSTW) ⁹ , an observatory dedicated to monitoring, analysing, and disseminating information related to the implementation of public services using AI, BCT and other emerging technologies in Europe. The PSTW is managed by the European Commission, more specifically by the Directorate-General for Informatics (DG DIGIT) and the Joint Research Centre (JRC). The dataset provides a consolidated view of public sector BCT-based use cases across Europe and offers an empirical basis for examining their thematic orientation and potential connections to the SDGs. All BCT-based use cases available in the PSTW at the time of writing were included in the dataset of analysis ¹⁰ .

As described in the PSTW methodology report (European Commission. Joint Research Centre, 2024), the cases were carefully compiled from a diverse array of secondary sources spanning the period from 2018 to 2025. These included international and national initiatives (e.g., the European Blockchain Observatory and Forum; the Dutch Blockchain Coalition), digital media (e.g., news outlets and analytical reports), and academic and grey literature. The data collection process also benefited from collaborative engagement with external researchers undertaking parallel investigations. The collection process followed a structured approach combining systematic scanning, source triangulation and consistency checks across classification fields to ensure coherence and minimise duplication. Although the dataset does not constitute a statistical census of BCT implementations in Europe, its breadth and diversity make it suitable for exploratory, cross-sector analyses of public sector BCT adoption.

The metadata fields extracted from the PSTW use case database included:

• Technology field: a category that specifies the type of technology used in each case, allowing for filtering of cases involving BCT and other emerging technologies.
• Name field: a brief title or identifier for each case, providing a concise summary of the project or initiative.
• Description field: a detailed summary of each case, used as input for GPT-4o-based classification against the SDGs to identify potential alignments and relationships.
• Classification of the Functions of Government (COFOG) ¹¹ : a standardised coding system that categorises government functions and expenditures, supporting the analysis of potential relationships between SDG targets and governmental functions, such as education, healthcare, or infrastructure development.

These fields form the basis of the SDG-mapping exercise, enabling the analysis of both the content of the described initiatives and their distribution across governmental functions.

3.2 SDGs mapping procedure

The mapping of BCT-based use cases to the SDGs followed a multi-stage, iterative process designed to balance analytical depth with scalability. The first step involved constructing condensed textual representations (<=500 characters each) of each SDG, retaining key terminology from their official SDG definitions as published by the UNDP ¹² , while reducing length to support automated processing. This ensured terminological precision without overwhelming the model with unnecessary detail.

Before selecting the final methodology based on LLMs, different approaches were tested. The initial approach employed keyword-matching techniques to identify SDG-related terms in each use case description. Although computationally efficient, this method lacked contextual understanding. To improve reliability, a supervised machine learning classifier was also tested, using a sample of human-labelled cases as training data. Although this approach produced more accurate classifications than keyword matching, its performance remained constrained by the availability of annotated data and its limited capacity to detect implicit or cross-cutting SDG themes.

The final stage involved employing LLMs as prompt-based evaluators to score the alignment between use case descriptions and the SDGs (Schroeder and Wood-Doughty, 2024). The analysis was conducted using the European Commission JRC internal GPT@JRC tool, due to its availability to all authors. Moreover, the tool integrates several recent LLMs within a protected and secure environment. Two main generative models available through the GPT@JRC platform (Fernández-Machado et al., 2025) were tested: OpenAI GPT-4o ¹³ and Meta LLaMA 3.3 ¹⁴ . The models were compared in terms of contextual accuracy, internal consistency, and computational efficiency. Both were embedded into a structured evaluation pipeline combining system-level and query-level prompts. Each use case was processed with refined SDG descriptions and relevant metadata (e.g., name, summary) to generate candidate SDG mappings. We also applied a LIME-based interpretability analysis (Ribeiro et al., 2016) to a subset of outputs to examine whether local feature attributions were broadly aligned with the expected decision rationale. This multi-stage approach allowed us to identify the limitations of simpler automated methods and to justify the use of LLMs as the primary analytical tool. For reproducibility, we documented the experimental configuration for each model, as exposed by the GPT@JRC platform interface, including model family and version identifier, inference parameters (temperature = 0.1; scoring and justification token limits), prompt templates, output-format constraints and parsing rules, retry logic, and execution conditions (e.g., run date and batching procedure, where available). These details are reported in Annex I/Supplementary Material. This documentation supports procedural reproducibility of the pipeline within the constraints of a managed platform environment. All runs were performed under fixed prompts and fixed parameters to minimise stochastic variation across executions. Where the platform abstracted provider-level API details, the available GPT@JRC configuration metadata was recorded and reported. The final LLM-based SDG-mapping pipeline used prompt-based inference and was not fine-tuned on task-specific training data; the human-labelled subset was used for benchmarking and validation.

An overview of the full classification pipeline is provided in Supplementary Figure 1, and a summary of the key configuration parameters is reported in Supplementary Table 1.

3.3 SDGs LLM-Evaluator prompt design

The manual validation of a 15% stratified sample of the use cases also confirmed the relative performance patterns described above, supporting the selection of GPT-4o as the primary model for the SDG-mapping pipeline.

The user prompt provided each initiative’s description and required the model to return exactly 17 integer values (1–10), one per SDG, in a strict format to facilitate automated parsing. A secondary prompt generated concise textual justifications for each score, limited to ≤500 characters and requiring explicit reference to the initiative’s content rather than generic SDG definitions. This two-step prompt design minimised variability in model behaviour, reduced ambiguity in numeric outputs, and maintained semantic alignment between the scoring and commentary phases.

When compared against human experts, the LLMs showed clearly differentiated levels of alignment in SDG classification performance. Human evaluators manually annotated a stratified 15% subset of all BCT-based use cases, and these annotations served as the benchmark for assessing model accuracy. Using quadratic weighted kappa as the evaluation metric (Bendavid, 2008), GPT-4o demonstrated the highest correspondence with expert judgments, consistently capturing both the ordered nature and the magnitude of SDG-relevance differences (see Figure 1). This indicates its suitability for automating complex mapping tasks that normally require expert interpretation. Quadratic weighted kappa was selected as the primary validation metric because it is suited to ordinal, multi-label scoring tasks, capturing both the direction and magnitude of disagreement between raters, whereas conventional binary metrics such as precision and recall are not directly applicable to a continuous 1–10 scoring scheme across 17 labels.

A quadratic weighted kappa value of 1.0 indicates perfect agreement with human evaluations, a value of 0.0 reflects performance no better than random chance, and negative values signify systematic disagreement. Higher scores correspond to stronger alignment with human scoring. Based on these results, the structured generative AI pipeline was implemented using GPT-4o as the primary model.

Based on these results, GPT-4o was selected as the primary model and integrated into a structured generative AI pipeline to operationalise the SDG-mapping procedure. The pipeline combines a system-level prompt, defining the overall task logic, with a query-level prompt adapted to each specific use case. For every BCT-based project in the PSTW repository, the model receives the refined SDG descriptions together with selected metadata fields (e.g., title, summary, thematic tags) and returns a structured set of SDG-specific alignment scores. This framework provides a replicable and scalable mechanism for SDG impact analysis, showing that LLM-as-a-judge approaches can deliver reliable, explainable outputs under controlled prompting conditions.

3.4 Validation and interpretation

The manual validation of a 15% stratified sample also confirmed the relative performance patterns described in Section 3.3, supporting the selection of GPT-4o as the primary model for the SDG-mapping pipeline. This validation process allowed us to identify patterns of misalignment, refine prompt design, and calibrate interpretation thresholds.

Inter-rater reliability among human evaluators was computed to verify consistency in manual coding, while cross-validation with multiple prompt configurations assessed the stability of LLM outputs. All experiments were conducted using fixed prompts, controlled temperature (0.1) and documented parameters (model version, batch size, API configuration) to minimise variance across runs.

Following validation, the full set of SDG alignment scores was analysed to detect recurring patterns, highlight underrepresented SDGs, and extract actionable insights on the alignment between BCT-based applications and the SDGs. This combined validation and interpretation framework provides a methodologically transparent and scalable way to analyse the sustainability orientation of public sector BCT-based use cases.

LLMs were used to interpret how each project description relates to the SDGs, rather than to measure actual impact. Because PSTW descriptions may be optimistic, promotional, or selective, the model may reproduce or amplify these biases. To mitigate this risk, the final GPT-4o results were checked against a human-coded sample (15% of cases), inter-coder agreement was assessed, and GPT-4o was compared with simpler methods previously tested, including keyword matching and supervised machine learning. Although this process cannot eliminate all bias in the source texts, it provides an external reference point and helps ensure that the final labels do not rely solely on the model’s unchecked judgments.

4 Results

Building on this validated framework, this section presents the results of the SDG-mapping exercise. It summarises the distribution of SDG alignment scores across the dataset, identifies dominant thematic linkages, and highlights the areas in which public sector BCT-based use cases show low or limited connections to the SDGs.

4.1 Overall alignment of BCT-based use cases with the SDGs

Across the 306 analysed BCT-based public sector use cases in EU Member States, the results reveal diverse patterns in the degree of alignment with the 17 SDGs. As illustrated in Figure 2, the average alignment scores vary substantially across goals, indicating that BCT-based applications in the public sector do not contribute uniformly across sustainability dimensions.

The highest alignment is observed for SDG 9 (Industry, Innovation and Infrastructure), which records an average score of 7.58. This reflects the predominance of initiatives aimed at strengthening digital infrastructures, enhancing data integrity, and supporting innovation ecosystems, areas that closely match BCT’s technical affordances. SDG 17 (Partnerships for the Goals) also scores comparatively high (6.72), suggesting that many projects involve cross-organisational collaboration, interoperability frameworks, or cross-border service provision. Moderate associations appear for SDG 8 (Decent Work and Economic Growth), SDG 10 (Reduced Inequalities) and SDG 16 (Peace, Justice and Strong Institutions), which collectively reflect BCT’s emerging role in strengthening administrative transparency, improving trust in public records, and supporting more efficient economic and governance processes.

In contrast, lower average scores are found for goals such as SDG 2 (Zero Hunger), SDG 6 (Clean Water and Sanitation), and SDG 14 (Life Below Water). These results highlight the limited direct application of BCT solutions in environmental and primary sector domains within the EU public sector. This uneven distribution may reflect both limited technological fit (e.g., BCT’s affordances are less directly applicable to marine ecosystems or food systems), and the relative scarcity of public sector experimentation in those areas.

To illustrate the diversity of applications, several analysed cases demonstrate how BCT contributes to specific goals. For instance, the Ukraine’s e-Auction 3.0 platform (PSTW-734) aims to support SDG 9 (Industry, Innovation and Infrastructure) by improving the state property privatisation process. Its decentralised and transparent structure reduces corruption risks and promotes fair competition, contributing to sustainable industrialization and innovation. Estonia’s Data Embassy initiative (PSTW-745) uses BCT for secure data management beyond national borders, reinforcing SDG 9 through enhanced cybersecurity and resilient infrastructure. The BIMChain project (PSTW-822) shows strong alignment with SDG 10 (Reduced Inequalities) by applying BCT to Building Information Modeling (BIM) to increase transparency and reliability in digital identity and project management while improving equity in information access, thereby supporting SDG 10. Additionally, the tokenisation of Real-World Assets (RWAs) initiative by Brickken (PSTW-2301) in Spain aligns strongly with SDG 17 (Partnerships for the Goals) by facilitating collaboration between technology providers and regulators within the European Blockchain Regulatory Sandbox. It strengthens partnerships that improve efficiency and transparency in asset management, fostering greater legal clarity and acceptance of decentralised technologies.

Taken together, these results show that BCT-based projects in the EU public sector most strongly align with SDGs linked to institutional innovation, digital infrastructure and cross-sector cooperation (see Figure 2). By contrast, SDGs related to environmental sustainability and primary-sector challenges exhibit weaker alignment, indicating areas where BCT’s relevance is either limited or still nascent in government practice.

4.2 Alignment by COFOG category

To contextualise how BCT is adopted across public administration functions, the use cases were classified according to the Classification of the Functions of Government (COFOG). Figure 3 presents the average SDG alignment score for each COFOG category, illustrating how BCT-based use cases align differently across policy domains. The results reveal clear concentration patterns, with some governmental functions showing strong associations with specific SDGs and others contributing only marginally.

The highest concentrations of alignment appear around SDG 9 (Industry, Innovation and Infrastructure), SDG 17 (Partnerships for the Goals), and, to a lesser extent, SDG 3 (Good Health and Wellbeing). These SDGs consistently receive the darkest values in the heatmap, indicating that BCT-based use cases most frequently support goals related to digital infrastructure, innovation ecosystems, and institutional cooperation. By contrast, lighter areas across SDG 2 (Zero Hunger), SDG 6 (Clean Water and Sanitation), and SDG 14 (Life Below Water) highlight that public sector BCT-based applications rarely target primary-sector or environmental-resource management functions.

Several sectoral patterns emerge. Projects in Education and Health display strong connections to SDG 4 (Quality Education) and SDG 3 (Good Health and Wellbeing), respectively. These cases often involve credential verification, academic record management, and secure health data exchange, reflecting a targeted use of BCT to improve information integrity and interoperability in these domains. An illustrative example in the education sector is the Micro-credentials pilot project ¹⁵ (PSTW-1969) which leverages the European Blockchain Services Infrastructure (EBSI) ¹⁶ to develop a presentation and verification platform that supports cross-university mobility. The initiative facilitates the cross-border issuance, recognition, and acceptance of digital educational credentials, enhancing trust and interoperability across higher education institutions within Europe. In the health sector, the EU-funded CUREX project ¹⁷ (PSTW-2148) provides another relevant case. It seeks to ensure the integrity and security of the risk assessment process, as well as the reliability of data exchanges among the diverse stakeholders involved, thereby strengthening trust and resilience in healthcare data management.

Recreation, Culture and Religion, together with Education, show relatively high alignment with SDG 11 (Sustainable Cities and Communities), suggesting experimentation with BCT-enabled services for cultural heritage, community services and urban data governance.

General public services and Economic Affairs exhibit the strongest alignment with SDG 9 (Industry, Innovation, and Infrastructure) and SDG 17 (Partnerships for the Goals), which might imply BCT’s relevance for digital infrastructure, administrative modernisation and cross-sector cooperation. SDG 8 (Decent Work and Economic Growth) and SDG 10 (Reduced Inequalities) also appear as recurring areas of alignment, reflecting BCT’s potential to enhance economic efficiency and institutional transparency.

In contrast, categories such as Housing and Community Amenities and Public Order and Safety show consistently low alignment across most SDGs (average scores between 2 and 3). Similarly, SDG 2, SDG 5 (Gender Equality), and SDG 14 remain underrepresented across nearly all COFOG categories, suggesting that these dimensions of sustainability are not yet integrated into BCT policy agendas in the EU public sector. Moreover, Environmental Protection shows a modest but notable pattern, with some alignment with SDG 13 (Climate Action) and SDG 15 (Life on Land). These cases often relate to traceability systems supporting emissions tracking, environmental reporting or resource stewardship, signalling an emergent, but still limited, role for BCT in environmental governance.

Figure 4 further disaggregates these results by showing, for use cases achieving a high alignment score (≥8), the distribution of evaluations across COFOG categories. This visualisation offers additional insight into how BCT use cases in the European public sector align with the SDGs. The results show a markedly uneven pattern, revealing both concentration areas and thematic gaps.

General Public Services and Economic Affairs dominate the landscape of high-alignment BCT applications. These two categories alone account for most items with strong SDG alignment, reflecting their broader implementation scope and the prevalence of BCT initiatives focused on administrative efficiency, transparency, digital identity, financial governance, and economic infrastructure. Within these categories, high scores are especially prominent for SDG 9 (Industry, Innovation and Infrastructure), SDG 17 (Partnerships for the Goals), SDG 8 (Decent Work and Economic Growth), and SDG 16 (Peace, Justice and Strong Institutions). This suggests that BCT deployments in these domains are perceived as highly relevant for improving institutional accountability, increasing the robustness of public sector processes, and enabling digital infrastructures that support innovation.

Other domains, such as Education, Health, Environmental Protection, Public Order and Safety, contribute fewer high-scoring cases but display distinct peaks: education-related initiatives cluster around SDG 4 (Quality Education) through credential verification and learning-data governance use cases, while health-oriented deployments show stronger links to SDG 3 (Good Health and Wellbeing), particularly in areas related to data integrity, patient record management, or epidemiological monitoring. Environmental Protection shows modest counts overall but includes notable alignment with SDG 11 (Sustainable Cities and Communities), SDG 13 (Climate Action) and SDG 15 (Life on Land), often linked to traceability systems supporting sustainability reporting or resource stewardship. Other COFOG categories such as Housing and Community Amenities, Social Protection, and Recreation, Culture, and Religion show even fewer high-alignment evaluations. Nonetheless, high scores in these areas tend to be associated with SDG 16 (Peace, Justice and Strong Institutions) and SDG 9 (Industry, Innovation and Infrastructure), reflecting BCT’s emerging potential in public safety records, urban service management, and social benefit distribution, though such applications remain limited and exploratory.

Overall, the results indicate that high-alignment BCT deployments in the EU public sector remain concentrated in domains related to institutional governance and economic systems, where the BCT’s core attributes (e.g., immutability, decentralisation, and auditability) most directly address existing administrative challenges. By contrast, areas such as health, education, social protection, and environmental protection display fewer but more specialised use cases, reflecting a growing yet still underdeveloped potential for BCT to advance the social and environmental dimensions of the SDGs. This asymmetric distribution underscores both the maturity of BCT adoption in certain public sector functions and the opportunity to extend experimentation to high-impact social and environmental domains that remain comparatively underrepresented.

4.3 Alignment by application type

Figure 5 presents the average SDG alignment scores across BCT-based application types included in the PSTW taxonomy, with a minimum threshold of 5 cases per category. The results reveal marked variations across application types in terms of SDG alignment, indicating that technical design choices and functional purposes may shape the sustainability relevance of BCT deployments.

Across all categories, SDG 9 (Industry, Innovation and Infrastructure) emerges as the consistently highest-scoring goal. Application types such as Improving Cybersecurity, Procurement Management, Registration and Data Notarisation, and Service Integration exhibit particularly strong associations, which might reflect BCT’s predominant use as an enabling infrastructure for secure data exchange, process integrity, and interoperability. An illustrative example is the EOGuard project ¹⁸ (PSTW-2145), developed by Guardtime in collaboration with the European Space Agency (ESA). The initiative establishes a blockchain-based security and trust service for Earth Observation (EO) data, ensuring data integrity and immutability while reducing the risks of accidental corruption or unauthorised modification. Certification and Validation Processes and Supporting Disintermediation Solutions also record high scores for SDG 9 although with slightly lower averages. These patterns underline the technology’s primary role in technological modernisation and the reinforcement of trustworthy institutional infrastructures.

Public policy innovation and governance-related applications show above-average alignment with SDG 17 (Partnerships for the Goals), which scored highly for Innovating Public Policy, Service Integration, Internal Support Processes, Data Sharing Management and Governance and Voting. This last application type also records the highest score for SDG 16 (Peace, Justice and Strong Institutions), highlighting BCT’s perceived potential to strengthen accountability, foster cross-sectoral collaboration and support trust, transparency, and institutional integrity. An example is the Participa.gov project ¹⁹ (PSTW-1310), a digital public participation platform developed by the Agência para a Modernização Administrativa (AMA) in Portugal. The platform supports participatory processes within public administration, enabling citizens to engage through simple, secure, and reliable technological solutions.

Application types linked to monitoring, traceability, and planning also show strong alignment with SDG 12 (Responsible Consumption and Production) and SDG 9 (Industry, Innovation and Infrastructure). This is particularly visible in categories such as Tracking of Goods and Assets and Prediction and Planning. These cases often involve provenance verification, supply-chain transparency or sustainability reporting systems; applications that leverage BCT’s auditability and data integrity features to support responsible production and resource management. An illustrative example is the Accudire project ²⁰ (PSTW-1635), which carried out the first shipment using fully digitised documents and blockchain-based processes, streamlining procedures and enhancing interoperability between the public and private actors involved. Accudire has since evolved into an innovative platform that enables large enterprises and SMEs operating in global supply chains to fully digitalise documentation and workflows through a paperless and environmentally sustainable approach, while safeguarding “Made in” certifications and strengthening protection against counterfeiting.

Moderate alignment is observed for application types such as Financial Management and Support, Payments and International Transactions, and Tracking of Goods and Assets along the supply chain, which exhibit more moderate but steady associations with these objectives. This suggests that BCT’s contribution to economic and supply-chain transparency is active but still developing within the EU public sector.

Environmental SDGs, including SDG 6 (Clean Water and Sanitation), SDG 7 (Affordable and Clean Energy), SDG 14 (Life Below Water), and SDG 15 (Life on Land), record the lowest alignment across all application types. This may indicate that BCT use cases targeting environmental sustainability remain relatively scarce or exploratory, with limited maturity or frequency.

Figure 6 shows the number of SDG alignment evaluations per goal that achieved a high alignment score (≥8) across different application types. The analysis reinforces the previous findings, revealing a clear concentration of high-scoring use cases in Certification and Validation Processes, Payments and International Transactions, and Public Policy Innovation. These categories together account for the largest number of strongly SDG-aligned initiatives, particularly for SDG 9, SDG 16, and SDG 17.

This reinforces the notion that BCT’s primary contribution to sustainable development in the EU context lies in building trustworthy digital infrastructures, reducing institutional inefficiencies, and facilitating secure data and value exchange. Meanwhile, emerging but less mature domains such as cybersecurity, internal management, and monitoring and evaluation processes are underrepresented among highly aligned cases, indicating areas with potential for further exploration and impact.

Overall, the results demonstrate that BCT-based applications in the EU public sector currently cluster around innovation, governance, and digital infrastructure goals, while social and environmental dimensions of sustainable development are less systematically targeted. This pattern underscores the opportunity for future policy initiatives to extend BCT experimentation toward green and socially inclusive digital transformation pathways, ensuring a more balanced contribution to the 2030 Agenda.

Figure 7 presents a Sankey diagram mapping the most referenced BCT-related application types on the left to selected SDGs on the right. This diagram emphasizes the distribution and intensity of alignment across goals. Each flow represents the relative strength of alignment from a given application type to an SDG. The diagram uses distinct colours for each application stream and for each SDG. As the diagram makes clear, most application types feed into SDG 9 (Industry, Innovation and Infrastructure) and SDG 17 (Partnerships for the Goals), while others additionally link to SDGs 1, 3, 4, 7, 8, 10, 12, 13, and 16.

4.4 Alignment by geographical extent

The analysis of average SDG alignment scores across different geographical extents (Figure 8) reveals several noteworthy patterns regarding how BCT-based use cases at varying administrative levels align with the Sustainable Development Goals. Across all extents, SDG 9 (Industry, Innovation and Infrastructure) and SDG 17 (Partnerships for the Goals) consistently emerge as the most strongly aligned goals. This finding underscores the centrality of BCT as both a technological innovation driver and a facilitator of multi-stakeholder collaboration, regardless of the scale of deployment.

Cross-country initiatives show the highest average scores, particularly for SDG 9 and SDG 17, followed by SDG 10 (Reduced Inequalities) and SDG 11 (Sustainable Cities and Communities). This suggests that BCT-based projects operating across national borders tend to address structural interoperability, cross-jurisdictional coordination, and large-scale infrastructure challenges, which naturally map onto these systemic SDGs. The stronger alignment with SDG 10 indicates that transnational BCT-based use cases may support harmonised access to services or more equitable data-driven processes across Member States. An illustrative example is the launch by the European Union Intellectual Property Office (EUIPO) of the first European blockchain-based platform designed to enhance services for public intellectual property institutions and their users ²¹ (PSTW-2603). By connecting national IP offices through a distributed ledger infrastructure, the system enables real-time updates, ensures the integrity and immutability of records, and strengthens interoperability across jurisdictions. Users can access authenticated histories of trademarks and designs, with additional functionalities under development, including downloadable blockchain-based certificates and an integrated IP Wallet.

Across all extents, alignment with SDGs 2 (Zero Hunger), 6 (Clean Water and Sanitation), 14 (Life Below Water), and 15 (Life on Land) remains consistently low. This reinforces the previous evidence that BCT-based applications in the public sector remain primarily oriented toward governance, economic, and infrastructural use cases rather than environmental or ecological domains.

5 Discussion

5.1 Contribution to research

Consistent with the results presented above, the findings broadly confirm earlier academic observations that BCT adoption in government tends to concentrate in administrative, economic and governance-related domains rather than in environmental or social policy areas. Similar to Thanasi-Boçe and Hoxha (2025), who found BCT research clustered around supply chains, energy systems, and socially oriented applications, our findings show that public sector use cases gravitate towards applications where data integrity, provenance, and auditability are central concerns. Likewise, Mulligan et al. (2024) noted that real-world BCT implementations remain fragmented and sector-specific; our results corroborate this fragmentation across COFOG categories, with only a few domains showing consistent patterns of strong SDG alignment.

Importantly, by grounding the analysis in a comprehensive EU dataset rather than thematic literature reviews or single-case studies, this study provides empirical confirmation of trends previously inferred theoretically or anecdotally. The systematic mapping reinforces the view that BCT functions primarily as an enabling infrastructure for transparency, institutional trust, and secure data exchange, while its proclaimed transformative potential in environmental and social domains remains largely untested in practice.

At a theoretical level, this study makes two contributions to the intersecting fields of digital governance and sustainability science. First, it provides large-scale empirical grounding for the conceptualisation of BCT as an enabling infrastructure for institutional trust and administrative transparency, a characterisation that has been proposed theoretically in prior governance literature (Ølnes et al., 2017; Wirtz, 2022) but rarely tested across a comprehensive, multi-country dataset of real-world deployments. Second, by demonstrating that LLM-based classification can operationalise SDG alignment assessment at scale, the study advances methodological discussions in sustainability science on how AI-assisted analytical tools can be applied to map and monitor technology-sustainability linkages. More broadly, the findings suggest that technology-sustainability alignment frameworks, typically developed from conceptual or private-sector perspectives, require empirical recalibration when applied to public sector contexts, where institutional mandates, governance constraints, and multi-level coordination dynamics shape adoption patterns in ways that differ substantially from market-driven settings.

While the analysis does not seek to explain why certain SDGs are more frequently aligned, given the scope of the study, the disaggregated results across COFOG categories, application types, and geographic extents generate pattern-level observations that can inform testable hypotheses for future explanatory research. In this sense, the study functions as a systematic empirical baseline for a domain where such evidence has been largely absent.

5.2 Alignment with EU digital and sustainability policies

These findings align closely with the European Union’s digital policy priorities, particularly the objectives outlined in the Digital Europe Programme (DEP), the Interoperable Europe Act (IEA), the European Blockchain Services Infrastructure (EBSI) and ongoing efforts under the European Digital Identity (eIDAS2) framework. Together, these initiatives reflect a coordinated effort to leverage emerging technologies, such as BCT, to enhance cross-border interoperability, trust in public services, and data-driven policymaking. The strong alignment with SDG 9, SDG 16, and SDG 17 observed in the dataset is consistent with this institutional focus on building the digital foundations of governance and supporting multi-level cooperation among Member States, public administrations, and private stakeholders. The prevalence of projects in general public services and economic affairs aligns with these policy directions, suggesting that EU-level initiatives are shaping the areas where governments perceive BCT to offer the greatest added value.

Similarly, the strong alignment with SDG 16 echoes the relevance of BCT for transparency, integrity, and anti-corruption, themes embedded in EU policy instruments such as the Open Data Directive ²² , anti-corruption frameworks, and digital government modernisation strategies. The clustering of highly aligned cases in domains such as procurement, public records, certification, and identity management reinforces the idea that BCT is primarily being used as a trust infrastructure within public administration, as suggested in prior studies (Martin-Bosch et al., 2022; Ølnes et al., 2017).

However, the limited alignment with SDGs related to environmental sustainability (SDG 6, 14, and 15) indicates a potential gap between EU environmental ambitions, such as the European Green Deal ²³ and the Circular Economy Action Plan ²⁴ , and actual BCT experimentation in the public sector. While environmental traceability and sustainability monitoring are often cited in the literature as promising BCT uses, their presence in real EU public sector deployments remains marginal. This resonates with previous reviews (Parmentola et al., 2022; Thanasi-Boçe and Hoxha, 2025) which highlight a mismatch between conceptual optimism and empirical evidence in environmental applications. Taken together, these findings suggest that current EU public sector BCT experimentation is more closely aligned with digital governance and institutional modernisation goals than with environmental sustainability objectives.

5.3 Policy and managerial implications

The findings carry concrete implications for three distinct stakeholder groups. For public administrations and project managers, the concentration of high-alignment use cases in institutional governance and digital infrastructure domains suggests that BCT is most readily adopted where its core affordances (i.e., immutability, auditability, and decentralisation) directly address existing administrative pain points such as fraud risk, information asymmetry, and limited interoperability. This highlights the importance of linking technology projects to sustainability objectives at the design stage, rather than treating SDG alignment as a post hoc attribution. Integrating SDG indicators into project templates and procurement requirements through frameworks such as EBSI and the PSTW classification system would enable more intentional and measurable contributions to the 2030 Agenda.

For EU policymakers and international organisations, the persistent underrepresentation of environmental SDGs (SDG 6, 14, and 15) signals an implementation gap that instruments such as the European Green Deal and the Circular Economy Action Plan have yet to bridge in the domain of public sector technology adoption. Policymakers should consider introducing SDG-oriented funding conditions and evaluation criteria that incentivise BCT deployments in underrepresented sustainability domains, particularly environmental governance, social protection, and gender equality. Cross-institutional coordination between digital government bodies and sustainability-oriented directorates would help ensure that BCT investment strategies are coherent with the EU’s broader 2030 commitments.

For blockchain developers and technology providers, the results identify both mature and underserved market segments within the public sector. The concentration of high-alignment deployments in general public services and economic affairs reflects established demand for BCT solutions in administrative efficiency, digital identity, and procurement transparency. By contrast, the underrepresentation of social and environmental SDGs points to underserved public sector needs where purpose-built BCT solutions could generate both measurable impact and institutional demand, particularly those exploring token-based incentive mechanisms that may reward sustainability-oriented behaviour.

6 Limitations and future research

6.1 Limitations of the study

Several methodological and empirical limitations should be noted when interpreting these results.

First, the analysis relies on project descriptions from the PSTW repository, which may not fully reflect the underlying objectives or operational realities of each initiative. As noted in the methodology, the dataset captures intentions and design features but does not offer information on actual implementation outcomes or long-term impact, limiting the ability to assess realised contributions to the SDGs.

Second, the LLM-based classification method has its own limitations. The model relies on project descriptions, which may present initiatives in a positive or aspirational way and may emphasise expected benefits more than actual results. Because of this, the model may assign SDG relevance based on claims made in the text, especially for SDGs linked to innovation, efficiency, governance, or partnerships. To reduce this risk, the final GPT-4o-based pipeline was not used without checks. A stratified 15% sample of cases was coded by human evaluators, agreement among human coders was assessed, and other automated approaches, such as keyword-based and supervised classification methods, were also tested during model development. These steps improve the reliability of the results, but they cannot fully remove the influence of how the original project descriptions were written.

Third, the dataset, although extensive, does not constitute an exhaustive census of EU BCT deployments. The PSTW collection is shaped by the availability of publicly accessible information and secondary data sources, potentially excluding non-publicised or early-stage initiatives. This may introduce selection bias, including possible overrepresentation of projects from administrations with stronger transparency practices, more active digital communication strategies, or greater engagement with EU-level reporting mechanisms. Similarly, certain project types, such as flagship digital government initiatives, may be more visible and therefore more likely to be captured than smaller-scale or local deployments. Moreover, as the dataset derives from the PSTW’s structured data collection framework, it reflects the scope and categories defined therein. Consequently, certain potentially relevant variables are not systematically captured, such as regional distribution, project scale, or the specific type of blockchain employed (e.g., public versus permissioned ledgers). These constraints limit the generalisability of the findings and caution against extrapolating the results to the entire universe of EU blockchain deployments or to other geopolitical contexts.

Finally, the SDG alignment scores should be read as measures of stated or perceived alignment, not as proof of actual SDG impact. A high score means that the goals and functions described in a use case are closely related to one or more SDGs. However, this does not mean that the project produced measurable social, environmental, or economic results. The method evaluates written project descriptions, not verified outcome data. For this reason, the findings should be understood as a structured estimate of SDG relevance, based on the available text, rather than as direct evidence of real sustainable development effects.

6.2 Future research directions

Several avenues for future research emerge from these findings and limitations:

6.2.1 Comparative global studies

Future work could compare EU BCT–SDG alignment patterns with those in other regions (e.g., Asia, Latin America, or OECD countries). This would help identify whether the European focus on institutional and infrastructure-related SDGs is unique or reflects global public sector trends.

6.2.2 Public versus private sector comparison

The present study focuses exclusively on public sector BCT deployments. Comparative research examining how private sector blockchain initiatives align with the SDGs, and whether the patterns differ systematically from those observed here, would contribute important evidence to debates on the relative roles of government and industry in driving technology-led sustainable development.

6.2.3 Longitudinal and outcome-based assessments

The present study analyses stated objectives at a point in time rather than realised outcomes over time. Future research could track project maturity longitudinally, evaluate implementation results, and assess whether SDG-aligned intentions translate into measurable improvements in transparency, efficiency, inclusion, or environmental performance.

6.2.4 Tokenomics and token-based incentive mechanisms

The PSTW dataset does not systematically capture whether individual use cases employ token-based mechanisms, such as tokenised assets, incentive structures, or digital value exchange instruments. As a result, this study cannot assess the specific contribution of tokenomics to SDG alignment. A small number of cases in the dataset, such as the Brickken tokenization of real-world assets (PSTW-2301) or the Rewatt peer-to-peer energy trading platform, suggest that token-based mechanisms may be associated with distinct sustainability outcomes, particularly for SDGs related to economic growth, partnerships, and clean energy. Future research should develop classification instruments capable of identifying and distinguishing tokenised from non-tokenised BCT deployments and examine whether token design features are associated with stronger or more diversified SDG alignment in public sector contexts.

6.2.5 Blockchain governance and architecture

The dataset does not systematically record the type of blockchain employed in each case (e.g., public, permissioned, or consortium ledgers). Future studies incorporating this variable could examine whether governance architecture shapes the nature and breadth of SDG alignment, contributing to a more granular understanding of how technical design choices influence sustainability outcomes.

6.2.6 Integration with complementary digital technologies

As many BCT initiatives coexist with AI, IoT or data space architectures, further research could explore how these combined technologies jointly support SDG progress, addressing calls in the literature for integrated socio-technical analyses.

6.2.7 Policy design and governance frameworks

There is scope to investigate how governance models, interoperability frameworks, and regulatory instruments (e.g., the AI Act, Data Governance Act, eIDAS2, and the Interoperable Europe Act) influence the adoption, direction, and sustainability contributions of BCT in the public sector.

7 Conclusion

This study provides the first large-scale empirical overview of how BCT deployed by public administrations across the EU aligns with the SDGs. By analysing 306 use cases through a structured LLM-based classification pipeline, the research reveals that BCT adoption in the EU public sector predominantly supports SDGs related to digital infrastructure, institutional trust, and cross-sector cooperation, namely, SDG 9, SDG 16, and SDG 17. Conversely, environmental and primary-sector SDGs remain weakly represented, pointing to untapped opportunities to leverage BCT for green and socially inclusive innovation.

More specifically, the analysis reveals that SDG 9 (Industry, Innovation and Infrastructure) records the highest average alignment score across all 306 use cases (7.58 out of 10), followed by SDG 17 (Partnerships for the Goals, 6.72) and SDG 8 (Decent Work and Economic Growth, 4.51). At the other end of the spectrum, SDG 6 (Clean Water and Sanitation, 1.93), SDG 2 (Zero Hunger, 2.04), and SDG 14 (Life Below Water, 1.99) record the lowest alignment, confirming that BCT’s current contribution to environmental sustainability in the EU public sector remains very limited. Disaggregated analysis further shows that cross-country initiatives achieve higher average alignment than local or national deployments, and that application types such as certification and validation processes, public policy innovation, and payments and international transactions generate the strongest and most diversified SDG alignment. These findings suggest that targeted investment in cross-border BCT initiatives and the expansion of current application types into environmental and social domains represent promising pathways for strengthening BCT’s contribution to the 2030 Agenda.

These findings contribute to academic and policy debates on the responsible adoption of BCT by identifying the domains where it already shows strong alignment with strategic public value objectives and the areas where its potential remains underexplored. The study also demonstrates the viability of LLM-assisted SDG mapping as a scalable tool for analysing large sets of public sector innovations.

While the analysis is limited by the descriptive nature of the dataset and by its reliance on stated intentions rather than verified outcomes, it establishes a solid empirical foundation for future research. Advancing this agenda will require comparative analyses across regions, qualitative investigations of implementation dynamics, and outcome-oriented assessments capable of determining whether SDG-aligned intentions translate into measurable sustainability effects.

Overall, the study suggests that BCT is emerging as a relevant enabler of trustworthy, collaborative, and innovation-oriented public services in Europe. With targeted policy support, clearer governance frameworks, and sustained experimentation in underrepresented sectors, BCT could play a more meaningful role in supporting the EU’s transition towards a more sustainable, inclusive, and digital public sector.

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Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fbloc.2026.1768217/full#supplementary-material

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Footnotes

Edited by: Enrico Ferro, Links Foundation, Italy

Reviewed by: Elisa Pautasso, Links Foundation, Italy

Atul Kumar Sahu, Guru Ghasidas Vishwavidyalaya, India

Footnotes

For example, the project Rewatt, website: https://www.metadata.cat/noticia/2691/rewatt-plataforma-comprar-vendre-energia-cbcat

Formal accreditation and recognition of academic credentials project: https://ec.europa.eu/digital-building-blocks/sites/display/EBSI/Formal+Accreditation+and+Recognition

Blockchain-based project for asylum seekers in Finland: https://www.technologyreview.com/2017/09/05/149330/how-blockchain-is-kickstarting-the-financial-lives-of-refugees/

The Digital Europe Programme (DEP) website: https://digital-strategy.ec.europa.eu/en/activities/digital-programme

The Interoperable Europe Act (IEA): https://eur-lex.europa.eu/legal-content/en/TXT/?uri=CELEX%3A32024R0903

The European Blockchain Services Infrastructure (EBSI): https://ec.europa.eu/digital-building-blocks/sites/spaces/EBSI/pages/447687044/Home

The European Digital Identity (eIDAS2) regulation: https://eur-lex.europa.eu/eli/reg/2024/1183/oj/eng

The European Digital Identity Wallet website: https://ec.europa.eu/digital-building-blocks/sites/spaces/EUDIGITALIDENTITYWALLET/pages/694487738/EU+Digital+Identity+Wallet+Home

Public Sector Tech Watch observatory website: https://interoperable-europe.ec.europa.eu/collection/public-sector-tech-watch

Latest data extraction: July 2025 (306 use cases). Dataset available at: https://github.com/ipsoeu/bc4sdgs/

United Nations Statistics Division, 2018. Classification of the Functions of Government (COFOG). United Nations, New York. Available at: https://unstats.un.org/unsd/classifications/Family/Detail/4

UNDP website: https://www.undp.org/

This model is hosted in the cloud on Microsoft Azure in the EU for the JRC with an opt-out clause on prompt analysis by third parties. It has a context length of 128k tokens.

3.3–70b-instruct, an open-weights model. It has a context length of 128k tokens, which allows it to work with long documents, and it runs on JRC’s own servers.

Micro-credentials EBSI pilot project website: https://ec.europa.eu/digital-building-blocks/sites/spaces/EBSI/pages/710119840/Micro+-+Credentials

The European Blockchain Services Infrastructure (EBSI) website: https://ec.europa.eu/digital-building-blocks/sites/spaces/EBSI/pages/447687044/Home

CUREX project: https://cordis.europa.eu/project/id/826404

EOGuard project: https://interoperable-europe.ec.europa.eu/collection/public-sector-tech-watch/eoguard-custody-earth-observation-data

Participa.gov project website: https://participa.gov.pt/base/home

Accudire website: https://accudire.eu/en/

More information: https://www.tmdn.org/network/-/euipo-connects-to-tmview-and-designview-through-blockchain

European legislation on open data: https://digital-strategy.ec.europa.eu/en/policies/legislation-open-data

The European Green Deal: https://commission.europa.eu/strategy-and-policy/priorities-2019-2024/european-green-deal_en

Circular Economy Action Plan: https://environment.ec.europa.eu/topics/circular-economy-topics/first-circular-economy-action-plan_en