Conference on Digital Government Research

Futuros possíveis de processos de inovação para o Poder Judiciário a partir de experiências formativas

João Guilherme de Melo Peixoto — 2025-05-19

This work aims to analyze senses and meanings related to the construction of continuing education processes designed with the objective of transversalizing the culture of innovation, creativity and public entrepreneurship in the Judiciary. For this, narrative interviews were carried out with actors from the Judiciary who participated in the lato sensu Postgraduate course “Innovative Jurisdiction beyond 2030”. Within the results obtained from the collected data, we found the presence of three macro themes, namely: a) meanings of the notion of innovation; b) dialogue between the field of law and the culture of innovation in the Judiciary; and c) perceptions about the effectiveness of the strategy for implementing innovation processes via training actions. Such aspects point to the need to structure training processes which point to the development of skills (whether individual, collective and/or organizational) which enable the actors of the Judiciary to reflect, produce and share knowledge, methodologies, approaches and other processes specific to current societies.

Improving Public Health Supply Chains

Ilka Corrêa De Meo — 2025-05-22

The National Pharmaceutical Assistance Policy (PNAF) in Brazil aims to ensure universal access to essential medications through primary care. To achieve this goal and reduce healthcare access inequalities, efficient health system supply chains are crucial. This study evaluates time series forecasting methods, specifically exponential smoothing (ETS) and autoregressive integrated moving average (ARIMA) models, to predict the demand for captopril, a widely used antihypertensive drug, in São Paulo’s Basic Health Units. Data on medicine consumption and demand from January 2018 to March 2023 were collected and analyzed to address current inefficiencies in demand prediction, compared through the Mean Absolute Percentage Error (MAPE). Results indicate that the ETS model achieved the best performance in captopril demand forecasting, with a MAPE of 2.26%, significantly improving on the 77.97% MAPE of the existing methodology. Holt-Winters seasonal models and ARIMA also demonstrated robust predictive capabilities, with MAPEs of 3.81% and 3.47%, respectively. This research highlights the potential of data-driven forecasting techniques, such as the ETS model, to optimize resource allocation, ensure medication availability, and improve service quality, providing a framework for future applications in similar contexts.

Transforming Justice

Fernanda Suriani — 2025-06-27

This paper examines Artificial Intelligence (AI) implementation and evolution in the Brazilian judicial system from 2021 to 2023, focusing on institutional framework, governance, and applications. Analyzing data from the National Justice Council's (CNJ) AI project dashboards, we identified patterns in project development, survival rates, and categorical shifts in AI applications. Our findings reveal a 238% increase in AI projects, yet with a high mortality rate; over 65% were deprecated by 2023.
The research indicates an evolution from basic data classification applications towards more sophisticated uses like procedural intelligence and user-focused services. While initial projects targeted efficiency, newer ones demonstrate transformative potential, including novel mediation and fraud detection. The study also assesses the regulatory framework (CNJ Resolution n. 615/2025) and its adaptation to emerging technologies like generative AI. Despite progress, challenges persist in the coordinated development and strategic implementation of AI systems. The paper concludes with recommendations for enhancing cross-court collaboration, establishing impact-focused metrics, and monitoring the new regulatory framework to ensure AI improves efficiency, transparency, and access to Justice, while considering risks like algorithmic bias, data quality, and accountability. These findings also provide valuable insights for other judicial systems undertaking similar transformations, highlighting the need for strong governance and strategic coordination for a successful AI integration.

Opportunities and Challenges for Management and Governance in Smart Cities in Brazil

Luísa Paseto — 2025-05-22

The inteli.gente platform is an adaptation and expansion of the Sustainable Smart City Maturity Model of the International Telecommunication Union – SSCMM-ITU and is the first step towards the formation of a Brazilian BIG DATA with customized information on the levels of maturity in digital transformation and sustainable development. The diagnoses and recommendations for the estimated maturity levels use AI and data science techniques for the analyses, predictions and estimates of the 5,570 municipalities, considering the diverse characteristics and specific needs of each Brazilian territory. The result presented on the Brazilian maturity level for digital transformation and development indicates a country between the planning level (3) and the alignment level (4) of its actions. For the sociocultural dimension, the diagnoses of the municipalities indicate the need for attention in their management and governance policies for digital inclusion and social inclusion in an equitable manner throughout their territory. For the economic dimension, the results indicate that Brazil already has a framework of management tools implemented that enable the development of digital transformation and a sustainable economy. The environmental dimension indicates that strong action is needed to improve basic infrastructure in sanitation, solid waste, among other topics for
the resilience of future generations. The result of the Brazilian maturity level for the institutional capabilities dimension demonstrates that municipalities should be concerned with data governance, training leaders for digital transformation, planning and elaboration of goals and plans, among other topics. The availability and use of the inteli.gente platform by managers and
public policy makers, using Artificial Intelligence (AI) tools, has made it possible to map and improve institutional public policies based on primary and secondary data from municipalities, promoting cooperation, exchange and the creation of innovative initiatives related to digital transformation and sustainable development in the public sector.

Government Data Science Teams

Hugo Augusto Vasconcelos Meideros — 2025-05-19

This paper presents a framework developed by Pernambuco’s Strategic Monitoring Data Science Team to design and implement data-driven solutions for monitoring public policies. Using an action research methodology, the study integrates data science, iterative development, and stakeholder engagement. Despite being major producers and consumers of data, governments still face significant challenges in applying data science for policy monitoring, including data quality issues, legal constraints, and institutional silos. Existing frameworks such as CRISP-DM, Scrum, and Kanban are either too technical or primarily focused on software development rather than the policy-driven decision-making required in government settings. The Strategic Monitoring Team was established within Pernambuco’s Secretariat of Strategic Projects, comprising a Chief Data Scientist as team leader, a Project Manager, three Data Scientists specializing in modeling, engineering, and visualization, and a Trainee. The team operates through an iterative five-step process: Diagnose, which involves meetings with stakeholders to identify policy issues; Plan, where internal discussions define solutions; Act, which includes the development of dashboards, reports, and applications; Evaluate, to review whether the solutions address policy needs; and learn, focusing on documenting findings and improving tools. To enhance their workflow, the team adapted Scrum methodology by incorporating policy research alongside software development, tracking projects via Notion, and deploying solutions using R and Shiny Proxy. The study highlights that traditional frameworks such as Scrum and CRISP-DM require adaptations to effectively integrate research aspects and government governance structures. By bridging data insights with decision-making processes, the team successfully balances software development, policy research, and institutional needs. The findings emphasize the necessity of specialized data science frameworks tailored for government applications, ensuring a structured yet flexible approach to strategic policy monitoring through data-driven
solutions.

Digital Platform Government in the Promotion of Brazilian Audiovisual Content

Lorena Abs — 2025-06-27

The paper presents the Brazilian Public Audiovisual Content Platform, an initiative by the Ministry of Culture that aims to democratize access to national audiovisual content, with a focus on cultural inclusion and diversity. The platform complies with Law 13.006/2014, which mandates the screening of national films in schools and adopts the principles of Digital Government as established by Law 14.129/2021, prioritizing citizen-centricity, social participation, interoperability, and integration with other public services. The study employed an exploratory evaluation, supported by a qualitative approach, for collecting and analyzing primary data. The research methodology incorporated document analysis, pilot testing, and representative groups from the platform's user base. Data collection initially involved reviewing official documents, including the Work Plan approved by the Ministry of Culture, compliance reports, public policy documents, and legislation related to Digital Government. The analysis highlights technological challenges such as data security and accessibility, as well as the need to reduce digital exclusion. It concludes that the platform represents progress toward building a more inclusive and transparent digital government, with the potential to inform future public policies in the cultural and digital domains.

Leveraging String Similarity Algorithms for Educational Data Validation

Débora Barbosa Leite Silva — 2025-05-19

Data validation is critical for ensuring the reliability of information in educational systems, particularly in the context of digital governance. In Brazil, fragmented student records across various governmental databases hinder the implementation of educational public policies that rely on massive, high-quality student data. One effective method for validating these records is cross-referencing data across different databases. However, textual data, such as student names, are often prone to errors, including misspellings. Applying overly strict validation rules may result in the exclusion of valid records, while too lenient rules may allow incorrect data to slip through undetected. This study addresses these challenges by proposing a new data validation methodology that uses the Levenshtein distance algorithm. The approach identifies an optimal similarity threshold by taking into account the capacity of the manual validation team since excluded students are manually verified as a subsequent step, allowing for a balanced solution. We applied this methodology to validate student data from the Sistema Gestão Presente (SGP), which manages around 7 million student records and integrated it with the Brazilian Federal Revenue database. Through two key experiments, we demonstrated how an optimal validation threshold could be determined by considering the manual validation team capacity. In this case study, we found an optimal 80% similarity threshold when the manual validation capacity is approximately 950,000.

Towards an empowered ‘Platform State’?

Gianmarco Cristofari — 2025-05-20

Over the last decade much of the scholarly discussion about the digital transformation of the state has focused on the notion of “platformization”. This term serves to refer to the way in which governments and public services are ever more strictly associated with the operation of various digital platforms, thus seemingly acquiring some of their properties. Despite this centrality of the notion of platformization of the state, to date there has been surprisingly little theoretical reflection about the underlying organizational logic of the “platform state”. Why is the state becoming “platformized”? Is it simply an attempt by government to update its functioning by absorbing the prevailing social logic of organization, as it has already been popularized by various companies; or is there something more structural and profound to this trend? We argue that in fact states and platforms – while pertaining to different categories and domains – share important organizational logics: an “ambient-making” power; a meta-organizational capacity; a centralizing drive; and most importantly a strong “infrastructural” power, to follow the terms of US sociologist Michael Mann. Using this concept we explain the reason why digital platforms appear to have progressively encroached on a variety of functions that tended to be typically state functions: functions that concern identification; the setting up of fundamental conditional operations of society; the affording of various “enabling” systems, lacking which individuals and
collective actors cannot operate. Hence, the convergence between governments and platforms is not just a “marriage of convenience”. Rather the process of platformization is for states an opportunity to reclaim some of their state capacity and practical power – and in particular infrastructural power – that they seem to have previously lost.

Game elements enabling citizens’ engagement

Budi Satrio — 2025-05-21

Gamification may foster citizen relationships with the government but can also result in a disinterest in participation. In the context of digital government, we do not know which game elements specifically contribute to citizen engagement. In this paper, we conduct an integrative study, drawing from existing literature on citizen engagement through gamification. We examined the citizens’ motivation to engage with the government, linked it with game elements explored in the literature, and finally exhibited how these elements could support or inhibit citizens’ motivation. Using self-concordance and civic engagement models, we investigated gamification focusing on individual experiences, both personally and as citizens. The findings of this research show a link of static game elements with external and introjected forms of motivation. In contrast, dynamic game elements seem more aligned with intrinsic and identified motivation. We develop a taxonomy outlining these relationships, enabling further research on game elements and their impact on citizen engagement over time.

Using Generative AI for Identifying Electoral Irregularities on Social Media

Sidney Moura — 2025-05-21

The increasing use of social media (SM) in political campaigns has raised concerns about electoral irregularities, such as unauthorized voter solicitation and the use of sound trucks. Monitoring and enforcing electoral regulations manually are time-consuming and prone to inconsistencies, highlighting the need for automated solutions. A major challenge in automating the detection of electoral violations is the lack of sufficient labeled data. Additionally, the effectiveness of Generative AI in addressing this issue remains underexplored, especially regarding its ability to create synthetic data and enhance detection accuracy. In this context, this study aims to assess the potential of Generative AI in identifying electoral irregularities on SM, focusing on two common violations in the 2024 Brazilian municipal elections: voter solicitation and the use of sound trucks. The goal is to evaluate whether synthetic image generation, combined with AI-based visual analysis, can improve the identification of such infractions. We first generate synthetic images using Imagen 3, Stable Diffusion, and FLUX, identifying Imagen 3 as the most effective in producing realistic and visually coherent images. Then, we test the ability of three AI models—Gemini 2.0 Flash, Llama 3.2 Vision, and PaliGemma 2—to detect electoral violations in both real and synthetic images. To enhance detection accuracy, we apply different prompting strategies, including basic, chain-of-thought, and detailed prompts. Our findings show that Gemini 2.0 Flash performs best, particularly when using detailed prompts. Also, synthetic images help mitigate data scarcity, improving model training and evaluation. Overall, the study demonstrates that Generative AI, combined with optimized prompt engineering, can significantly enhance the accuracy of detecting electoral irregularities.

Citizen’s interaction, perceived benefits, and effectiveness of open government data on trust in government

Hanim Astuti — 2025-05-22

The declining trend of trust in government has received significant attention among scholars in various fields, particularly in efforts to find ways to reverse this decline. This paper investigates the relationship between trust in government and open government data (OGD), through a proposed model that links trust in government and three variables, i.e., citizens’ interaction with OGD, citizens perceived benefits of OGD, and perceived effectiveness of OGD. Utilizing the dataset from Pew Research Center’s survey on public perceptions of OGD, we test the model using structural equation modeling (SEM). Our findings show that the three variables positively affect trust in government. However, while the three variables are significant, perceived benefits and effectiveness of open government data are more essential determinants of trust than citizens interaction with government data. This study contributes to understanding how open government data initiatives could increase trust in government, by suggesting practical implications. Nevertheless, this study uses 2014 dataset that might not be able to capture changes in society, such political, economic, social, and technological conditions.

Why broadband availability differs across states in the U.S.?

Hanim Astuti — 2025-05-26

The U.S. government has made various efforts to increase broadband access, even before the pandemic. However, there is still a significant gap in broadband coverage across U.S. states, indicating the persistence of digital divides. Previous research has focused on geographic and socio-demographic factors, often overlooking the role of state governments, including state administrative efforts. In this paper, we explore how the administrative capacity of states influences the coverage of four broadband technologies across states in the U.S. Using secondary data, beta regression is employed to explore the impact of state administrative capacities, i.e., broadband plans, grantmaking, broadband offices, broadband maps, and state regulations, on the coverage of cable, fiber optics, fixed wireless, and fiber/cable at urban, rural, and state levels. The findings confirm the dominance of cable, followed by fixed wireless, while fiber shows limited coverage. Infrastructure-focused broadband plans negatively affect fiber optics’ coverage, highlighting implementation challenges. Conversely, grantmaking positively affects fixed wireless but not fiber, highlighting a tendency toward cost-effective, faster-deployment technologies.

AI drifting and converting emergency policies

Francesco Gualdi — 2025-05-19

The impact of Artificial Intelligence (AI) on emergency policies has been widely examined in digital government literature, focusing primarily on AI’s role in policy design and delivery and on its effects on policy outcomes. However, limited attention has been given to how AI directly impacts emergency policies’ change, that is, in which ways AI reshapes and steers the policies it mediates. Drawing on Hacker et al. (2015) framework of institutional change, particularly the concepts of drift and conversion, this research provides a novel lens to understand policy change in emergency contexts. Drift occurs when policies remain formally unchanged but fail to adapt to evolving contexts, altering their effects. Conversion refers to the redirection of policies towards new purposes without modifying their formal structure. By applying this framework, the paper investigates AI’s dual role in changing emergency policies, both as a source of resistance to formal policy change and a catalyst for policy redirection. The research adopts an explanatory case study of Peru’s welfare policies during the COVID-19 pandemic, focusing on the use of the SISFOH AI system to allocate emergency subsidies. Findings demonstrate how AI changes the policies it mediates by drifting formal policy modification and enabling conversion by reshaping policy ends. This paper contributes to the digital government literature by highlighting AI’s ambivalent role in emergency policy change and offering fresh insights into the intersection of AI and emergency policies.

Integrating an Online Management System into Technical Schools

Suellen Lages — 2025-05-26

This article presents the implementation of the Unified Public Administration System (SUAP) in technical schools across the State of Mato Grosso, Brazil, as a key initiative in the state government’s digital transformation strategy. Developed in collaboration with UFMT, IFMT and SECITECI, the project aimed to modernize educational governance by replacing fragmented, manual processes with a centralized, cloud-based platform. By integrating SUAP into school administration, the initiative enhanced transparency, streamlined workflows, and standardized digital services across urban and rural institutions, reinforcing social cohesion and reducing regional disparities in access to technology. The project addressed critical challenges such as infrastructure limitations, data security, and resistance to change. Custom solutions were implemented, including improved Moodle integration and enhanced SUAP functionalities for certificate management and user permissions. A collaborative, agile approach guided the development process, ensuring that technical teams, policymakers, and educators worked together to build a robust and scalable system. Additionally, a comprehensive capacity-building program equipped staff and students with the necessary digital literacy skills to maximize system adoption. Results demonstrated significant impact, with 719 students, 124 technical staff, and 190 teachers actively using the system, alongside the migration of over 800 historical records. By aligning with the State of Mato Grosso Digital Strategic Agenda (2023–2027), this initiative exemplifies how subnational governments can leverage digital transformation to optimize public services, enhance institutional efficiency, and foster digital inclusion. The success of SUAP in Mato Grosso provides a replicable model for other regional administrations seeking to modernize governance and ensure equitable access to digital public services.

Are hybrid work arrangements in the public sector fair and equitable?

Maria Gintova — 2025-05-21

The COVID-19 pandemic has significantly transformed work arrangements and reshaped employees' expectations of their employers. In Canada's public sector, hybrid work, where employees alternate between office and home, has become the new norm. However, the fairness and equity of existing hybrid work arrangements remain understudied. For instance, in 2022, the Ontario Public Service (OPS) mandated three office days per week for all employees, but the latest OPS People Plan (2023-2026) lacks concrete commitments to hybrid work. This paper explores public servants' perspectives on the fairness and equity of hybrid work arrangements within the OPS. Specifically, it examines public servants' views on access to hybrid work arrangements, consistency in their implementation, and the impact of hybrid work on recruitment and retention. By analyzing Reddit posts from 627 OPS subreddit users collected in 2022 and 2023, the study addresses two research questions: 1) How do Ontario public servants interpret fairness and equity in the current hybrid work model? and 2) How can these interpretations inform potential changes in the Ontario Government’s approach to hybrid work? The findings reveal vivid discussions on hybrid work arrangements, highlighting concerns with the existing approach as well as the operationalization and implementation of the hybrid work. From a fairness and equity perspective, several key aspects emerged: the uneven burden of hybrid work, lack of consistency in its implementation and enforcement, and the impacts on employee recruitment and retention. The study concludes that significant changes are needed in the OPS approach to hybrid work, starting with a thorough analysis and subsequent incorporation of public servants' perspectives on fairness and equity. This could determine if the Ontario government remains competitive in the digital age.

Inteligência artificial como apoio à tomada de decisão no setor público

Camila Taciana Sandrini — 2025-05-21

O artigo apresenta uma Revisão Sistemática da Literatura sobre a adoção de soluções de inteligência artificial (IA) como ferramenta de apoio à tomada de decisão na administração pública, destacando como essa tecnologia pode contribuir para modernizar os processos de gestão governamental. O levantamento de 38 artigos sobre inteligência artificial aplicada à tomada de decisão destaca sua versatilidade em diversas áreas, incluindo governança, serviços sociais, saúde, meio ambiente, justiça e orçamento público. Na governança, enfatizam-se a transparência, a explicabilidade e a supervisão humana, essenciais para decisões automatizadas confiáveis. Serviços sociais enfrentam desafios éticos, como impactos no bem-estar dos trabalhadores e desumanização do atendimento. Na saúde, IA otimiza cadeias de suprimentos e resposta a crises, enquanto na justiça, melhora a análise de dados e a prevenção de crimes. Na operação de sistemas de energia e em sistemas ambientais o foco está na eficiência e precisão. Embora a inteligência artificial tenha um enorme potencial para transformar a gestão pública, seu uso requer uma análise criteriosa de questões éticas, governança e transparência. Problemas como viés algorítmico e ausência de supervisão reforçam a importância de regulamentações adequadas e de diferentes abordagens que integrem a tecnologia com a supervisão humana.

From Trust Antecedents to Trust Frameworks

Louise van der Peet — 2025-05-23

Companies and public agencies who are looking to improve their services can benefit from more data sharing. However, due to regulations and security concerns, data sharing between individuals, businesses and public agencies is complicated. There are many variables to consider in a multi-actor environment where actors with various roles and incentives look for legal and technical certainty. Public and private organizations increasingly acknowledge the need for multi-organizational agreements on data sharing standards. This results in the rise of trust frameworks to guide efforts towards trustworthy data sharing in an interorganizational setting. However, academic literature on trust frameworks is scarce, and we lack a systematic understanding of the factors that constitute trust in a multi-actor data sharing environment. The objective of this paper is to provide a systematic understanding of the antecedents of trust playing a role in trust frameworks. A two-stage approach is followed, starting with a systematic review of antecedents, followed by an empirical inquiry as verification. Our findings indicate a wide range of antecedents - including technological and organizational antecedents - can be considered.

Using ICT to Patch the Shortcomings of New Public Management in a Post-Communist Welfare State

Sebastian Sosnowski — 2025-06-30

New Public Management approach in the welfare sector led to outsourcing and disaggregation of the services, which makes it difficult to implement new ICT technologies into such context. In this paper, I analyse the case of Electronic Care System (ECS) implemented in selected municipalities in Poland. These municipalities carry different characteristics of inhabitants and service provision. Additionally, Polish welfare system is a case of transformative system which is a mix of diverse European systems. I analyse secondary data (documents, strategies), interviews and observations regarding the implementation of ECS. Based on that, I draw the main conclusions regarding how context of welfare provision impedes the successful implementation of the ICT within the public institutions. I argue that introduction of ICT in fragmented institutions needs to include diverse perspectives of stakeholders and take into account the values important for the system users. Especially, I focus on how diverse modes of care provision need to be mirrored in the systems, how political and managerial pressures make it more difficult for other actors to navigate through the change. At the end, I ask the question about organisational and cognitive costs of implementing innovations.

Advanced Leveraging of Government Data on Firms’ Vulnerability to Crisis Using Artificial Intelligence

Mohsan Ali — 2025-05-19

Government agencies possess large quantities of valuable data, which have to be leveraged to the highest possible extent, using the most advanced processing methods, in order to extract as much as possible the valuable knowledge they contain, in order to support future decisions, policies and programs. In this paper we develop a methodology for sophisticated advanced leveraging of data that government agencies possess concerning firms’ behaviour during recessionary economic crises as well as firms’ vulnerability to them, which is based on a combination of artificial intelligence (AI) techniques, both unsupervised and supervised ones. Economic crises are one of the most important significant challenges that market-based economies face, which has detrimental effects on businesses of most sectors. Governments employ diverse interventions, including extensive programs in order to mitigate the adverse effects of economic crises, which may include employment reduction, famine, public disturbance, and political instability. These government interventions, particularly the extensive economic stimulus programs during crises, can be rendered more efficacious by concentrating on the firms that are more vulnerable to economic crisis. In this direction the proposed methodology includes initially the use of unsupervised learning AI techniques (clustering) in order to identify based on the abovementioned government data the main typologies of firms with respect to the impacts of economic crisis they experience. Then it includes supervised learning AI techniques (classification) in order to predict based on these data the susceptibility/vulnerability of individual firms to future economic crises. Additionally, the authors present an initial implementation and substantiation (application) of the proposed methodology utilizing a dataset from the Greek Statistical Authority made available upon request, pertaining to 363 companies, data acquired during the Greek economic crises that occurred from 2009 to 2014. Satisfactory results were obtained from this first application.

Assessment of the LLM-based Chatbots on Student Engagement and Learning Outcomes in Afghanistan

Jawad Ahmad Haqbeen — 2025-05-19

The integration of Generative AI (GenAI) technologies, such as ChatGPT, into online education is accelerating; however, their effectiveness in under-resourced contexts remains insufficiently studied. This paper investigates the impact of a Large Language Model (LLM)-based conversational agent on student engagement and learning outcomes in Afghanistan, where access to formal education—particularly for women—is severely restricted or banned. We conducted an experimental study involving 80 undergraduate computer science students (40 male, 40 female) in Afghanistan, randomly assigned to control and treatment groups. All participants attended identical 50-minute online lectures followed by 40-minute post-lecture discussions moderated by a human instructor, and completed a follow-up self-report questionnaire. The treatment group additionally engaged in AI-facilitated discussions using a GPT-4-based chatbot during post-lecture discussion. Analysis of discussion logs and post-intervention surveys revealed that the treatment group demonstrated significantly higher participation rates, with more posts and replies, during post-lecture discussion and reported greater confidence in their understanding of the course material. These findings highlight the potential of LLM-based chatbots to enhance interactive learning and foster educational inclusion, particularly for marginalized populations in low-resource environments.

Move Fast and Break Things?

Nathan Davies — 2025-05-20

Governments depend on procurement to help them achieve their digital transformation goals. Historically, public sector technology contracts have overwhelmingly flowed to large technology firms. However, governments have begun to explore opening up the procurement process to GovTech startups to drive innovation. Yet, this policy goal has proved challenging to implement. This paper explores why this is the case by presenting the case study of GovTech startup procurement in the United Kingdom. By focusing on the role of temporal dynamics in shaping procurement processes and drawing on 32 primary interviews with stakeholders across the UK GovTech ecosystem and supplementary archival data, this study identifies how the financial, staffing, and strategic processes within public sector bureaucracies enact an erratic and unpredictable procurement rhythm. It further demonstrates the challenges startups face when encountering this rhythm, struggling to predict or synchronise with it. Startups who are successful face new challenges from managing multiple rhythms. While conventional discourse often frames this procurement challenge as a mismatch between the "slow" public sector and "fast" startups, this paper instead reveals the complex and contradictory rhythms that frustrate GovTech procurement.

Social media and deliberation in the period of COVID-19 crisis

Daniil Volkovskii — 2025-05-21

Deliberation is a basic term about reaching a decision through balanced discussion, which openly raises the issues of consensus and its achievement through communication. The current article aims at studying the quality of online deliberation between citizens and Russian authorities on social media in the conditions of global health crisis COVID-19. Indeed, the quality of online deliberation between citizens and authorities on public policy issues is traditionally explored in periods of social certainty and mainly in democratic contexts. However, when this problem is considered in times of crisis and out of democratic societies, there is a huge gap in political science. Indeed, studying the quality of deliberation in online sphere becomes more significant and simultaneously complicated in the context of the COVID-19 pandemic. To evaluate the quality of deliberation, we propose a methodology of content analysis based on the theories of democratic deliberation and cumulative deliberation as well. Also, we employ a medium-size case dedicated to discussing state measures of quarantine and self-isolation in the social network VK.com during March-May 2020 in Russia. These conversations were conducted on the state VK.com platform Stopcoronavirus.rf, which is the official information resource of the Russian Government on coronavirus control issues. In total, 5215 comments of both citizens and authorities were analyzed. As a result, the quality of social media deliberation between Russian authorities and citizens is described and assessed in such categories as participatory activity, (ir)rationality, argumentation, constructive politics, interactivity, (in)civility, (dis)agreement and striving for consensus. Generally, the paper contributes to a better understanding the phenomenon of deliberation in non-democratic societies like Russia, going beyond the Western liberal democracies where deliberation is investigated as one of the most important components in the process of making legitimate decisions. Also, our work shows how the digital interaction can be implemented in the conditions of COVID-19 crisis and whether the results of political dialogue between state officials and people on social media can be taken into consideration in the real process of public policymaking in non-democratic societies.

A Normal Form for Representing Legal Norms and its Visualisation Through Normative Diagrams

Diogo Sasdelli — 2025-06-03

Representing legal norms by means of an adequate formalism is essential for the development of legally compliant autonomous systems. The remarkable variety of both formalisation and implementation frameworks proposed during the last decades enables the development of relatively efficient formalisations over a wide range of applications. Notwithstanding, this abundance of frameworks also leads to some practical problems, especially with respect to the integration of – or the translation between – different frameworks. While more or less widely applicable meta-formalisms are already available, they are often too complex and counter-intuitive, thus being clearly closer to the technical implementation than to the conception phase of the formalisation process. As a complementary, more human-oriented solution to the problem, the paper at hand introduces and discusses a more intuitive normal form structure, which is based on elements of legal theory and aims at facilitating the interdisciplinary communication among the many partners involved in the process of developing law-abiding machines.

Rethinking AI Readiness

Lucia Mariana Galarreta Bolia — 2025-07-08

Standard indices and AI readiness criteria often do not adequately capture digital transformation's complex and context-specific dynamics in the public sector, especially in low and middle-income countries (LMICs). These tools typically provide decontextualized, static indicators that fail to consider historical processes and the evolution of local institutions. This
paper examines Argentina's experience with AI adoption in the public sector using the Digital Government Ecosystem (DGE) framework —a context-sensitive tool that emphasizes the interaction of institutional, organizational, and governance factors. Drawing on empirical data, the study analyzes how AI initiatives have emerged, evolved, and been influenced by both national and subnational dynamics. It argues that understanding AI implementation as a situated and evolving process is essential for developing more meaningful assessments and strategies in LMIC contexts. The findings aim to contribute to more accurate, locally grounded approaches to analyzing and guiding AI integration in public administration.

Comparing Machine Learning and an Expert System for Legal Document Classification

José Jorge de Queiroz Santos Filho — 2025-05-19

This study assesses the performance of machine learning models and a rule-based expert system in classifying legal documents, specifically in distinguishing relevant from irrelevant cases. The evaluated models include Random Forest, Naive Bayes, XGBoost, SVM, and Decision Tree, alongside an expert system developed by a State Attorney from PGE-PE. The datasets, representing Alvará, Arrolamento, and Inventário legal processes, contain labeled instances of legal cases. The models were assessed based on accuracy, precision, recall, and F1-score. The results suggest that while machine learning models—particularly Random Forest—achieve higher accuracy and precision, the expert system outperforms in recall and F1-score, ensuring that no relevant cases are overlooked. The choice between machine learning models and expert systems depends on the legal context, requiring a balance between efficiency (reducing false positives) and reliability (capturing all relevant cases).

Application of Design Thinking in Digital Transformation in Human Resources in the Public Sector

Iury Monte — 2025-05-20

The digital transformation of public sector organizations is often hindered by bureaucratic rigidity, inefficient processes, and resistance to change. This study explores how Design Thinking can drive innovation in the Department of People Management at the Court of Auditors, addressing these challenges through a user-centered approach. Using a mixed-methods methodology, the research combines qualitative interviews with people management leaders and quantitative surveys with employees to identify inefficiencies and co-develop solutions. Key pain points include complex leave request workflows, lack of integration with digital tools, and communication gaps. To tackle these issues, Design Thinking was applied iteratively, facilitating collaborative workshops, prototyping, and continuous stakeholder engagement to develop a more efficient, automated leave management system. This solution improved transparency, accessibility, and decision-making, reducing administrative burden and enhancing regulatory clarity. The findings indicate that Design Thinking fosters problem-solving, streamlines people management processes, and promotes adaptability within bureaucratic institutions. By embedding empathy, co-creation, and iterative problem-solving into digital transformation efforts, this approach enables sustainable innovation in public sector organizations. The study contributes to the broader field of digital government by presenting a replicable framework for modernizing people management practices. Future research could assess the long-term impact of these interventions and explore their applicability to other domains of public administration, ensuring continuous improvements in efficiency, service delivery, and user experience.

Generation of public value through the adoption of government blockchain networks

Milber Fernandes Morais Bourguignon — 2025-05-21

This paper analyses the generation of public value through the adoption of government blockchain networks by different entities of the Brazilian federal government. To this end, the theory of Public Value in Electronic Government is used, with the approach proposed by Twizeyimana & Andersson (2019) with six dimensions of analysis. The method is a multiple case study with the three Brazilian blockchain networks: RBB, RNDS and PIER, which are at different stages of development. The results indicate the governance is a common challenge identified, and exchanging information with other networks is seen as a way of learning and developing the own models. Indeed, the already implemented government blockchain networks (RNDS and PIER) generate public value in the six dimensions and that the RBB has the potential to generate public value in the same dimensions. Furthermore, the choice of blockchain technology was an efficient solution for PIER and RNDS when compared to other technologies available at the time. The RBB was created to be an infrastructure for the development of other blockchain artifacts, to later house applications using the same technology. Governance challenges and balance between participants are crucial aspects in the development of networks. While RBB, a top-down initiative (governance development prior to applications) seeks a stable balance, the hierarchical deployment of PIER and RNDS allows for faster progress of deployment and development of applications on these networks. The paper has limitations in analysing public value from the perspective of public managers and not from co-creation with citizens. As future research, we suggest approaching the cases from the perspective of innovation theories and an investigation of the blockchain ecosystem in government in Brazil.

Virtual Visions

Summer Boucher-Robinson — 2025-05-21

Metaverse technologies are rapidly emerging and providing innovative opportunities to both the public and private sectors. Despite technological progress, governments worldwide face challenges in keeping pace, resulting in a misalignment of technological capability and governance mechanisms. This research aims to assess the differences in European Union and United States metaverse governance approaches, focusing on how broader digital governance models are being extended into immersive technology domains. This assessment utilizes a qualitative exploratory document analysis and two expert interviews to identify the key governance mechanisms and thematic orientations shaping early policy responses. Despite actions that both the EU and the US are taking to establish metaverse governance models, explicit regulation of immersive technologies remains limited. However, both have existing strategies, regulations, and legislation on related technology topics, such as AI and data privacy, which are expected to directly and indirectly impact the development and management of the metaverse. Drawing on an existing geopolitical technology governance assessment model as a framework, this research upholds existing assertions that the European Union values risk management and user protections in its digital governance and regulation. In contrast, the United States takes two other approaches: the Silicon Valley techno-solutionist approach and the Washington D.C. business-focused laissez-faire approach. These broader digital governance cultures are reflected in how each actor is beginning to position itself with regard to immersive technologies.

Practitioners’ Perceptions on Human-Centered Design Techniques in Digital Government Development

Viviane de Oliveira Garcia Coutinho — 2025-05-23

This paper focuses on the application of Human-Centered Design (HCD) techniques to enhance the agile requirements engineering process within the context of Brazilian Digital Government. Providing a public experience that prioritizes digital platforms represents a significant opportunity to improve citizens’ quality of life by facilitating access to information and services. Our analysis is based on a case study conducted in a large Brazilian public company, where a survey was applied to assess the use of HCD techniques such as prototyping, usability testing, Design Thinking, personas, user journey mapping, UX Writing, and Plain Language. The survey results highlighted prototyping as the most widely used technique. There was a high perceived value for usability testing; however, barriers to its broader implementation may exist. Techniques such as persona creation, user journey mapping, and Design Thinking showed moderate usage, while UX Writing and Plain Language had low adoption rates. The adoption of these techniques may vary depending on team roles. Factors such as age group, role accumulation, and time within the company influence their application. The findings reinforce the need to expand HCD training, especially for underutilized techniques, to maximize their benefits within the agile requirements engineering process. This effort can contribute to improving project efficiency and enhancing the quality of digital services in the governmental context.

Use of AI tools in the Colombian Judiciary

Juan David Gutiérrez — 2025-06-30

This paper aims to answer three main questions regarding the use of artificial intelligence (AI) tools in the Colombian judiciary. First, what type of AI tools do judges and judicial staff in Colombia access and use? Second, how and for what purposes are these AI tools used? Third, do demographic factors (e.g., age, gender) influence how judges and judicial staff approach AI tools? This paper is based on three comprehensive surveys conducted in 2024. Two surveys conducted by the authors targeted participants in the course ”Artificial Intelligence for the Administration of Justice: Fundamentals, Applications, and Best Practices”, offered by the Universidad de los Andes and the Superior Council of the Judiciary (CSdJ). A total of 1,391 judicial staff members responded at the start of the course, and 824 responded at its conclusion. A third survey, conducted later by the CSdJ, gathered responses from 3,152 judicial personnel. Our analysis reveals that training significantly improved AI familiarity among judicial personnel—initially, 63% reported minimal knowledge, but after the 50-hour course, 85% claimed moderate to high familiarity. While approximately one-third of respondents initially used AI for work tasks, this increased to nearly half post-training. Over 80% of users accessed free AI versions, raising concerns about confidentiality as these platforms may share information with third parties. Judicial officials primarily employ generative AI for information searches and document writing, particularly for jurisprudence (59%), legislation (52%), and definitions (51%). This reliance on AI for information retrieval presents risks if outputs aren’t verified against reliable sources. Although age and gender disparities in AI familiarity exist, reported usage patterns show minimal demographic differences. These findings emphasize the importance of enhancing digital literacy among judicial professionals and inform our recommendations for developing appropriate regulations and guidelines governing AI systems in the justice sector.

GoViz

Larissa Guder — 2025-05-19

Public speech from government figures often describes relevant actions that can impact the population’s lives. However, most people do not have time and access to analyze and understand public speech. Such a scenario narrows the participation of the people in the main discussions, which leads to multiple misunderstandings. In this work, we propose GoViz, a tool that automatically produces visual representations to outline governmental speeches regarding the subject, its main actors, and how they connect to the discussion topics. GoViz processes natural language from speech transcriptions in a pipeline that identifies part-of-speech elements, named-entities, and the relation between persons, making speech content more accessible and insightful. Using publicly available data, we evaluate our tool in two different languages (Portuguese and English). The results demonstrate that the visualizations from both data facilitate understanding the speech content. Thus, our main contribution is to encourage the participation of citizens in parliamentary issues, allowing a simplified and visually engaging avenue to access long speeches and fostering improved communication between parliamentarians and the population.

Diversity in GovTech

Luca T. Bauer — 2025-05-20

This study investigates the potential role of diversity in shaping innovation outcomes within the GovTech sector, an emerging domain where startups collaborate with public administrations to drive digital transformation. While GovTech is positioned as a vehicle for more agile, inclusive, and citizen-oriented public services, its effectiveness hinges on the extent to which it mirrors the populations it serves. Grounded in theories of diversity management and diffusion of innovation, this research explores how the demographic composition of GovTech founders compares to public administration employees, the broader startup ecosystem, and the general citizenry in Germany. The study employs a mixed-methods approach, combining 108 expert interviews with GovTech founders and comparative analysis using secondary data from national datasets. It focuses on three diversity dimensions: gender, migration background, and socio-economic (labor vs. academic) background. The findings reveal substantial misalignments. GovTech startups are heavily male-dominated (85.7% male founders), starkly contrasting with the higher female representation in public administration (58.6%) and the near gender parity in the citizenry. Migration background is also underrepresented among GovTech founders (22.7%) relative to citizens (28.6%), though aligned with general startup trends. GovTech shows relatively strong socio-economic inclusivity, with 62.8% of founders from labor backgrounds, exceeding
both startup and citizen benchmarks. These demographic mismatches raise concerns about the representational legitimacy and inclusiveness of GovTech solutions, which may limit their relevance, adoption, and impact. Public administrations, while more gender-diverse, also exhibit gaps, particularly in migration and socio-economic representation, potentially compounding the dis-
connect between technology providers and end-users. The study proposes strategic responses, including inclusive procurement policies, support for diverse founders, and cross-sector alignment initiatives to strengthen equity in digital public services.

European urban strategic initiatives involving emerging technologies for addressing climate change

Manuel Pedro Rodríguez Bolívar — 2025-05-21

In the contemporary era, climate change (CC) has become a defining challenge and a wicked problem for society, particularly in urban areas, due to their direct experience of the impacts of climate variability and extreme events. This has led to a heightened focus on the strategic planning processes, which are now under pressure to develop long-term strategies and investments for CC adaptation at the local level. This includes the implementation of effective measures and smart initiatives to address CC. In this context, smart cities (SCs) are progressively adopting emerging technologies (ETs) that hold the promise of enhancing urban resilience. Nonetheless, this implementation should be grounded in the strategic smart initiatives previously delineated in the strategic document of these cities, a domain that has remained largely unexplored. Thus, the present study aims to examine how a sample of European SCs are planning strategic actions to address the CC challenge through the design and execution of smart initiatives. Particularly, we focus on the analysis of governance issues -the leadership of the smart initiatives (RQ1) and the departments involved (RQ2)-, the smart dimensions involved in the strategic actions (RQ3) and, finally, the use of ETs (RQ4) in the
different CC adaptation actions planned. The findings indicate fragmented governance, weak interdepartmental coordination, and minimal involvement. While some municipalities have dedicated sustainability departments, many initiatives lack centralized management. Although big data and AI play a key role in decision-making, the adoption of advanced technologies remains limited.

Serviços eletrônicos de governo, datafication e data justice

Luiz Claudio Mendes Vargas — 2025-05-21

Este artigo aborda o contexto dos casos em que o crescimento da disponibilidade de dados permite aos governos prover serviços a partir da identificação e análise automática dos beneficiários. Com o objetivo de entender como questões relacionadas a datafication e data justice estão sendo consideradas na implementação de serviços de governo eletrônico no Brasil, este estudo utilizou uma abordagem metodológica qualitativa baseada no estudo de caso do Auxílio Emergencial da COVID-19. Os resultados obtidos indicam que ainda há necessidade de evolução nos mecanismos para mitigar riscos e garantir aderência aos direitos básicos de dados, transparência, procedimentos justos e equidade nos resultados. Por não termos todos os conceitos relacionados aos riscos de desigualdade e injustiça de dados disseminados e endereçados entre os agentes públicos responsáveis pela implantação de serviços eletrônicos de governo baseados no uso intensivo de dados, o debate sobre exclusão digital se mantém relevante. Além disso. este artigo contribui para a literatura acadêmica com a apresentação de um modelo conceitual baseado no referencial teórico de datafication e data justice, aplicado a um caso real no Brasil.

How Could Public Libraries Empower Communities to Participate in Government AI Initiatives?

Zong-Xian Huang — 2025-05-23

Public libraries hold significant potential for advancing inclusive civic engagement in government Artificial Intelligence (AI) initiatives. Drawing on interviews with 34 staff members from three public libraries across the United States—Palo Alto Public Library (PAPL) in California, Queens Public Library (QPL) in New York, and Schaumburg Township District Library (STDL) in Illinois—this study examines the AI-related programs offered by these libraries, along with the benefits, costs, and challenges associated with designing and implementing these programs. Built on the purposes of increasing awareness of patrons about AI and fostering competencies of patrons in using AI tools, public libraries offer various AI-related programs that create notable benefits for their patrons and the libraries themselves. Moreover, when designing and implementing AI-related programs, challenges such as insufficient staff expertise and limited staff engagement, as well as the lack of a unified and comprehensive strategy to promote AI-related programs to the public, must be addressed. This study also discusses that public libraries currently focus on informing citizens rather than higher levels of civic engagement, such as collaboration and empowerment. However, we argue that public libraries already provide a strong foundation for promoting civic engagement in government AI initiatives by informing citizens about the fundamentals of AI and enabling them to explore specific AI tools and applications. Future studies can build on this foundation to develop actionable strategies that public libraries can use to achieve more advanced levels of civic engagement in government AI initiatives.

Applying Active Learning in Named Entity Recognition Corpora Expansion in Legal Domain

Rafael P. Gouveia — 2025-05-19

This work investigates the application of Active Learning methodologies for data annotation in Named Entity Recognition (NER) tasks mainly when used in documents from the legal domain in Portuguese. Its aim is to determine an algorithm able to improve the efficiency of the annotation process and reduce the human cost involved, without compromising the quality of the classifiers trained in these corpora. Three sample selection methods were explored: (i) Multi-Criteria Active Learning, using informativeness, representativeness, and diversity as selection criteria, (ii) Dynamic Selection Guided by Entity Volume, and (iii) Random Sentence Selection (used as a baseline for evaluating the other two). The study was conducted using the BERT model for classification, employing different amounts of labeled data for each approach (annotation budgets). The results show that, although Multi-Criteria Active Learning performed better in some scenarios, Dynamic Selection Guided by Entity Volume consistently showed good performance, especially for low annotation budgets, in addition to being computationally more efficient. Thus, the analysis of the results suggests that the volume of named entities is a good predictor for selecting informative samples. This study contributes to the Active Learning field by applying these techniques to modern language models and providing efficient solutions for reducing costs in data annotation for Named Entity Recognition.

What drives local governments’ digital transformation in Brazil?

Lizandro Lui — 2025-05-20

In the context of increasing demands for efficient and equitable public service delivery, digital transformation has become essential for local governments, particularly within federations marked by inequality. This study investigates the factors driving digital transformation in Brazilian municipalities—a country with significant regional disparities and varying administrative capacities. The objective is to identify which economic and technical-administrative variables influence the digital maturity of local governments. Using data from 4,265 municipalities collected in 2023, the study constructs a Digital Transformation Index encompassing technological infrastructure and digital service provision. Multiple linear regression models assess the relationship between digital transformation and variables such as fiscal autonomy, IT expenditures, bureaucratic quality, and mayors’ educational profiles. Results indicate that municipal revenue generation and IT spending positively correlate with digital transformation, while reliance on intergovernmental transfers is negatively associated. Additionally, better-educated civil servants and mayors are more likely to lead digitally advanced municipalities. However, when accounting for regional and population size controls, many of these associations lose statistical significance, underscoring the role of broader structural disparities. The findings suggest that economic and human resource capacity are important but insufficient alone; a more coordinated national strategy is necessary to reduce regional inequalities and support local digital transformation.

Integrating VR/AR and AI-Chatbots in the Public Sector

Raphael Palombo — 2025-05-22

Public administrations are increasingly confronted with demands for greater citizen engagement and a shortage of qualified professionals. The adoption of emerging information and communication technologies (ICTs) is often shaped by organizational factors such as resource availability, leadership, and interorganizational dynamics. As digital transformation accelerates, virtual technologies, particularly virtual reality (VR) and augmented reality (AR), offer promising opportunities to enhance administrative processes through immersive and augmented environments. However, the integration of these technologies remains complex and presents numerous applicational challenges. This study investigates the barriers to VR/AR adoption in the public sector, with a particular focus on organizational and adaptation-related issues. Additionally, it explores the potential of AI-powered chatbots to mitigate these barriers. To that end, a deductive thematic analysis was conducted on a sample of 104 VR/AR projects. The study further examines the synergies between VR/AR systems and AI chatbots. The findings provide a foundational understanding of the applicational barriers associated with VR/AR integration in public administrations, highlighting challenges related to infrastructure, human–computer interaction, system stability, financial constraints, and complexity. While AI-powered chatbots show potential in addressing several of these issues, the study emphasizes the importance of designing both technologies as complementary systems to enhance effectiveness, efficiency, and user experience.

The Impact of Data Orchestration on Data Value Generation in the Judicial Data Ecosystem

Felipe Fonseca Salerno — 2025-05-21

This study investigates the role of data orchestration in enhancing data value generation within the judicial data ecosystem, grounded in Resource-Orchestration Theory (ROT). Data orchestration is defined as a multidimensional construct comprising data strategy, data governance, synergy, and technological infrastructure. These dimensions collectively facilitate the integration and coordination of data resources, processes, and stakeholders to maximize data value. Guided by the principles of ROT, which conceptualizes data as strategic resources to be structured, bundled, and leveraged, this study emphasizes the importance of orchestrating data resources to enhance their value within the judicial data ecosystem, where diverse actors and complex systems interact, ensuring data is effectively utilized as a strategic asset. A quantitative methodology was employed, with a survey conducted among experts from Brazilian courts and councils. Regression analysis was used to evaluate the relationship between data orchestration and data value, revealing a significant positive effect (0.687, p < 0.001), with data orchestration explaining 45.6% of the variance in data value. These findings demonstrate that coordinated efforts to align data-related resources and practices significantly enhance the value generated from data within the judicial ecosystem. By operationalizing ROT in this context, the study provides empirical evidence of how data orchestration contributes to improving the strategic potential of data in data ecosystems. The research advances theoretical understanding of ROT in the field of data ecosystems and offers practical insights for improving data management and governance in judicial settings. Although limited by sample size, the study opens pathways for future research to explore additional dimensions influencing data value generation and to validate these findings in other institutional contexts, acknowledging that generalizability is constrained by the specific characteristics of the Brazilian judicial data ecosystem.

Automating Test Design Using LLM

Artur Raffael Cavalcanti — 2025-05-23

An efficient test process can detect failures earlier in software development, contributing to the quality of software produced by governmental entities and bringing the potential to improve government service delivery. Due to the high cost and the reduced resources available, the automation of the test activities plays a strategic role in improving testing efficiency. Designing test cases from user stories is a common approach to assessing the quality of a system under testing. This paper reports on the research, implementation, and evaluation of a tool that automatically generates system test designs from user stories with the support of Generative Pre-trained Transformer 4 (GPT-4) in the context of a public sector organization. The tool has been conceived to match the needs and particularities of the organization’s test process. Such a tool reads user stories from the Redmine tool, interacts with GPT-4 using a prompt that outputs test cases, and stores the automatically designed tests in the Squash TM test management tool. Organization test analysts stated that the tool produces good quality tests and reduces the effort to create tests. As a consequence, analysts can put more energy into other activities related to testing. Moreover, comparing the tests designed manually by test analysts with the tests designed by the tool shows that both have the same functional coverage. The paper discusses the impacts of the approach in the process, limitations, and related and future work.

Assessing the capability of open government data for process mining

Gyslla Vasconcelos — 2025-05-26

The growth in Open Government Data (OGD) availability over the last decade offers significant potential for promoting transparency and improving operational efficiency in government. OGD can support the identification of inefficiencies and the extraction of process models through Process Mining (PM) applied to public service tasks. Various OGD portals, maintained by federal and subnational governments, provide access to diverse public datasets that can be explored for these purposes. Applying PM to OGD, however, requires addressing key aspects such as the tabular nature of data, variability in quality and standardization, and the frequent lack of process context. This study proposes a method to classify and evaluate OGD datasets based on their relevance and potential for process discovery. The method was applied to data from the Brazilian Federal OGD portal (dados.gov.br) to investigate whether OGD can be effectively used in PM tasks to identify processes and bottlenecks. The research involved steps of data collection, selection, and evaluation. Datasets were classified based on their potential utility and suitability for transformation into event logs. The results showed that 24% of the sampled datasets were considered relevant for PM, with 23% in dated tabular format and 1% already in event log structure. Moreover, 52% of the datasets addressed public policies, suggesting the potential of PM to reveal inefficiencies in processes that affect citizens. These findings demonstrate that, with structured evaluation criteria, PM can be effectively applied to public data. This research contributes by presenting an empirical and replicable method to support the evaluation and preparation of OGD for PM appli- cations in digital government. The results reinforce the importance of adopting clear assessment protocols to broaden the use of OGD in understanding and improving public processes.

Assessing Challenges in the Implementation of Digital Services by the NUG

Kyaw Lwin — 2025-06-30

This research investigates the challenges encountered by the National Unity Government (NUG) of Myanmar in delivering digital services amidst the complex socio-political landscape shaped by the 2021 military coup. Employing a sociotechnical framework, the study examines the interplay of technical systems and social dynamics in NUG's initiatives across health, education, and financial services. Digital services such as Telekyanmar, Nway Oo University, and Spring Development Bank are analyzed as transformative tools for governance and public engagement. Despite their potential, these services face critical obstacles, including internet connectivity issues, cybersecurity threats, power shortages, resource constraints, and digital literacy gaps, particularly in rural and conflict-affected regions. The study also highlights the importance of inclusivity, with attention to ethnic and cultural diversity, emphasizing the need for localized solutions and multilingual accessibility.Using mixed-method research, the analysis incorporates in-depth interviews, surveys, and secondary data to capture diverse perspectives from stakeholders, technology experts, and the public. Findings reveal significant adoption barriers stemming from security concerns, trust issues, and lack of infrastructure. Moreover, the public's willingness to engage with NUG’s digital services is deeply influenced by
their perception of the government’s legitimacy, inclusivity, and responsiveness to marginalized communities. The study underscores the importance of building trust and enhancing public access to digital platforms through community-centered approaches, targeted digital literacy initiatives, and robust cybersecurity measures.By addressing these challenges, the research offers actionable policy recommendations to optimize NUG’s digital governance. It calls for investment in digital infrastructure, capacity-building programs, and international collaborations to support the sustainability and effectiveness of these services. The findings provide critical insights into how digital governance can serve as a tool for resilience, inclusivity, and legitimacy in the face of authoritarian oppression, advancing the broader goals of democracy and transitional justice in Myanmar.

Algorithmic fairness as sociotechnical system

Mortaza S. Bargh — 2025-05-19

Organizations and enterprises search for ways to exploit the vast amount of data that is produced by citizens, sensors, devices and administrative processes. Capitalizing on the produced data should be done responsibly by preventing, mitigating and managing undesired side effects such as violation of rules and regulations, human rights, ethical principles as well as privacy and security requirements. A key challenge in employing data, algorithms and data-driven systems is to adhere to the principle of fairness and justice. In this contribution we focus on the issue of algorithmic fairness, which itself can be framed as a sociotechnical system with interacting social and technical/formal subsystems. Information is a key construct of any sociotechnical system, where information creation and exchange can ease the opacity of interactions between the social and formal subsystems, and of interactions between the subsystems and the environment in which they operate. Based on literature, we categorize the types and flows of the information construct within the sociotechnical systems of algorithmic fairness in 7 categories. As such, the presented insights about the 7 categories of the information construct can form a common mental model whereby social and technical disciplines can inform each other systematically and align their views on algorithmic fairness.

A Generative AI approach for creating and validating simplified versions of government documents

Karine Alves — 2025-05-20

Abstract. In the context of Brazil’s re-democratization and the need for greater transparency in public administration, the 1988 Constitution established the right to access public information. However, the complexity of legal language, particularly in court documents, poses a significant barrier to understanding for the general public, especially given that only about 25% of Brazilians aged 25 or older have completed or are pursuing higher education. This study addresses this issue by leveraging generative AI models to simplify legal texts from the Court of Accounts of Pernambuco into plain language, making them more accessible to individuals with a high school education level. The research evaluates the effectiveness of two Large Language Models (GPT and Gemini) and five prompt techniques (Tree of Thought, COSTAR, Zero Shot, One Shot, and Meta Prompting) in producing simplified versions of 14 preliminary decisions. A total of 140 simplified texts were generated and evaluated using an 18-question questionnaire based on plain language principles, with scores generated by AI models and validated through human review. The results show that Gemini with the Tree of Thought technique achieved the highest average score (67.64), based on responses to the plain language questionnaire, while GPT with the COSTAR technique performed best in preserving essential information and achieving the highest readability scores (Flesch Reading Ease: 55.26). However, omissions of critical information were a common issue across all models, highlighting the need for human oversight. The study also found that GPT outperformed Gemini in evaluation accuracy, with lower Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) compared to human evaluations. Despite this, AI models tended to overestimate readability and comprehension, underscoring the importance of a hybrid approach that combines AI-generated assessments with human review. The findings demonstrate the potential of generative AI to reduce costs and improve accessibility to legal and governmental documents, while also emphasizing the need for further research to address limitations such as omissions, biases, and ethical considerations. This study contributes to the growing body of literature on AI-assisted text simplification and provides a foundation for future work in this area.

Context-sensitive measurement

Manuella Maia Ribeiro — 2025-05-21

Various organizations and researchers have developed Smart Cities Measurements (SCM) to monitor the advance of Smart Cities (SC) initiatives worldwide, yet there is no consensus about their impact on local governments. Local managers implement SC and SCM projects differently depending on their contexts, but few studies have analysed these measurement initiatives from local governments’ perspective. To address this gap, this paper aims to identify how municipalities use SCM and adopt indicators according to local context. Data were collected by in-depth semi-structured interviews with representatives from seventeen Brazilian cities, including different regions and population sizes. The results describe how local governments adopt measurement frameworks, expanding the literature on SCM.

Impacto social, econômico e ambiental da implantação de soluções de governo digital

Bernardo Campolina — 2025-05-21

Este artigo busca analisar os impactos da digitalização dos serviços públicos em amostra de serviços digitais disponibilizados pelo governo federal brasileiro. Foi desenvolvido um instrumento metodológico de avaliação, que permite a mensuração de impactos econômicos, sociais e ambientais da iniciativa de soluções de governo digital. Para tanto, foram simulados dois estudos de caso, a saber: Solicitação de aposentadoria por idade (Instituto Nacional do Seguro Social) e Obtenção de passaporte (Polícia Federal). As simulações realizadas indicam que a implementação do governo digital no Brasil possui impactos expressivos em termos econômicos, sociais e ambientais. Observa-se que a redução do tempo dedicado ao deslocamento e aos atendimentos presenciais é um fator fundamental na composição dos impactos, especialmente os de natureza econômica. Em se tratando dos impactos ambientais, verifica-se que a digitalização contribui para a redução de desmatamento e emissões de CO2, alinhando-se a políticas de transição verde. No entanto, cumpre destacar a necessidade de considerar contrapartidas ambientais, como o aumento de emissões relacionadas à maior demanda por armazenamento de dados e dispositivos mais avançados. Apesar das limitações, os resultados reforçam o papel do governo digital como uma ferramenta estratégica para a formulação de políticas públicas inclusivas, sustentáveis e baseadas em evidências, promovendo maior eficiência e impacto positivo na sociedade. Sugere-se aprimorar o modelo com variáveis adicionais, como idade, renda e modais de transporte, além de adaptar o cálculo do rendimento médio para diferentes perfis de usuários e serviços. A inclusão de custos relacionados ao consumo energético, segurança cibernética e gestão de lixo eletrônico também se mostra essencial para uma análise mais abrangente.

This article aims to analyze the impact of the digitalization of public services in Brazil. A methodological evaluation tool was developed to measure the economic, social and environmental impacts of the Digital Government Solutions initiative. For this purpose, two case studies were simulated: Applying for a retirement pension (National Social Security Institute) and obtaining a passport (Federal Police). The simulations carried out indicate that the implementation of digital government in Brazil has significant economic, social and environmental impacts. The reduction of time spent on travel and face-to-face services is a fundamental factor in the composition of the impacts, especially those of an economic nature. In terms of environmental impacts, digitalization contributes to reducing deforestation and CO2 emissions, in line with green transition policies. However, environmental trade-offs need to be considered, such as the increase in emissions associated with greater demand for data storage and more advanced equipment. Despite the limitations, the results reinforce the role of digital government as a strategic tool for formulating inclusive, sustainable and evidence-based public policies, promoting greater efficiency and positive impacts on society. It is suggested that the model be improved with additional variables such as age, income and transport mode.

Exploring generative AI effects on Korean civil servants’ performance

Sukwon Choi — 2025-05-23

This study explores the factors influencing civil servants’ perceptions of generative AI-assisted work performance, focusing on extrinsic and intrinsic motivations and the moderating role of organizational power, as measured by government level and organizational rank. Artificial Intelligence (AI) has emerged as one of the most influential technologies, driving transformation in both government and society. Generative AI, as a subfield of AI, has gained recognition for its capabilities to automate routine tasks, enhance decision-making, and improve work productivity. However, little is known about who perceives the positive effects of these tools on performance and why. Drawing on the notion that motivations affect work performance and the reinforcement politics model, this study analyzes survey data from 1,608 Korean civil servants collected by the Korean Institute of Public Administration (KIPA) in April 2023, when generative AI was still in its early stages of development. The survey targeted civil servants from central, provincial, and local governments to gauge their perspectives on generative AI-assisted work performance. This study employed partial least squares structural equation modeling (PLS-SEM), an appropriate method for predictive modeling and identifying key driving factors in complex relationships to investigate the connection between two types of motivation and perceived work performance. The findings reveal that extrinsic and intrinsic motivations positively influence perceived work performance, with intrinsic motivation having a more substantial effect. Also, extrinsic motivation significantly enhances intrinsic motivation, highlighting the dynamic interaction between the two constructs. However, the moderating effects of government level and organizational rank on the relationship between motivations and perceived work performance were not statistically significant. These results underscore the critical role of individual motivation in shaping perceptions of generative AI tools while suggesting that organizational power may play a less significant role in this context than previously anticipated. Theoretically, this study provides empirical evidence supporting the idea that motivations affect work performance by demonstrating the effectiveness of generative AI tools in public administration while challenging the reinforcement politics model. It challenges the foundational assumption of the model that organizational power makes a significant impact on the adoption and effectiveness of generative AI tools.

Unpacking Digital Public Infrastructures

Luca T. Bauer — 2025-06-30

Digital Public Infrastructures (DPIs) are an emerging concept for building foundational digital capabilities—such as digital identity, data sharing, and payments—designed and governed in the public interest to foster generative value creation. Although DPIs are increasingly promoted as instruments for enabling collaboration among governments, citizens, and organizations, the concept remains underdefined in both academic and policy discourse. This study addresses that gap by applying the Technology-Organization-Environment (TOE) framework and a grounded theory approach to analyze 143 academic and non-academic sources published between 2011 and 2024, including work from international organizations, think tanks, and philanthropic entities. We
offer three primary contributions: First, we define DPIs as socio-technical systems with modular and layered architectures, governed through public-private collective action to support value creation and multi-actor interaction at scale. Second, we develop a conceptual framework structured around technological, organizational, and environmental dimensions. This framework identifies governance architecture and functional modularity, stakeholder orchestration, and public-private governance, as well as policy context and public rationale, as critical characteristics of emerging DPIs. Third, we position DPIs as an evolution of digital infrastructure and platform models, reoriented toward public interest objectives. We conclude with a call for interdisciplinary research to examine the design, implementation, and governance of DPIs across diverse regional contexts. Emphasizing their potential to deliver inclusive, interoperable, and scalable infrastructure capabilities, we argue that DPIs offer a promising foundation for addressing complex societal challenges

Ensuring Data Quality in National Educational Databases

Abílio Nogueira Barros — 2025-05-19

This study investigates challenges in ensuring data quality within Brazil’s national educational database, the Sistema Gestão Presente (SGP), and proposes solutions. Reliable and integrated data systems are critical for evidence-based policymaking, particularly in education. The SGP, designed to centralize student attendance and enrollment data, faces issues such as inconsistent data entry, logical errors, and systemic reporting anomalies. To address these challenges, a data-driven methodology inspired by the DMAIC framework was implemented, focusing on defining problems, measuring and analyzing data inconsistencies, improving processes through tailored solutions, and monitoring outcomes for continuous quality assurance. Seven case studies illustrate the results of this approach. These include resolving inconsistent enrollment dates, limiting multiple active enrollments per student, and ensuring consistency between disenrollment justifications and active statuses. Further, systemic anomalies, such as inflated attendance rates and implausibly high class hours reported at state levels, were identified and corrected through validation rules, training initiatives, and auditing mechanisms. These interventions reduced data
inconsistencies, enhanced reliability, and improved system usability. The findings demonstrate how integrating validation mechanisms, improving data entry workflows, and fostering stakeholder collaboration can address large-scale data challenges. By ensuring the quality and integrity of educational data, the SGP enables more accurate insights into attendance patterns, dropout rates, and program effectiveness. These improvements lay the foundation for robust evidence-based policies and equitable educational outcomes across Brazil, highlighting the transformative potential of data quality assurance for public sector decision-making.

Crowdsourcing in Municipal Ombudsman Offices

Jean Zahn — 2025-05-26

Municipal ombudsman offices face challenges in managing increasing citizen demands and stimulating meaningful participation, despite legal frameworks guaranteeing citizen rights. Crowdsourcing presents a potential avenue to improve the efficiency of the Ombudsman office and the engagement of citizens. This systematic literature review (SLR) investigates the application of crowdsourcing in municipal ombudsman offices, synthesizing existing research to identify best practices, challenges, and research gaps. A comprehensive search of academic databases from 2010 to 2023 initially yielded 1590 papers. Following a rigorous five-stage filtering process, 24 relevant studies were selected for in-depth analysis. The findings reveal a growing trend of utilizing crowdsourcing primarily for feedback collection and complaint management, although its application in direct decision-making processes within ombudsman offices remains limited. While the literature reports benefits such as increased efficiency and faster problem resolution, significant challenges persist. These include digital inequality, which can exclude vulnerable populations; concerns about the credibility of citizen-submitted data; and institutional resistance to adopting new, crowdsourced approaches. This review indicates the need for further research into the long-term impacts of crowdsourcing on citizen empowerment and ombudsman office accountability. The study provides a valuable foundation for researchers and practitioners seeking to leverage crowdsourcing to strengthen municipal ombudsman services and promote citizen participation, emphasizing the importance of addressing these identified challenges to realize the full potential of crowdsourcing in this context.

Child-focused challenges in the digital transformation of government services

Makpor Mercy Erhi — 2025-05-21

The digital transformation of government services fundamentally reshapes how citizens engage with public institutions and services, creating new opportunities and challenges for inclusive governance in the digital age. Amongst the most critical yet often overlooked stakeholders in this transformation process are children, who represent a significant portion of the global population and the future drivers of digital innovation and civic participation. As digital platforms become central to service delivery, children’s unique needs, rights, and vulnerabilities must be explicitly addressed to ensure equitable access, protection, and empowerment. This paper examines the implications of government digital services for children in some selected countries. The paper focuses on governments’ role as stakeholders in shaping public services and the importance of contributing to digital literacy, safeguarding privacy, and promoting child-friendly participation mechanisms. Drawing on five-country case studies – Bangladesh, Brazil, Ghana, Sweden, and Timor-Leste - the paper highlights the challenges and opportunities associated with integrating child-sensitive approaches into digital governance. The cases provide insights into how digital government services can increase active citizenship and civic engagement among children and their families while addressing disparities in access and usage. The findings build on a collaborative study conducted in 2021 by the United Nations Children’s Fund (UNICEF) and the United Nations University Operating Unit on Policy-driven Electronic Governance (UNU-EGOV). The study underscores the transformative potential of child-sensitive digital government initiatives in promoting early civic participation and empowering marginalized communities. The analysis emphasizes the need for a nuanced understanding of age-specific requirements, improved data collection mechanisms, and a coordinated whole-of-government approach to digital transformation. By integrating child-sensitive practices into digital governance, children’s rights are not only safeguarded by governments but also spurs a generation of digital literates, active citizens who are empowered to impact their communities and futures. This paper calls for a concerted effort to prioritize children in digital governance strategies, ensuring that no child is left behind in the digital era. Key contributions include the identification of best practices in inclusive ecosystems, the articulation of a holistic framework for digital service delivery and online safety, as well as the enhancement of strategies for bridging digital divides for marginalized children.

AI-enabled co-creation for evidence-based policymaking

Nina Rizun — 2025-05-21

This study focuses on developing and validating the key parameters of Artificial Intelligence (AI) -enabled co-creation integrated into evidence-based policymaking. We critically analyzed prior research to ensure a participatory, data-driven, and iterative policymaking process. We identified essential parameters shaping AI-enabled co-creation processes in public sector organizations (PSOs), including legal conformance, sustainability, and ethics. The parameters were validated and refined through a workshop with experts from academia and technology organizations, contributing to the development of a conceptual model structured around four interconnected co-creation phases: 1) co-commissioning; 2) co-designing; 3) co-delivering; and 4) co-assessing. Our study contributes to both theory and practice. Concerning theory, it positions AI-enabled co-creation as a core institutionalized process within evidence-based policymaking rather than a standalone participatory practice. It also introduces a key conceptual distinction between digital co-creation, where digital tools facilitate participatory processes, and digital public service co-creation, where digital solutions are the co-creation outcomes. Concerning practice, the study provides a structured framework for integrating co-creation into policymaking, aligning AI-enabled mechanisms with four identified policy co-creation phases. The framework offers policymakers and public administrators actionable guidance on designing adaptive, stakeholder-driven, AI-supported policy solutions.

Emerging models of national competent authorities under the EU AI Act

Emanuele Parisini — 2025-05-22

This paper examines the emerging models of national competent authorities under the European Union's Artificial Intelligence Act (AI Act), providing novel insights into how different jurisdictions approach AI governance institutionalization. Through systematic analysis of official documents from early implementing Member States, we identify three fundamental dimensions that characterize distinct regulatory approaches. First, the organizational architecture reveals a spectrum from centralized to fragmented oversight models, reflecting different philosophies about coordinated versus distributed AI governance. Second, the institutional choices between leveraging existing regulatory bodies versus establishing new AI-specific authorities highlight contrasting approaches to building governance capacity and expertise. Third, the regulatory scope demonstrates a critical divide between horizontal and vertical oversight frameworks, with some jurisdictions pioneering hybrid solutions that attempt to balance specialized knowledge with coordinated supervision. Our methodology combines document analysis of legislative proposals, government resolutions, and administrative acts with a three-dimensional analytical framework examining degrees of centralization, institutional arrangements, and oversight models. The findings contribute to the theoretical understanding of AI governance by revealing how different jurisdictions interpret and operationalize regulatory requirements, balance competing institutional priorities, and address the complex challenge of overseeing AI systems. Furthermore, the analysis offers insights into the evolution of AI governance structures and contributes to the broader discourse on institutional design for emerging technology oversight. While our analysis is limited to early implementers and based primarily on formal documents rather than operational evidence, it provides a foundation for future research examining the effectiveness of different models, their evolution over time, and their impact on AI innovation and oversight. Future studies could benefit from comparative analyses of implementation outcomes, stakeholder perspectives, and the practical challenges of operationalizing these different governance frameworks.

Data-Driven Analysis for Improving Educational Policies

André Araújo — 2025-05-23

Data analytics can support evidence-based decision-making in public policies by enabling the identification of patterns, forecasting needs, and prioritizing actions. Consequently, data-driven analysis can aid policymakers in redesigning and enhancing educational policies, such as textbook distribution for public schools. However, there is no consensus on a structured approach for descriptive analytics in this context. This study presents a descriptive approach to textual data analysis aimed at improving policy implementation and monitoring, with a focus on effort, productivity, and quality of reviews produced by textbook evaluators. Through a case study, we apply natural language processing techniques to analyze thousands of answers to rubrics during the pedagogical evaluation of a public call for literary works under the Brazilian textbook program (Programa Nacional do Livro e do Material Didático - PNLD). The PNLD is one of the most extensive textbook policies, impacting millions of students. Our findings shed light on challenges related to the effort involved and the quality of written reports in the pedagogical evaluation process. Analyzing reports, which reflect some desired and undesired behaviors of evaluators, can offer policymakers insights for making informed decisions and improving textbook programs worldwide. Our descriptive approach to textual data analysis leverages insights to enhance transparency, inform improvements, and guide policy implementation through real-time monitoring.

The wallet demarcation problem

Bert Lukkien — 2025-05-26

Digital wallets are emerging as new tools that provide citizens with control over their personal data while allowing innovation in service delivery. Wallets promise various functionalities, from authentication, authorisation, and signing, to storage and generating qualified electronic attestations. Given the potential, policymakers and service providers face significant challenges in selecting, developing, implementing, and regulating digital wallets due to the lack of clarity about their characteristics. This paper focuses on this lack of clarity. Through a socio-technical systems theory lens, we developed a comprehensive taxonomy for classifying digital wallets. Our empirical analysis reveals a taxonomy of 47 characteristics in 14 dimensions. The contribution of this taxonomy is two-fold. Firstly, it can help develop a more precise theory on specific types of wallets. Secondly, actors in the field can use the taxonomy for more granular communication on wallet development and adoption challenges, standardisation efforts, and policy development.

Digital Public Service Quality (PS-DigQual)

Juliano Nunes Alves — 2025-06-30

This study introduces a multidimensional framework designed to assess Digital Public Service Quality (PS-DigQual) within e-government systems. The proposed framework integrates three pivotal dimensions: System Quality (QSt), Operation Quality (QOp), and Information Quality (QInf). QSt ensures a robust technical foundation through infrastructure reliability, navigability, and compliance with accessibility standards. QOp focuses on responsiveness, personalization, and user support to enhance service delivery. QInf emphasizes transparency, accuracy, and the timely availability of information, thereby fostering trust and accountability. Addressing gaps in traditional models such as SERVQUAL and E-S-QUAL, the framework adapts to the unique requirements of public digital services, where transparency, inclusion, and citizen engagement are critical. The research methodology is grounded in a systematic literature review and bibliometric analysis, spanning publications from 1990 to January 2025. This approach ensures a comprehensive theoretical foundation and identifies critical gaps in existing frameworks. The study further applies the PS-DigQual framework in practical scenarios, demonstrating that improvements in one dimension positively impact others, creating a cycle of continuous enhancement. Key contributions include a scalable analytical tool for policymakers and a robust foundation for further academic inquiry. The framework’s adaptability allows it to be tailored across different cultural and institutional contexts, with the potential for incorporating emerging technologies such as artificial intelligence and blockchain. By promoting efficiency, transparency, and inclusion, PS-DigQual represents a significant advancement in evaluating and improving digital public services. The study concludes with suggestions for future research, emphasizing the development of measurement scales and strategies to ensure sustainable public value in the digital era.

AI-Driven Innovation and Collaboration in Public Services

Ramon Chaves — 2025-05-19

Recently, governments and organizations have expanded their interest and efforts toward acquiring Artificial Intelligence-powered systems to support the delivery of public services. However, there is insufficient information in the literature to help us understand how different types of public services are supported by AI, particularly regarding aspects such as collaboration support and the innovation achieved within organizations. To address these literature gaps, we conducted a rapid review to identify types of AI applications, problem solved, government functions supported, their impacts on innovation in public organizations, and the collaborative arrangements they have fostered among various stakeholders. Furthermore, in this same scope, we also designed a taxonomy as an analytical framework to answer the literature review questions. The review found that AI in the public sector is mainly used for prediction, data visualization, predictive analysis, and automating repetitive processes, particularly in economic affairs, health, and public order. Governments develop AI solutions primarily for administrative and repetitive tasks. In this sense, there is potential growth for new AI adoption forms and public management innovations, benefiting public service delivery and society. These contributions aim to help researchers, public managers, and tech companies better understand and analyze the complex domain of AI in public services, enabling them to develop and responsibly implement new AI solutions in the future.

Developing a BI Solution for Public Process Monitoring

Rafael José Moura — 2025-05-20

The development of Business Intelligence (BI) tools is essential for improving the efficiency and quality of services in public and private organizations. However, public institutions, especially at the subnational level, often face challenges due to legacy systems that complicate effective data utilization. This study focuses on a subnational public institution, the Court of Auditors of the State of Pernambuco (TCE-PE), which previously relied on a dashboard with several limitations, including usability issues, data inconsistencies, and maintenance complexities due to its dependence on multiple SQL Server database views. This study presents the development of a new dashboard, designed using an agile methodology, to centralize data transformations within the BI tool. The proposed solution focuses on the Accountability process, aiming to enhance data consistency and improve performance monitoring. The development process was structured into four key phases: Problem Identification, Planning and Requirements Collection, Design and Development, and Validation and Testing, ensuring a systematic and iterative approach to address the institution’s needs. The new system utilizes Qlik Sense, eliminating dependency on SQL Server views and allowing real-time analysis through interactive dashboards. The solution overcomes prior limitations, providing faster, more accurate, and reliable analyses aligned with the institution’s strategic objectives. By improving flexibility, usability, and data reliability, this initiative not only serves as a reference for other subnational institutions in Brazil but can also be adapted as a model for organizations operating in diverse contexts worldwide.

Challenges for monitoring flexible work

Fernando Kleiman — 2025-05-21

Flexible work has become a trend since the pandemic emergency. All around the world, governments have increased the number of civil servants working in hybrid or full-remote work settings. This new landscape of work practices has raised several new challenges to public administrations, including monitoring work activities. Some governments support the idea that flexible work requires new monitoring methods. Instead of controlling timesheets, a new trend towards results management has emerged. Accordingly, new management information systems have been developed to support the management methods. This paper discusses challenges from data use through the new information systems for flexible work monitoring. Based on a Brazilian Federal government case, we raise new questions regarding the levels of formality of the data and its use. We conclude that flexible work information systems can produce more data regarding work practices. However, the level of formality in the use of the information produced may reduce the data availability to improve decision-making.

Caminhos rumo a uma Região de Fronteira inteligente Brasil-Argentina

Rosiane Alves Palacios — 2025-05-21

Cada vez mais as iniciativas de cidades e regiões inteligentes vem sendo pensadas a fim de conferir mais qualidade de vida para os cidadãos. A governança do espaço urbano é um elemento primordial ao desenvolvimento e gestão de cidades e regiões que almejam se tornarem inteligentes. Nas regiões de fronteira, que apresentam dinâmicas distintas das demais regiões dos países, desenvolver cidades e tornar regiões de fronteira inteligentes pode ser possível através da atuação conjunta dos governos subnacionais e da comunidade por meio da composição de uma governança binacional. Esse estudo de caso único teve por objetivo entender a motivação e o processo de criação de uma região de fronteira inteligente (RFI) no contexto latino-americano através da análise das iniciativas e resultados de uma rede formal de governança binacional localizada na fronteira Brasil-Argentina. Foram entrevistados 23 atores da governança e analisados diversos documentos. A motivação para criar uma governança binacional está relacionada a articulação e instrumentalização das ações de desenvolvimento planejadas em conjunto para a região de fronteira. As ações e iniciativas envolvem infraestrutura, inovação, segurança, tecnologia, educação, empreendedorismo e turismo. Com um considerável histórico de ações de desenvolvimento, a região estudada teve avanços em alguns projetos e ações, porém, foi só com a presença de uma governança binacional que muitas das ações planejadas puderam começar, de fato, a sair do papel. As ações de articulação se mostram indispensáveis para operacionalizar as iniciativas planejadas. O capital social e as redes que a governança movimenta são motrizes para a realização das ações e projetos inteligentes.

Wind of Change or Just Another Digitalization Breeze?

Ina Jäger — 2025-05-23

Digital transformation (DT) is a critical challenge for public administration, requiring municipalities to modernize services while overcoming bureaucratic inertia and workforce resistance. Hence, many German states have recently invested in municipal digital change agent (MDCA) initiatives (kommunale Digitallotseninitiativen) to facilitate and accelerate the DT process within municipalities. However, the effectiveness of such initiatives remains underexplored, as public sector constraints differ from those in private organizations, and due to their novelty. This study adopts a case study design using interviews and document analyses to examine the effectiveness and potential of MDCA initiatives. The findings indicate that the success of digital change agents is contingent on clearly defined roles, effective communication strategies, and adequate resource support. The findings highlight key drivers of success, including digital capabilities, appointing dedicated digitalization staff, fostering proactive employee initiatives, participatory leadership, proactive communication, (re)building trust, and personal benefits. However, several challenges impede MDCA’s effectiveness, such as unclear role definitions, insufficient training, lack of assigned responsibilities and communication, resource scarcity, and inadequate leadership support. Structural obstacles, such as low prioritization of digitalization, absence of incentives, and resistance from tenured employees, further restrict progress. The study derives four propositions regarding the effectiveness of MDCA initiatives and DT enhancement in public administration: Clearly defining the MDCA role and responsibilities, assigning DT responsibilities to managers, increasing visibility and prioritization of DT, and introducing incentive mechanisms to foster engagement. These insights contribute to the literature on DT and change management in public administration, highlighting the need for structured frameworks and accountability measures. While MDCAs can act as catalysts for digital change, their effectiveness depends on strategic alignment, leadership commitment, and adequate resource allocation.

Factors Influencing the Potential Adoption of Social Media for Citizen-Based Monitoring in South Africa

Lesedi Senamele Matlala — 2025-06-30

Social media platforms have globally transformed governance, serving as vital tools for real-time communication, transparency, and public engagement. These platforms are widely used in South Africa for government-citizen communication and engagement. Still, their application in citizen-based monitoring (CBM)—a participatory governance mechanism that enables citizens to monitor public service delivery and hold governments accountable—remains unrealized. Despite South Africa’s relatively high internet penetration rate of 68% and widespread social media adoption, systemic, institutional, and socio-economic barriers hinder its use for CBM. This study explores the factors influencing the potential adoption of social media for CBM in South Africa, offering insights into the opportunities and constraints shaping this emerging governance tool. Using a mixed-methods approach, the research incorporates qualitative data from interviews with government officials, media representatives, and civic organizations alongside quantitative findings from a citizen survey. The study identifies critical barriers, including unequal access to digital infrastructure, limited digital literacy among citizens and government officials, the absence of policy frameworks for social media governance, and socio-economic disparities perpetuating a digital divide. Moreover, trust deficits between citizens
and government institutions present significant challenges to adopting social media for participatory monitoring. However, the research also highlights enabling factors, such as growing digital adoption, isolated cases of innovative practices, and an increasing recognition of social media’s potential to enhance governance accountability. This study contributes to the discourse on digital governance by examining the factors influencing social media adoption for CBM in South Africa. It provides actionable recommendations, including investing in digital literacy programs, strengthening infrastructure, and fostering trust through participatory policy frameworks. By contextualizing South Africa’s experience within the broader African governance landscape, the research lays a foundation for future strategies to harness social media’s potential in bridging the gap between citizens and governments through monitoring and accountability initiatives.

Enhancing Open Data Findability

Umair Ahmed — 2025-05-19

Metadata is essential for improving the discoverability and findability of datasets. According to the European Data Portal (EDP), Europe’s largest open data portal, keywords and categories alone contribute to 60 percent of a dataset’s visibility. Given that datasets can have highly variable and complex contexts, we propose leveraging the power of Large Language Models (LLMs), specifically T5-small and T5-large, to generate these metadata. In our study, we used EDP as our case study. We obtained 60,000 datasets from EDP and undertook thorough data cleaning and transformation. This process yielded 3,131 datasets for keyword extraction and 2,790 datasets for category extraction, ready for model fine-tuning. The base versions of T5-small and T5-large initially struggled to produce keywords that were representative of those generated by humans, resulting in F1 scores of only 0.0455 and 0.1051, respectively. However, fine-tuning significantly improved their performance, achieving an F1 score of 0.4538 for T5-small and 0.6085 for T5-large. A similar pattern was observed in category extraction. The base T5-small and T5-large models had F1 scores of only 0.1222 and 0.3326, respectively. In contrast, the fine-tuned models produced F1 scores of 0.6284 and 0.8322, respectively. Notably, T5-large produced keywords similar to those generated by humans in over 60% of cases, and its category predictions matched human-generated ones in over 80% of cases. This highlights the potential of using large language models (LLMs) for generating human-like metadata, thereby significantly enhancing data findability and usability across various applications.

Managing AI risks in the Public Sector

Boniface Ushaka Adie — 2025-05-28

Ensuring organisations are safe from cyber-attacks requires the contribution of every staff member and this also applies to AI risk mitigation. Organisations must assess and implement strategies that ensure AI risk mitigation is not just the responsibility of the cybersecurity team (who are always in short supply), but the entire organisation from the front-line staff who need to classify documents correctly, to the cybersecurity engineers who implement technology solutions to mitigate risks, and top management who drive and implement effective AI strategies, policies and investment prioritisation. In this study, we examine how the distributed digital leadership (DDL) framework can be used to enable agencies across government to mitigate AI risks in the public sector. We conducted semi-structured interviews with cybersecurity practitioners from public sector agencies and determined that AI risk mitigation is indeed everyone’s responsibility – spanning people, process, technology and data controls. Using the distributed digital leadership (DDL) framework, we provide actionable suggestions on how collective, and collaborative risk mitigation strategies can be implemented across the public sector by making everyone competent in their respective job role responsibilities. We suggest that a well-aligned DDL can help cushion the skills shortage risks in cybersecurity and the overall management of AI risks in the public service.

Breaking Tech Monopolies

Jan Westermann — 2025-05-22

The growing dominance of large technology companies in Europe’s digital markets raises concerns about innovation concentration, limited competition, and reduced technological sovereignty. Public procurement represents a powerful yet underutilized instrument to address these dynamics by enabling smaller firms to compete, innovate, and scale within critical sectors. This study examines how public procurement can strengthen innovation capacity and economic diversity in the European information and communication technology sector. Focusing on the participation of startups and small businesses, we provide large-scale empirical evidence on structural barriers and market concentration in cross-border procurement practices. Our study
reveals that public procurement systems often reproduce existing power asymmetries, despite policy ambitions to foster inclusivity and competition. Our findings highlight the significance of procedural complexity, limited outreach, and insufficient institutional capacity as key obstacles to startup participation. Moreover, we show that small and medium sized companies are far from homogeneous, necessitating targeted policy responses rather than uniform support measures. By framing startup inclusion as a systemic condition for innovation and digital sovereignty, the study contributes to ongoing theoretical debates on demand-side innovation policy and strategic governance. It also offers actionable insights for policymakers and procuring agencies aiming to design inclusive, innovation-oriented procurement ecosystems. In doing so, the study advances the academic discourse on public procurement and provides practical insights to support a more competitive and resilient European ecosystem by leveraging public procurement volume.

Flying chairs, heated takes

Gabriela B. Kurtz — 2025-05-26

The 2024 São Paulo mayoral election sparked intense political discourse, particularly following a highly publicized altercation during a live debate on September 15. The incident, in which candidate José Luiz Datena struck Pablo Marçal with a chair, led to widespread discussion on social media, particularly on YouTube. This study investigates the dynamics of online discourse surrounding this event, focusing on audience engagement and sentiment across five major YouTube news channels: UOL, Folha de São Paulo, CNN Brasil, Poder360, and Itatiaia. Using a discourse analysis approach adapted from Teixeira et al. (2018), we collected and categorized 500 top-ranking YouTube comments, classifying them into four primary categories: Humor, Support, Criticism and Protest, and Neutral. A second layer of analysis further refined support and criticism, differentiating between pro-Datena, pro-Marçal, and general political dissatisfaction. Our findings reveal that humor was the dominant response across all platforms, suggesting a tendency toward memefication and satire in Brazilian digital political discourse. However, significant polarization was observed, with Datena receiving both overwhelming support and the highest level of criticism across outlets. Media framing influenced audience reactions, as outlets with in-depth coverage fostered broader critiques, while those with shorter, sensationalist clips amplified polarized sentiments. This study contributes to research on political communication and social media discourse by demonstrating how digital platforms mediate political controversies and shape public perception. The results highlight the role of algorithmic content curation in reinforcing ideological divides and fostering emotionally charged interactions. By offering a systematic analysis of audience reactions, this study provides insights into the evolving nature of digital political engagement in Brazil and lays the groundwork for future research on media framing and discourse analysis in online environments.

The Role of Regulatory Frameworks in Shaping E- Governance

Zoran Jordanoski — 2025-05-23

As digital transformation accelerates globally, the quality of national regulatory
frameworks has become a key determinant of effective e-governance. This paper investigates how regulatory maturity influences the development and implementation of digital government initiatives across eight countries. It introduces a three-tier classification: advanced, moderate, and early-stage, based on the scope of legal frameworks, operationalisation of digital enablers, and integration into public service delivery. Countries such as Belgium, Estonia, and Singapore demonstrate that coherent and enforceable legal ecosystems when paired with institutional coordination and technical infrastructure, achieve high digital governance performance. By contrast, fragmented frameworks constrain implementation and trust. Using cross-case comparison and internationally recognised indices (e.g., EGDI, OSI, EPI, GCI), the study validates this classification and identifies recurring barriers such as regulatory lag, institutional misalignment, operational and infrastructure gaps, and societal mistrust. The findings confirm that while legal maturity is foundational, institutional capacity, technical readiness, and public engagement are critical for inclusive and resilient digital transformation.

Assessing rule-based document segmentation and word normalization for legal ruling classification

Giliard Almeida de Godoi — 2025-05-19

The Brazilian judiciary has shown promising interest in applying Natural Language Processing (NLP) techniques to various legal tasks. One such application is classifying legal rulings by the topics of recurring appeals. This study investigates two key strategies for preprocessing legal documents, drawing on insights from legal domain experts: whether using specific sections of the document is more effective for legal ruling classification than analyzing the entire document, and which expressions can be normalized to standardize the document vocabulary. The experimental results indicate that combining normalization preprocessing with the extraction of the judge’s manifestation section yields better performance, as measured by the F1 score. Additionally, we demonstrate how the Jaccard similarity index provides valuable insight into the impact of the preprocessing pipeline on the TF-IDF feature extraction method and, by extension, on document representation. This paper underscores the importance of leveraging domain expertise to guide an optimal set of preprocessing operations.

Brazilian Federal Institutions as Intermediaries

Joel Lima-Júnior — 2025-05-20

The integration of Open Innovation (OI) and Digital Transformation (DT) is relevant in the public sector, particularly in developing countries where resource constraints demand innovative approaches. OI fosters collaboration between governments, businesses, academia, and civil society, enabling the co-creation of digital solutions that enhance public service efficiency and transparency. In this context, intermediaries play a fundamental role in bridging technical capabilities and institutional needs, facilitating policy implementation, and overcoming cultural and financial barriers. However, while OI and DT have been studied independently, little research has examined how intermediary-driven OI influences the digital transition in government settings. This study investigates the role of federal public institutions as intermediaries in Brazil’s OI-driven DT efforts, analyzing how they facilitate innovation adoption at the state and municipal levels. Through a case study of two federal-level institutions, the research identifies key mechanisms by which intermediaries promote digital integration and examines the challenges they face, including budget limitations and resistance to change. The findings identify the strategic role of these institutions in mitigating administrative and legal barriers and in fostering cross-sector collaboration.

Multi-level Collaborative Governance Framework for Designing Accountable AI Systems for Emergency Management

Yu-Che Chen — 2025-05-21

This paper addresses a gap in the AI governance literature in understanding collaboration between national governments and tribal nations in governing AI systems for emergency management. This conceptual work develops and presents a governance design framework for accountable AI systems to fill the knowledge gap by drawing from the fields of public administration, information systems, indigenous studies, and emergency management. This framework situates the governance framework in a cross-sovereignty historical, legal, and policy contexts. It captures the multi-level features and embeddedness of governance structures, including the levels of collaborative governance structure, software system governance rules, and technical software system design. The focal governance dynamics involve the collaborative process in the bi-directional relationship between governance rules and technical design for accountability and the feedback loop. The framework highlights the importance of multi-level and process considerations in designing accountable AI systems. Productive future research avenues include empirical investigation and resulting refinement of the framework and analytical rigor employing institutional grammar.

Driving Public Values through LinkedIn

Lukas Weller — 2025-05-21

As digital transformation progresses, platforms such as LinkedIn present unique opportunities for professional engagement in public governance and sustaining public values, yet their potential remains underexplored. This study analyses the communication practices of the EU Digital & Tech LinkedIn account – a channel for promoting Europe's digital transformation initiatives led by the European Commission. By analyzing 159 posts with their engagement metrics and user comments over a six-month period in 2024, we identified key patterns in content type, sentiment, and thematic focus. Informational posts dominate the account's feed, with an emphasis on topics such as artificial intelligence, cybersecurity, and data governance. These posts generate the highest interaction scores, reflecting LinkedIn's suitability for professional and policy-driven discussions and reinforcing the platform's value in generating thoughtful, substantive exchanges. LinkedIn is likely to promote public values such as transparency, inclusivity, and collaboration effectively when communication strategies prioritize detailed content and meaningful stakeholder interaction. However, the analysis also reveals missed opportunities for direct engagement, such as responding to user comments, posing open-ended questions, or leveraging other interactive features like polls or events, possibly allowing users to take on more active roles as prosumers. By embracing more participatory formats, public sector accounts could foster richer interaction and co-ownership of policy narratives. Ultimately, we underscore LinkedIn's underused potential as a dynamic platform for collaborative innovation in digital public governance, offering actionable insights into how communication strategies can strengthen trust, responsiveness, and legitimacy in the public sector.

Geospatial artificial intelligence for automating forest land encroachment detection in India

Soorya Narayan Satheesh — 2025-05-23

Forest lands in India are under severe pressure from illegal encroachment despite the enactment of the Indian Forest Act (IFA) 1927 and Forest (Conservation) Act (FCA) 1980. This situation effectively reduces the land available for afforestation, affecting India’s global commitment to fighting climate change. Encroachment in remote locations goes undetected, preventing any measures for removal. The feasibility of applying Artificial intelligence(AI) methods on Very High Resolution(VHR) satellite imagery to automate the identification of encroachments was examined. The evaluation found that the current level of research makes it feasible. A novel method for detection and monitoring of eviction of encroachment on forestland was proposed to increase the land available for afforestation. This method can ensure more CO2 sequestration to help India meet its commitments in fighting climate change.

Fast Track for Collaborative Solutions

Wander Cleber Maria Pereira da Silva — 2025-06-30

Context: Innovation and agility are critical needs in the public administration, driving the development of methodologies that optimize collaborative processes. Goal: This study focuses on co-creating a digital solution for a Service Plan of Functions through a Service Design Workshop. We propose and apply a fast track for collaborative Solutions approach, integrating large language
models (LLMs) to streamline idea consolidation and facilitate consensus in service design workshops.

Method: We conducted a workshop aimed at rethinking an existing solution from the perspective of the service user. This involved defining personas, mapping the user journey, proposing functionalities, and aligning these functionalities with the journey stages.

Results: The proposed methodology significantly reduced execution time and enhanced the efficiency of service design processes involving large groups, without compromising decision quality. The study provides a detailed description of the methodology, the prompts employed, and the outcomes of a case study conducted in a Brazilian public-sector state-owned enterprise.

Forecasting Student Enrollments in Brazilian Schools for Equitable and Efficient Education Resource Allocation

Lenardo Chaves e Silva — 2025-05-19

In recent years, there has been growing scientific interest in developing effective techniques for forecasting student enrollment across the school spectrum (i.e., primary, secondary, and higher education). Enrollment forecasting is crucial in shaping public education policies by guiding resource allocation and ensuring equitable access to educational opportunities. In this sense, Machine Learning (ML) models emerge as a promising approach to forecasting the number of students that should be enrolled in a given school term by considering the high complexity of grouping and identifying useful patterns in the prediction process. In this work, we develop a predictive model based on the Random Forest (RF) algorithm to forecast the enrollment of students across the entire spectrum of Brazilian education. We use a database provided by the National Education Development Fund (FNDE), a Brazilian government body responsible for purchasing and distributing textbooks to all public schools. We generate 1,531,185 time series to serve as an input to RF processing. Our training dataset utilized data between 2010 and 2020, and our testing dataset utilizes data from 2021. As a result, RF obtains a higher performance in all the investigated scenarios concerning the Exponential Smoothing (ES) baseline algorithm. Since RF demonstrated acceptable performance, the Brazilian government could benefit from this forecasting technique for student enrollment in school environments and to ensure equitable access to essential resources, such as didactic materials, for the students.

Not only what, but also when

Matheus Cerqueira — 2025-05-19

Legislative public spaces are important structures for participatory democracy, allowing citizens’ voices to get engaged with politic decisions. As a consequence of the popularization of information and communication technologies, internet based tools have played an important role to improve public participation in political decisions, known as e-Democracy. These tools are usually composed of a set of functionalities or small services, named microservices. The better the microservices, the higher the citizen participation. This work investigates how to extract useful knowledge from citizen participation in the microservices of the public portal of the Brazilian Chamber of Deputies. For such, it analyzes public comments incorporating Natural Language Processing and Artificial Intelligence techniques in a platform named Ulysses. The tasks developed on this paper focus on a temporal analysis of comments on bills in the portal through Stance Detection and dynamic Topic Modeling tasks. For the first task, OxêSD, a BERTimbau-based model, was trained on two different corpora, one of them translated into Portuguese, and its predictive performance was evaluated using the F1 and ROC-AUC metrics, achieving 73% for both on our proposed Political-BRSD a mixed dataset containing both translated content from a bigger multilingual dataset (adapted from x-Stance) and bill-specific content (adapted from Ulysses-SD); for the second, BERTopic, a Topic Modeling framework, was used. Visualization tools to analyze how the proposed approach addressed the task were also used to explore the knowledge extracted. They allow the user to understand over time how the comments relate to each other and how the comments relate to a given legislative bill.

From Complexity to Clarity

Lukas Daßler — 2025-05-20

Digital transformation in public administration is increasingly driven by GovTech startups, which leverage innovative technologies to address complex societal and administrative challenges. Despite their growing importance, the business models underlying these startups remain poorly understood, limiting their effective integration into public sector ecosystems. While existing research focuses on defining GovTech and exploring its potential, little attention has been paid to the systematic analysis of the business models that enable these startups to align technological innovation with the unique requirements of public administration. Addressing this gap, our study develops a taxonomy of GovTech business models to provide clarity and actionable insights for stakeholders. Our research identifies 11 dimensions and 55 characteristics that structure the business models of GovTech startups, emphasizing meta-dimensions such as value proposition, value creation and delivery, and value capture. These insights offer a comprehensive framework to classify and analyse the diverse approaches within the GovTech sector. By analysing 85 GovTech startups in Germany through an iterative taxonomy development process, we reveal distinct patterns in areas such as funding strategies, stakeholder alignment, technological enablers, and operational scope. The taxonomy highlights how GovTech startups address key challenges like citizen engagement, operational efficiency, and compliance assistance, providing practical examples of successful implementations. This study contributes to both theory and practice by offering a structured understanding of GovTech business models. For researchers, the taxonomy provides a foundation for further exploration of this emerging field. For practitioners and policymakers, it serves as a strategic tool to foster public-private collaboration, optimize innovation adoption, and address public sector challenges in a dynamic environment.

Digital Inclusion and Social Cohesion in Smart Cities

Christos Karelis — 2025-05-21

In the era of smart cities and digital transformation, ensuring digital inclusion has become a critical factor in fostering social cohesion and equitable urban development. While digital technology brings unprecedented opportunities for development, education, and civic engagement, barriers such as limited infrastructure, financial constraints, digital literacy gaps, and social exclusion continue to hinder full digital inclusion. This article explores the complex challenges of the digital divide and its impact on marginalized groups, including older adults, low-income households, migrants, and rural communities. Through a critical review of literature and policy analysis, this study examines key obstacles to digital inclusion in smart cities and evaluates the European Union’s response to these challenges through policy interventions, broadband expansion, digital skills programs, accessibility standards, and affordability measures. Additionally, the paper highlights strategies to enhance digital participation, such as citizen engagement, inclusive urban planning, and public-private partnerships. Through the analysis of EU initiatives and emerging policy approaches, this research contributes to the discourse on digital equity and provides insights into building smart, sustainable, and inclusive urban environments. The findings emphasize the need for integrated, cross-sectoral strategies to bridge the digital divide, ensuring that all citizens can access and benefit from the digital economy and society.

What do we know about E-participation at the Local Level?

Cláucia Piccoli Faganello — 2025-05-23

This paper aims to examine the phenomenon of e-participation at the local level. This study addresses the following research question: What is currently known about the transition from participation to e-participation at the local level? This paper employs a systematic literature review to understand the current state of art about e-participation at the local level by identifying and categorizing the relevant structures, assessing the prevailing barriers, recognizing the challenges, and analyzing the potential benefits of e-participation at the local level. The purpose of this research is to provide insight into the existing knowledge base on the transition from traditional forms of participation to e-participation at the local level. The findings indicate that while e-participation presents an opportunity to improve democratic engagement and inclusivity, it also faces substantial challenges, including digital devices, institutional resistance, and the necessity for solid technological infrastructure. These findings have implications for both practice and academic discourse. From a practical perspective, the findings suggest that local governments need to invest in technology and digital literacy programs to ensure effective e-participation. From an academic viewpoint, the study contributes to the existing literature by providing a comprehensive understanding of the dynamics of e-participation and its implications for local governance.

Interactive Data Visualization for Decision-making in Government-funded Advanced Research Computing Service

Xiaoyue Cheng — 2025-05-19

Data-driven decision-making has become more prevalent in the field of digital government. Data visualization as a key tool for data exploration, can help decision makers quickly understand data and grasp insights behind pages of spreadsheets. To better support scientific discovery through advanced research computing, the U.S. National Science Foundation has funded the cyberinfrastructure programs including TeraGrid, XSEDE, and ACCESS for over twenty years. These programs have generated extensive data about the awarded projects along with their resource allocation and usage. However, existing visualization tools for these data were not designed for in-depth analysis or direct decision-making support. This research investigated the needs of resource providers and users, analyzed the data collected from TeraGrid and XSEDE projects between 2003 and 2022, and developed a publicly accessible interactive visualization dashboard. The goal of this visual platform is to enable resource providers and users to independently explore data through graphs and tables and make informed comparisons and decisions. Resource providers can use the platform to study and compare trends in resource allocation and usage across projects funded at various institutions and within different fields, identify more efficient resource users and research directions, and provide personalized services to institutions and principal investigators in need. Resource users can search for potential collaborators and helpers from successful cyberinfrastructure project awardees in similar fields, nearby locations, or related research topics. Additionally, this paper demonstrates the practical application of the visualization dashboard through three examples: a research-intensive institution, an under-represented minority-serving institution, and a junior researcher from a specific field of science, showcasing how each can leverage the platform for decision-making.

How can E-Government respond to the Digital Divide?

Bruno Andrade de Figueiredo — 2025-05-20

This research explores how distinct municipal contexts in Brazil influence the design and implementation of digital public policies, focusing on two city-level digital initiatives. The study investigates the paradox of digital government efforts, which aim to enhance inclusivity and efficiency but often exacerbate the digital divide, particularly affecting underprivileged populations. This issue is significant for public administration, as understanding how local contexts shape policy outcomes is essential for creating inclusive and effective public services. Existing frameworks can fall short in addressing this puzzle because they often neglect the role of contextual variability and the necessary local adaptations to overcome digital exclusion. These frameworks overlook how sociotechnical factors specific to each locality impact user engagement and the success of digital policies. Building on this gap, we hypothesize that the adaptability of municipal governments to local demands and digital barriers is a decisive factor in user adherence and policy effectiveness. To address this question, we conducted a comparative analysis of two municipal digital initiatives: the "Ouvindo Nosso Bairro" participatory program in Salvador and the "Saúde Já Curitiba" digital health platform in Curitiba. These cases demonstrate how municipal governments have tackled digital barriers and tailored information and communication technology (ICT) solutions to meet the diverse needs of their populations. Our qualitative research design combines documentary analysis with interviews of program managers and participants. Fieldwork and primary data collection took place between October 2022 and January 2023. Using the digital divide lens, we analyze how local contexts influenced the development and outcomes of these initiatives. This study aims to contribute to the broader discourse on digital inclusivity by demonstrating how municipal governments can adapt public policies to bridge the digital divide. By offering insights into these adaptations, the research aligns with the Sustainable Development Goals, particularly those promoting inclusive and equitable societies, reducing inequalities, and fostering innovation in public administration.

Enhancing Public Procurement Through GRC Management: Navigating the Evolving EU Regulatory Landscape

Andreas Schmitz — 2025-05-21

The increasing complexity of the extensive regulatory frameworks in the European Union (EU) creates significant challenges for public procurement processes. Besides the existing Public Procurement Directives, new regulations, such as the Corporate Sustainability Reporting Directive (CSRD), the Corporate Supply Chain Due Diligence Directive (CSDDD), and the EU Taxonomy Regulation introduce intricate compliance requirements that strain existing procurement standards and systems. This paper explores the pivotal role of Governance, Risk, and Compliance (GRC) frameworks as enablers of legal interoperability and process optimization in this evolving landscape. The research first develops an overview matrix categorizing EU regulations from 2021 to 2027 based on their relevance and impact on public procurement. Building on this foundation, a second matrix maps tailored solution components to core challenges posed by high impact regulations, identifying critical areas requiring intervention. Synthesizing these findings, the paper proposes enhancements to current standards for electronic public procurement. These include extending the European Single Procurement Document (ESPD), introducing standalone reporting formats, and leveraging GRC software to manage compliance complexities. The study highlights the importance of integrating GRC frameworks with scalable, AI-driven solutions to foster legal interoperability and operational resilience. It therewith offers actionable insights for policymakers, for practitioners in the public procurement processes, and for researchers.

Lessons Learned for Local Cybersecurity

Johanna Maria Schmidt — 2025-05-21

Cybersecurity is an integral part of digital public governance and aims to ensure the confidentiality, integrity and availability of sensitive citizen-, business-, and government-related data. Given the increasing complexity of cyberthreats, driven by the digital transformation of the public sector and emerging technologies, local governments need robust and resilient cybersecurity strategies. This exploratory study examines the October 2023 cyberattack on Südwestfalen IT (SIT), an IT service provider for over 70 municipalities, cities and districts in Germany. As a result of this ransomware attack, for several months, public services were severely disrupted for over 1.6 million citizens. Against the backdrop of the particular challenges that local governments face in managing their cybersecurity, this study identifies lessons that small and medium-sized municipalities and cities derive from this cyberattack. The paper adopts a multi-method qualitative exploratory research approach, combining key informant interviews and document analysis through reflexive thematic analysis. Key findings highlight the importance of thorough implementation of cybersecurity standards such as network segmentation, tighter monitoring practices and two-factor authentication. To mitigate cluster risks, other key lessons include increased focus on top-down decision-making to enforce non-negotiable cybersecurity standards, given the need for IT service collaboration and the use of economies of scale resulting from the resource constraints of smaller local administrations. Further practical implications include an increased focus on staff training and implementing change management strategies to reduce resistance to reform at various stakeholder levels. This exploratory study of the SIT’s recent cyber incident also serves as an example for small and medium-sized municipalities that are not part of cooperation networks, encouraging them to reconsider their cost-benefit analysis of independent cybersecurity strategies versus collaborative frameworks. Overall, the study offers valuable insights into the implications of cyberattacks for local administrations of small- and medium-sized municipalities. As such, it aims to contribute to developing more equitable and resilient cybersecurity strategies.

Smart Communities in Climate Disasters

Carolina Tavares Lopes — 2025-05-23

This study explores the role of smart communities in responding to climate disasters, focusing on the 2024 floods in Porto Alegre, Brazil, as a case study. Grounded in existing concepts of smart communities and based on 23 in-depth semi-structured interviews with community leaders, community members, community collaborators, and local government authorities, this research employs an existing framework designed to understand how these communities evolved into smart communities and whether their adoption of smart governance practices helped them mitigate the disaster’s impacts and navigate the recovery process more effectively. The findings, derived from a qualitative data analysis, reveal that pre-existing smart communities demonstrated greater effectiveness in coordinating disaster response efforts, mobilizing resources, and building resilience. Community cohesion was reinforced during the crisis, largely due to established networks, collective trust, and decentralized governance mechanisms.
However, the study also identifies significant challenges, particularly concerning the availability and reliability of ICT-based communication systems during crises, difficulties in coordinating across different levels of government, and broader governance barriers that are especially pronounced in developing countries like Brazil. By highlighting these dynamics, this study offers valuable insights into how smart communities can be strengthened to enhance disaster response and resilience, particularly in urban areas facing increasing climate risks. More than just showcasing best practices, this study emphasizes the importance of human connections, local knowledge, and governance innovations, demonstrating that integrating community-led governance into formal disaster planning is essential for proactive and adaptive urban resilience.

Data circulation between statistics agencies and journalists

Ricardo Kadouaki — 2025-05-26

This study investigates how data circulate between statistics agencies and journalists, with particular attention to the role of dissemination strategies—especially press releases—in shaping news production. While much of the literature addresses data production and use, the dynamics of data circulation remain understudied. Drawing on a case study of the statistical agency of the state of São Paulo (SEADE) in Brazil, the paper analyzes all news articles published in 2024 that referenced SEADE data. Articles were categorized according to the level of influence of press releases: full reproductions (verbatim replication), value-added reproductions (with complementary analysis or context), or organically produced (independent of any press release). These were examined through the lenses of framing theory and journalistic role performance approach. Results show that 70% of the news articles were influenced by press releases, with a significant presence of the Loyal-Facilitator dimension, particularly in government-issued releases. National outlets were more likely to produce organic content, while local media— despite showing higher demand for statistical information—relied more heavily on press releases to produce their coverage. Thematic focus also varied: national journalists prioritized economic indicators, while local outlets focused more on labor statistics. The study also found that articles based on SEADE press releases more frequently incorporated added value, while those based on government releases were more likely to be reproduced verbatim. These patterns may indicate structural constraints, particularly in local newsrooms, and varying levels of data literacy among journalists. By mapping how official statistics circulate in the media ecosystem, the research highlights the importance of hybrid, user-centered dissemination strategies that combine traditional tools like press releases with open government data practices. Such approaches can broaden the reach and enhance the relevance of official statistics in journalism and public discourse. By demonstrating how a better understanding of data circulation helps statistical agencies tailor their dissemination practices, this study contributes to the Open Government Data literature and highlights how user-centered strategies can foster more meaningful and critical engagement with official data.

Is Digital Government Strengthening or Weakening Society?

David Duenas Cid — 2025-06-30

Governments are facing technical, organizational, political, financial, etc. limitations on their capacity to tackle major policy problems like pandemics, climate change, migration, etc. that endanger societal well-being, security, and development. Overcoming such limitations requires a collective response, where different members of the society – individuals and institutions – are working with government and each other to address the problem. The aim of this paper is to examine the digital transformation of government and whether the outcome – digital government – makes society stronger or weaker, thus facilitating or undermining such collective response. To this end, we examine six qualities of social development – inclusion, equality, justice, collectivism, order and democracy – which presence or absence make societies stronger or weaker, and collect the evidence from scientific literature of digital government impacting such qualities, leading to inclusive vs. exclusive societies, equal vs unequal societies, just vs. unjust societies, etc. The result of this research is a landscape of different approaches, experiences, and designs, through which digital government contributes to the presence or absence of these qualities. This result has both research and policy implications.

AI-driven public consultation platforms

Meredith Dedema — 2025-05-19

The integration of artificial intelligence (AI) in local governments has gained increasing attention as a means to enhance civic engagement and streamline public participation. This study examines how local governments utilize AI-powered platforms for civic engagement, exploring the perspectives of public servants and developers on the implementation of AI, its benefits, challenges, and ethical considerations. With a qualitative approach, semi-structured interviews were conducted with developers, product designers, public servants, and decision-makers involved in developing and using the AI-powered platform for civic engagement initiatives. Thematic analysis was employed to identify key themes related to AI functionalities, user experiences, and governance challenges. The preliminary results reveal that four distinct types of AI applications have been employed, including AI-powered optical character recognition (OCR), AI-based content moderation, AI sensemaking, and AI-driven translation. These AI tools facilitate efficiency in data processing, enhance accessibility, and support decision-making. However, concerns regarding AI transparency, data privacy, and public trust remain significantly challenging. Additionally, public servants emphasized the need for AI literacy training and the development of ethical guidelines to ensure the responsible use of AI in local governance. This study contributes to the growing discourse on AI in civic engagement by offering insights into the practical and ethical dimensions of AI adoption in local governments. The findings underscore the need for policy frameworks, digital inclusivity measures, and ongoing capacity-building efforts to enhance AI-driven public participation.

Performance Analysis of LLMs for Abstractive Summarization of Brazilian Legislative Documents

Danilo C.G. de Lucena — 2025-05-20

Legislative documents present substantial obstacles to summarization due to their complex argument structures and specialized terminology. This research investigates the application of Large Language Models (LLMs) in summarizing Brazilian legislative proposals from the Chamber of Deputies, examining a dataset of over 56 thousand texts from 2013 to 2023. The paper explores three main summarization methodologies: extractive, abstractive, and hybrid, with an emphasis on abstractive summarization using LLMs. The performance of the LLM LLAMA2-13b is assessed using metrics such as ROUGE, BLEU, METEOR, BERTScore, and BERTopic, compared against reference summaries. The results show that LLMs can generate coherent and informative summaries, with positive evaluation metric results. Notably, the study reveals that traditional summary evaluation metrics may not be adequate for evaluating LLMs in summarization tasks. On the other hand, metrics based on pre-trained models like BERT provide a more effective evaluation of this innovative automatic summarization approach.

Towards social cohesion

Rosiane Alves Palacios — 2025-05-21

Smart cities (SC) are becoming increasingly popular around the world. Within the scope of SC studies is governance, which is directly related to the success of planned actions. Refugee migration is currently a challenge all over the world. But at the local level (cities) it can be better examined. The local migration governance network is one way for welcoming and integrating refugees in cities. However, there are barriers that can influence smart governance as well as migration governance. It is important that cities can be more inclusive and effective in welcoming migrants and refugees by promoting social cohesion. This study aimed to identify barriers of local migration governance in two smart cities in order to reflect on the possibility of increasing social cohesion for immigrants and refugees. A multiple case study was carried out on the local migration governance networks of two smart cities in the Global South: Porto Alegre-BRA and Cape Town-ZA. Twenty-five interviews were collected with migration experts and local migration governance actors, nine documents were analyzed, and observations were made in both cities. The data was analyzed through content analysis. The results of the research pointed to sixteen structural, social and political barriers. Social cohesion can be built through public policies that take diversity into account and where, once integrated, refugees can truly feel that they belong to the community. We propose a frame that summarize the actions that can promote social cohesion for immigrants and refugees in smart cities. We based the actions proposed on the barriers and the possibilities of interventions.

Cidadania no contexto da transformação digital na América Latina

João Paulo dos Santos da Silva — 2025-05-21

O artigo é um ensaio teórico que busca apresentar um framework de análise e um quadro analítico das dimensões de cidadania no contexto da transformação digital na América Latina a partir dos diferentes projetos políticos em disputa na região. Para a construção do framework e do quadro, são utilizadas as dimensões de cidadania de status legal/associação, direitos sociais e participação. O conceito de cidadania no contexto da transformação digital é apresentado em contraposição ao conceito de cidadania digital, a partir do entendimento de que a cidadania é um processo abrangente e em constante mudança através das práticas sociais dos agentes e das instituições. A transformação digital afeta este processo permanente da cidadania permitindo o uso das tecnologias da informação e comunicação (TIC) por parte das instituições e agentes na construção destas práticas sociais. No contexto latino-americano, os projetos políticos democrático-participativo e neoliberal estabelecem uma disputa de significados de dimensões chave como status legal/associação, direitos sociais e participação. Neste contexto, as práticas sociais são orientadas por estes projetos políticos em disputa. O framework e o quadro analítico propostos neste estudo buscam contribuir para a análise da complexidade do contexto latino-americano ao estabelecerem essa relação entre o impacto das práticas sociais com uso de TIC nas dimensões da cidadania e a orientação dessas práticas pelos projetos políticos em disputa.

Evaluation of Public Services Through the Lens of Digital Ethics

Narek Andreasyan — 2025-06-05

The rapidly growing popularity of digital services requires robust frameworks to identify and address associated ethical concerns. This paper presents a structured framework for assessing ethical concerns of digital services, offering a scalable and adaptable tool to assess concerns, including data misuse, cybersecurity, transparency, inequality, and sustainability. The framework employs a customized Delphi method to gather diverse expert insights, translating them into quantifiable metrics through a mathematical model. These metrics inform structured surveys, generating actionable outputs, including visual summaries, static recommendations, and AI-driven insights. To illustrate the framework’s application, we detail its implementation in the context of electronic voting (e-voting). By addressing key ethical challenges, mainly privacy, transparency, and inclusivity, this use case demonstrates the framework’s utility in analyzing complex digital services. The study highlights the importance of balancing technological innovation with ethical accountability, providing a practical approach to ensuring transparency and trust in public digital services.

Development and Deployment of Sentiment Analysis AI on Citizens’ Feedback in Goiás

Rafaela M. Rosa — 2025-05-19

This study presents the development and deployment of a sentiment analysis model based on Natural Language Processing (NLP) techniques in the context of public service evaluation. The model was implemented to automate the classification of citizens’ feedback on services provided by the EXPRESSO program in the State of Goiás, Brazil. Before implementation, the classification process was manual, which was time-consuming, and prone to inconsistencies. The dataset used included a wide range of citizen experiences, ensuring that the model captured a comprehensive and representative sample of comments. Preprocessing techniques such as noise removal, tokenization, stemming, and customized stopword adjustments were applied to refine the data for analysis. Among the algorithms tested, Multinomial Naïve Bayes (MNB) stood out for its slightly superior performance in identifying negative feedback — a critical class for monitoring service quality and addressing citizen concerns efficiently. The model was validated with managers to ensure its practical application and was subsequently integrated into the State's Data Warehouse (DW) to feed a real-time monitoring dashboard. Additionally, a visual interface was developed to allow managers to analyze feedback on demand. This interface includes features such as word clouds for positive and negative feedback, facilitating the quick identification of key themes, trends, and recurring issues. The integration of artificial intelligence into the EXPRESSO Program establishes a scalable and replicable framework to improve decision-making processes, enhance operational efficiency, and promote inclusivity. This methodology can be extended to other public service centers, emphasizing the vital role of AI in fostering responsive governance, improving service quality, and enhancing citizens’ satisfaction.

Digital Transformation, Technology, and Innovation

Daniel S. Valotto — 2025-05-20

With the advent of the Knowledge Society, Digital Transformation, and Digital Government, Brazilians have increased their presence and use of digital and knowledge resources to meet their needs. Whether in Government, the Economy, or Citizenship, the digital, knowledge, and innovation era has brought significant challenges and opportunities to Brazil, especially for large Brazilian municipalities. In this context, this study aimed to identify the proposals for Digital Transformation, Technology, and Innovation from candidates in the 46 municipalities with populations exceeding 500,000 inhabitants who were best positioned in the voting intention polls for the 2024 municipal elections. Methodologically, a qualitative study was conducted using the technique of documentary analysis of secondary data, with government plans of the best-positioned candidates in electoral polls from the 46 selected municipalities as the primary source. A nine-step protocol was used to select proposals containing one of the 31 key terms employed. A total of 2,557 proposals from 142 candidates were identified, with 1,268 (49.59%) related to Digital Government, 658 (25.73%) to the Digital Economy, and 631 (24.68%) to Digital Citizenship. With an average of 17 proposals per candidate, the main thematic areas of the proposals were related to Digital Services, Health, Education, Business, and Public Management. The analyzed proposals provide an overview of candidates' priorities and can support the development of public policies that reflect a more strategic perception of the role of digital tools in municipal development, aligned with the demands of an increasingly digital society.

Unleashing Public Sector Innovation

Sulemana Bankuoru Egala — 2025-05-21

Big data analytics (BDA) is fast revolutionizing circular economy being driven by the avalanche of data. In public governance, harnessing the value-driven opportunities of BDA has been challenging studied to improve resource allocation, decision-making, and openness and accountability but, with little attention in existing literature. Through the lens of the task technology fit theory, this study examines how big data analytics and value-driven capabilities improve public sector digital governance innovation and performance. The study leveraged PLS-SEM and collected data from 310 staff of public sectors institutions in Ghana. The study found that, task complexities, value-driven capabilities, data quality, organizational support and analytical literacy have significant impact on public sector innovation. this relationship is not however moderated by digital governance maturity. Moreover, public sector innovation was found to influence digital governance performance. The study underscores how data-driven innovations could be leveraged to improve service delivery and citizen participation in digital governance. This study outlines best practices for public sector organizations to effectively utilize big data, enhancing decision-making and governance, and fostering trust and performance in the digital era.

Collaborative Governance for the Construction of Public Policies on Social Sustainability

Sabrina Callegaro — 2025-05-21

Government actors promoting collaborative initiatives for a more inclusive and democratic society must understand that effective strategies for lasting social impact demand significant effort. Collaborative governance relies on the interaction between the government, private sector, and civil society. However, success is not guaranteed by collaboration alone, due to various factors can affect decision-making effectiveness. This article explores the key factors in collaborative governance, with a specific focus on social sustainability, to optimize governance practices. The field research was conducted using a qualitative approach through a case study in Porto Alegre city, Brazil. We conducted semi-structured interviews with 16 stakeholders, analysed documents, and performed direct observations. The study provides valuable insights for public managers and governments on effective strategies for addressing social issues and improving governance, aiming to enhance social sustainability and project efficiency. Additionally, it identifies factors for collaborative governance in the Latin America context.

Triple Transition Ecosystem As Catalyst of Public Value Generation

Dimitrios Symeonidis — 2025-05-22

Digital transformation is increasingly reshaping the public and private sectors by enhancing the efficiency and quality of services. With the integration of emerging technologies such as Artificial Intelligence (AI), blockchain, and Internet of Things (IoT), this transformation is becoming a key driver in achieving the United Nations Sustainable Development Goals (SDGs). This shift has given birth to concept of the “triple transition” emphasizes the interconnected the social, green and digital transitions as part of a systemic approach to achieve the SDGs. However, for these technologies to generate meaningful public value, they must rely on high-quality, accessible, and interoperable data. Public Data Ecosystems (PDEs) , as networks of stakeholders engaging in data exchange across the data lifecycle, provide a foundation for transparency and accountability as elements of public value. Their capacity to create broader societal and economic value remains limited without the synergy of advanced digital technologies. To this end, this study proposes the concept of Triple Transition Ecosystems (TTEs) networks of actors leveraging both PDEs and the four-intelligence (4I) paradigm (Data, Artificial, Collective, and Embodied Intelligence) to generate multidimensional public value aligned with the SDGs. Using a systematic literature review that includes thematic analysis informed by public value frameworks, we examine the potential of TTEs across various policy domains. Our findings indicate that TTEs have the potential to generate public value in terms of better service quality and governance, but also higher societal value. By conceptualizing TTEs, this study offers a novel framework for understanding digital transformation as a systemic enabler of sustainable development and provides actionable insights for researchers and policymakers seeking to design triple transition–oriented policies.

Factors Affecting the Use of Evidence in Public Sector Programmes in South Africa

Lesedi Senamele Matlala — 2025-05-23

The effective use of evidence is crucial for improving public sector programmes' design, implementation, and outcomes, particularly in addressing the complex challenges developing countries like South Africa face. Outcome 8 of the National Development Plan (NDP), which aims to transform human settlements and improve the quality of life for South African citizens, has been the subject of multiple evaluations since its introduction in 2010. Despite the availability of extensive evaluation data, integrating findings into policy and practice has often been inconsistent, with recurring issues identified across various evaluation cycles. This study systematically reviews the factors affecting the use of evidence generated from these evaluations in Outcome 8 programmes, specifically focusing on evaluations conducted from 2010 to the present. The review synthesizes government evaluations, policy reports, and academic literature to identify key barriers and facilitators in using evidence for policy-making and programme implementation. The findings reveal several barriers to evidence use, including political interference, which often influences the prioritization and implementation of evidence-based policies; limited capacity within government departments, hindering the interpretation and application of evaluation findings; and challenges in data consistency across national, provincial, and local government levels. Additionally, the review identifies that public sector programmes often rely predominantly on quantitative metrics, which may overlook the value of qualitative insights that could offer more context and a deeper understanding of policy impacts and outcomes. On the other hand, facilitators of evidence use, such as establishing strong institutional frameworks, forming evidence networks to promote knowledge exchange, and enhancing collaboration between evaluators and policymakers, were also highlighted. These facilitators help create an environment where evidence is more likely to inform policy decisions, leading to more effective governance and better programme outcomes. The review concludes by recommending strategies to address these barriers and improve the integration of evidence into policy-making and programme implementation. Key recommendations include strengthening the capacity of public sector officials to interpret and apply evaluation findings, promoting collaboration between evaluators and policymakers, and institutionalizing the use of evidence across government departments. Overcoming these challenges is crucial for improving the effectiveness of Outcome 8 programmes, advancing the broader goals of human settlement transformation in South Africa, and enhancing the impact of public policies.

Remote and Hybrid Work in Crime Victim Services

Lane Gillespie — 2025-05-26

Using the PRISMA framework for scoping reviews, we identified 27 studies on remote and hybrid work in the victim services sector that met our inclusion criteria. Studies were examined regarding (1) the data and methods used to examine remote and hybrid work in victim service agencies; and (2) provider-level and client-level outcomes. Findings show most studies are exploratory in nature, rely on qualitative data from professionals only (i.e., not service users), and suffer from methodological limitations (e.g., reliance on small, convenience samples). Further, most studies focus on the transition to remote service delivery during the COVID-19 pandemic and on domestic violence/sexual assault agencies. Findings show that common provider-level challenges include technological barriers, concerns about the security of online services, and the development of rapport with clients virtually; while strengths include personal-professional flexibility, the development of new collaborations, and work productivity/efficiency. Client-level challenges include technology access, digital literacy, and confidentiality and safety concerns, while strengths include increased access to services, reduced cost, and increased anonymity of virtual services. Results suggest that we need additional, rigorous evaluation research to understand how processes and outcomes differ between remote and in-person services. Expanding research to a wider range of types of crime victim service providers and crime victims are also important next steps.

Plataforma Pública de Conteúdos Audiovisuais Brasileiros Sob Demanda

Luciana Santa Rita — 2025-06-30

As tecnologias de streaming audiovisual reúnem aspectos relevantes sobre o desenvolvimento tecnológico e as formas de acesso, difusão e democratização do audiovisual. No Brasil, nos últimos anos, o crescimento do número de plataformas de streaming audiovisual tem representado um fenômeno social, cultural, econômico e político que desperta a atenção e o interesse de corporações privadas, governos, realizadores(as) e espectadores(as) do setor audiovisual, especificamente sobre os propósitos e usos mercadológicos, públicos, democráticos, sociais e culturais dessa tecnologia. Este artigo apresenta e contextualiza o desenvolvimento de uma plataforma de streaming pública, gratuita e brasileira, desenvolvida pelo Governo Federal, enquanto tecnologia social com potencial para impactar significativamente o audiovisual brasileiro. A discussão deste artigo a respeito do streaming público é estruturada a partir de três objetivos da plataforma: (1) formação de público, (2) difusão do audiovisual brasileiro e (3) descentralização dos espaços de exibição. Por meio de uma abordagem exploratória, são analisadas as ações implementadas e os desafios enfrentados em seu desenvolvimento, considerando um contexto marcado pela concentração geográfica da produção e da exibição, predominância de conteúdos estrangeiros em salas de cinema e plataformas de streaming comerciais, bem como a fragilidade das políticas de democratização cultural. Com base em revisão de literatura - nacional e internacional - e análise de dados secundários, avaliamos se essa iniciativa pode reconfigurar as dinâmicas de acesso e difusão do audiovisual, tendo em vista a adoção estratégica de tecnologias sociais pela Secretaria do Audiovisual do Ministério da Cultura. O artigo discute o potencial de ampliação da visibilidade de produções nacionais e regionais, do(as) realizadores(as) sub-representados(as) e narrativas plurais, com vistas a promover transformações sociais, culturais e educacionais.

Developing competences for Artificial Intelligence in the Public Sector

Gianluca Carlo Misuraca — 2025-06-03

This article introduces the AI4Gov Canvas, an evidence-based framework designed to identify and develop the competences needed by individuals working with artificial intelligence (AI) in the public sector. Recognising the need for functional specialist profiles in AI management, use and implementation within public administrations, we address the challenge of combining a variety of domains, such as technology, management and design, and policy, ethical and legal expertise.
The AI4Gov Canvas was developed through a three-step process of competence identification, clustering, and validation, involving a review of research and grey literature, expert interviews (N=5), and an online survey (N=54). It is structured around three dimensions: technology, management and design, and policy/legal/ethical, with each dimension further categorized into three levels of abstraction: meta-competences, governance competences, and operational competences.
The Canvas serves as a practical tool for mapping existing competences, identifying training needs, and designing functional specialist profiles that balance competence importance with the difficulty of obtaining them. We provide concrete examples of how the Canvas can be used to create personas, such as the "TechnoSteward" and the "Policy Sentinel", which highlight the framework's ability to guide the development of realistic and multi-disciplinary competence profiles. We conclude by outlining lessons learnt and future steps.

The implementation of an integrated education data system at national level

Fabíola Peres — 2025-05-20

This article analyzes the implementation of the Sistema Gestão Presente, an initiative of NEES (UFAL) in partnership with the Ministry of Education for the interfederative integration of educational data, with the aim of optimizing data management and supporting educational programs at a national level. This study highlights the main challenges faced during the process of implementing this system, using as a repertoire the discussion about data governance, which has already existed in Brazil for some decades. Based on focus groups, one-on-one meetings, discussion groups and experience reports, the article brings together challenges and strategies in four categories: 'Programa Pé-de-Meia business rules challenges', 'Service challenges', 'Follow-up and monitoring challenges' and 'Technological challenges'.

Bridging the Metaverse and Social Cohesion in Smart Cities

Elli Kontogianni — 2025-05-21

It is estimated that the metaverse has the potential to affect peoples’ and communities’ lives. As an integrative virtual space that offers immersive experiences to its users, the metaverse can foster virtual interactions that not only mimic but also enhance real-world social activities and relations. With its ability to narrow or eliminate physical boundaries, the metaverse presents potential opportunities for enhancing social cohesion in diverse communities. Social cohesion - characterized by a sense of belonging, mutual trust, and collaboration - plays a vital role in connecting community members. This article provides a systematic review of existing literature on the metaverse’s implications, to explore its potential to promote social connections and inclusivity in communities, both essential elements of social cohesion. The study reviews articles sourced from the scientific repositories ScienceDirect, Web of Science, Google Scholar, and Scopus. The results show that the metaverse has the potential to bridge economic, social, and cultural gaps by facilitating social interactions, broadening access to education, fostering engagement as well as by creating new economic opportunities. These advancements can encourage a sense of unity and belonging, especially in the context of smart cities, where innovation and community building come together.

Uso de DAG e IA para inovação na gestão pública e privada

Cassiano Oliveira da Motta — 2025-05-21

O presente estudo analisa o uso de Dados Abertos Governamentais (DAG) e Inteligência Artificial (IA) para inovação em Santo Antônio da Patrulha - Rio Grande do Sul sob a ótica de gestores públicos e gestores privados. A pesquisa é de cunho qualitativo, e os dados foram coletados por meio de entrevistas realizadas com oito gestores, sendo eles cinco da administração pública e três do setor privado, e também a partir do portal de dados abertos do município. A análise revela que, apesar do reconhecimento dos potenciais benefícios advindos dos Dados Abertos Governamentais e da Inteligência Artificial, sua adoção efetiva é limitada. Foram identificadas deficiências críticas na qualidade, acessibilidade e divulgação dos Dados Abertos Governamentais, além da falta de capacitação técnica em Inteligência Artificial, especialmente no setor público. A resistência à mudança também é uma barreira significativa, contudo, os gestores vislumbram o potencial da Inteligência Artificial no intuito de otimizar processos e impulsionar a inovação, e destacam a colaboração público-privada como crucial. O estudo conclui que o município de Santo Antônio da Patrulha pode se beneficiar dessas tecnologias, mas precisa investir na melhoria dos Dados Abertos Governamentais, na capacitação técnica e na promoção de uma cultura orientada a dados. Este trabalho contribui para auxiliar na compreensão do tema ao fornecer insights sobre a realidade de um município brasileiro e delinear caminhos para a adoção bem-sucedida de Dados Abertos Governamentais e Inteligência Artificial, visando à promoção da transparência, eficiência e desenvolvimento socioeconômico. As limitações da pesquisa, como a amostra reduzida, apontam para a necessidade de estudos futuros.

Analysis of automation and retraining opportunities for the Brazilian federal public service

Yuri Lima — 2025-05-23

Context: The speed of technological advancement has raised concerns about the impact of automation on work. Previous studies have analyzed this impact on the private sector, but there is little research focused on the Brazilian public sector, which faces additional challenges in dealing with this issue. Objective: To estimate the impact of automation on intermediate-level federal public positions and indicate professional retraining paths for civil servants, in the face of technological changes. Methodology: A 4-step approach was used, involving (1) mapping of automation technologies, (2) extraction and review of the job duties of 142 intermediate-level public positions from a government document with the support of AI models, (3) assessment of the importance level and horizon of automation of each job duty by GPT-4 Turbo and (4) suggestion of professional retraining courses for each position. Results: A considerable potential for automation of the analysed positions was identified, with 72% of the job duties with different automation levels in an immediate or short-term impact horizon. However, also considering the frequency and importance of each job duty, a considerable part of the positions had an impact between 0.10-0.28 points on a scale of 0 to 1. The technologies with the most occurrences in the analysis of automation impact were Machine Learning, Smart Sensors and Process Digitization Systems. In the end, 236 professional retraining courses were suggested to better prepare employees for possible technological impacts.

Enhancing Government Efficiency Through Cybersecurity Hardening

Shreyas Kumar — 2025-06-13

The rapid digitization of public sector services has fundamentally reshaped how governments operate, manage resources, and interact with citizens. From digital identity platforms to AI-enabled service portals, technology enables faster decision-making, seamless operations, and more responsive governance. Yet, this digital transformation introduces growing cyber risks, including ransomware, insider threats, and nation-state attacks. These risks not only threaten data privacy and national security but also undermine service reliability and institutional trust. To mitigate such threats and sustain innovation, cybersecurity hardening has emerged as a critical enabler of government efficiency. It includes proactive strategies such as continuous threat monitoring, network segmentation, encryption, and Zero Trust frameworks that reinforce operational continuity. While existing literature often frames cybersecurity as a compliance necessity, our research recasts it as a core strategic asset for enhancing public service performance. Specifically, we examine how cybersecurity contributes to resilience, reduces service disruptions, and improves resource allocation—three pillars of efficient governance. This approach aligns with emerging policy shifts, notably the formation of the U.S. Department of Government Efficiency (DOGE) in January 2025, which identifies cybersecurity as central to improving operational outcomes. Supported by similar initiatives in Texas, Kansas, and Louisiana, this paper situates cyber defense as a linchpin of modern administrative reform. By exploring real-world breach case studies and integrating economic modeling with cybersecurity strategy, we demonstrate how protecting systems is not just a cost-saving imperative but a means to power smarter, faster, and safer governance.

From Theory to Telegram

Julie Ricard — 2025-06-30

This study addresses two central questions: (1) What enabling factors associated with information disorder are identified in the literature? and (2) Which of these factors manifest in anti-vaccine Telegram communities in Brazil, facilitating the spread and normalization of related disinformation? Combining a systematic literature review with empirical analysis of nearly 10 million posts from Brazilian conspiracy theory groups on Telegram (2016–2024), the research identifies 18 enabling factors—classified into sociopolitical and informational ecosystem dimensions—that contribute to information disorder. Of these, 11 are empirically observed in the analyzed Telegram communities. Drawing on both qualitative and computational methods—including time series, content, and link analysis—the study proposes a conceptual model that illustrates how these conditions interact and reinforce one another, creating an environment in which disinformation can flourish. The findings contribute to ongoing theoretical analyses on the sociotechnical dynamics of disinformation.

XML as a Basis for Interoperability in Technical Education Documents

Giovana Nunes Inocêncio — 2025-05-22

Technical Education in Brazil faces challenges in standardizing digital certificate issuance and exchange across diverse platforms, affecting compliance, efficiency, and workforce integration. Unlike higher education, technical education has unique structural and regulatory demands that require a tailored interoperability solution. This study proposes an XML Schema Definition (XSD) designed specifically for technical education, extending beyond existing models used in higher education. Leveraging XML’s flexibility, the schema creates machine-readable digital certificates that improve security, transparency, and fraud prevention by providing a structured framework. The research aims to facilitate regulatory compliance and streamline data exchange between technical institutions and the Ministry of Education. A systematic literature review and comparative analysis highlight gaps in current digital document practices and support the schema’s development. The findings demonstrate XML’s potential as a transformative standard for managing educational records in technical education, optimizing accessibility and enabling seamless platform integration. Unlike prior efforts focused on higher education, this model addresses the specific operational and regulatory complexities of technical education. Implementing this schema tackles critical interoperability challenges and lays the foundation for advancing digital certification. By fostering innovation and collaboration, this work supports a unified, secure, and accessible digital certification system, promoting modernization and trust in Brazil’s educational environment.

Performance Indicators Development for Public Services using an AI-based clustering approach

Victor de Almeida Xavier — 2025-06-30

Despite the hype for AI-based generative applications, the original pitfalls in implementing AI-based technologies remain: data quality, readiness, and availability. AI results are tied to the quality of the data provided to the underlying algorithms. Inevitably, bad data produces bad results. The same happens for data readiness and availability: without correct preparation and access, even high-quality data cannot be used in AI-based solutions. To help decision-makers in the public sector, performance indicators applied to processes and, therefore, to public services can be used as tools to guide public project selection, allocation of resources, monitoring of results, etc. In this way, performance indicators can be used to standardize the evaluation of public
policies, helping citizens and city administrators make more informed decisions regarding the environment they live in. In the present work, we propose a performance indicator development process (PIDP) based on AI clustering techniques, which can be used to gather key performance indicators (KPI) among available data from open data sources and consumed and/or produced by the core processes that implement a public service.

The Impact of Government Emotion-based Response Strategies on Citizens' Satisfaction

Ruoyun Wang — 2025-05-19

Government responsiveness is a critical component in citizen-government interactions, shaping public trust and the effectiveness of e-governance initiatives. However, resource constraints often lead to strategic responses aimed at managing citizens’ emotions and avoiding conflicts, rather than resolving all issues. Despite this, few studies have examined government response strategies and their impact on citizen satisfaction. This study examines the impact of emotion-based responses on citizen satisfaction within the context of China’s e-governance initiatives. Utilizing data from the Chinese People’s Daily ”Message Board for Leaders” platform, we introduce the Emotion-based Responsiveness Framework in Government Communication, which quantifies government responses along four dimensions: positivity, empathy, reassurance, and personalization. We first use text analysis to identify linguistic patterns and emotional cues in government replies. Then, we apply few-shot learning via the ChatGPT API to infer dimension scores across the dataset. Lastly, we test whether government’s emotion-based responses will affect citizen’s overall satisfaction. The result shows that the emotion-based response will positively affect citizens’ satisfaction. The study contributes to e-governance literature by providing empirical evidence on the effectiveness of emotional communication strategies in digital government-citizen interactions. These insights have important implications for theory development in public administration and offer practical guidance for improving government communication strategies in the digital age, especially in situations where complete problem resolution may not be feasible.

Leveraging Conversational AI for Adolescent Medical Financial Education

Wesley Chen — 2025-05-22

Medical financial literacy is essential to make smart decisions in healthcare settings and prevent unanticipated financial hardships. Existing literature has shown that young adults often struggle to understand information associated with health insurance and the financial planning necessary for health-related costs. AI-driven chatbots are emerging as educational tools that have the potential to address this issue. This exploratory study examined an AI chatbot aimed at enhancing medical financial literacy among high school students. Participants engaged with the chatbot’s responses to medical financial questions while also rating the clarity, ease of use, trustworthiness, and educational value of the chatbot engagement. Our experiment results supported that the chatbot increased students’ understanding of the financial aspect of healthcare - 76.9 percent of students reported a high degree of understanding, 80.8 percent rated the chatbot’s responses as clear, and 73.1 percent reported they would recommend it to a peer. The responses indicated that students found the chatbot helpful, but suggested that interactive features be added and/or real-world finance features be incorporated into the chatbot.

Data Report on School Dropout in a Brazilian State

Leogildo Alves Freires — 2025-06-30

School dropout is a multifaceted and persistent challenge with serious implications for public health, economic development, and social equity. In Brazil, where educational disparities remain deeply rooted in structural and contextual inequalities, addressing dropout requires more than tracking attendance, academic performance, or behavior. This study presents the development and implementation of a Relational Model (RM) aimed at identifying and mitigating school dropout risks through a comprehensive, data-informed approach. Central to this model is the Alternative Instrument for Assessing School Dropout Risk Factors (IAFREE-A), which evaluates 13 interrelated risk factors across five key dimensions: Student-School, Student-School Professionals, Student-Family, Student-Community, and Student-Student. These dimensions allow for a nuanced understanding of how relational dynamics and contextual conditions shape students’ engagement with schooling. A pilot study was carried out in the state of Mato Grosso, involving 624 students across 10 public schools. Data collection was conducted through physical questionnaires, digitized using Optical Character Recognition (OCR) technology, and processed via an integrated digital platform. This platform generates individual and institutional dropout risk profiles by mapping protective and risk factors, providing actionable insights for educators, school administrators, and policymakers. Results highlighted critical concerns such as inadequate school infrastructure, perceptions of insecurity, and weak family-school connections, reinforcing the need for early, context-specific interventions. The findings demonstrate that school dropout is not an isolated event, but the outcome of complex relational, institutional, and structural factors. The RM and IAFREE-A offer an innovative and culturally sensitive framework for prevention, enabling tailored interventions that respond to students’ lived realities. By fostering stronger connections among students, educators, families, and communities, this approach has the potential to reduce dropout rates and promote more equitable and supportive educational environments in Brazil and beyond.

PIX, Open Finance, and DREX

Vanessa da R.S. Almeida — 2025-06-03

Digital Public Infrastructure (DPI) is a new concept that garnered significant attention during the 2023 G20 discussions. DPIs can help advance all United Nations Sustainable Development Goals, making research in this area critically important. Despite its significance, academic literature on DPI is still scarce. To help cover this gap, this poster proposes a DPI evaluation framework based on the United Nations' definition of DPI. The evaluation framework was applied to three potential DPI cases that emerged from the Brazilian finance sector. The selected cases include PIX, an instant payment solution; Open Finance Brazil, a consent-based data exchange solution; and DREX, the Brazilian central bank digital currency. Using the proposed evaluation framework, it was demonstrated that the first two cases can be considered DPIs, and the last one has the potential to become a DPI.

Digital Governance and Institutional Challenges in Rural Heritage Restoration

Oscar Miranda-Hospinal — 2025-05-19

This study aims to analyze the challenges faced by local governments in the preservation and restoration of rural historical buildings in Peru, using the Caqui Hacienda in the Chancay Valley as a representative case. It is proposed that the rigidity of Peruvian regulations on cultural heritage, combined with the limited technical and budgetary capacity of local administrations, represents a significant obstacle to the recovery of these properties. Additionally, other barriers are identified, such as the weak implementation of digital governance, lack of institutional coordination, and limited availability of accessible digital platforms for citizens. Through an exploratory qualitative approach that combines historical analysis, regulatory review, field observation, and surveys of public works professionals, the study seeks to evaluate how the adoption of technological tools and the modernization of public policies could contribute to a more efficient, transparent, and sustainable management of cultural heritage. The expected results aim to provide evidence on the need for regulatory reforms and institutional strengthening and to propose the use of emerging technologies, such as artificial intelligence, in the monitoring and restoration processes of historical heritage in rural contexts.

Leveraging official government data for enhanced understanding of health crisis communication topics

Houcai Wang — 2025-05-22

Taking full advantage of multiple official government data sources is crucial for government emergency management agencies and authorities to formulate scientific and feasible crisis communication policies and measures. The current study examined the case of the public health emergency to explore the association between government microblog activities and the evolution of the public health emergency. Moreover, the present research utilized latent Dirichlet allocation (LDA) topic modeling to detect dominant pandemic-related themes in the government microblog dataset and the government press release conference dataset. Research results indicate that the evolution of government microblog activities is generally similar to that of the pandemic outbreak. The current research also found that government microblog messages and press releases had consistent pandemic-related themes (medical treatments, nucleic acid testing, pandemic statistics, pandemic updates, press conferences, and material support). These results can assistant government agencies and stakeholders obtain a comprehensive understanding of the evolution of public health emergencies and public feelings, concerns, and issues, which will further improve their crisis communication ability.

A Comparative Study on Judicial Visualization in the U.S. and China

Jiawei Zhou — 2025-08-07

The visualization of judicial statistics is a new form of judicial openness in the era of big data, which is of great significance for the public to understand judicial dynamics and maintain judicial fairness. The study finds that neither the Supreme Court of China nor the U.S. Supreme Court provides a dashboard of judicial statistics, but the frequency of data updates in the United States is quarterly, and in China, it is updated in the form of annual reports. Among the court web portals of 35 provinces (including Hong Kong, Macao, and Taiwan) in China, only 3 courts provide visualization of judicial statistics. Among the 51 state court web portals in the United States, 18 courts conduct visualization of judicial statistics. For dg.o attendees, this research offers unique insights into how the two countries approach the challenge of making judicial data accessible and understandable to the public.

Digital Dependence vs. National Performance

Jaromir Durkiewicz — 2025-05-19

Countries differ in their capacity to develop and use digital technology – some build such capacity locally, others rely on foreign countries and corporations, and yet others do both. While sourcing arrangements may vary, the outcome is critical to countries’ performance – their ability to pursue national goals and priorities. The paper explores the relationship between the countries’ digital dependence and performance, relying on the calculation of the Spearman correlation coefficient between the Digital Dependence Index and the Online Service and E-Participation Indices, for 23 countries in 2020. The calculation established a small to moderate negative correlation between the variables, i.e. the better performance, the lower dependence, in line with theoretical assumptions, and identified cases that violate these assumptions.

Urban Resilience and Virtual Communities

Dulce M. Villegas N. — 2025-05-22

Urban resilience is perceived as the response of governments towards unforeseen events. However, communities also develop their own mechanisms to transform and adapt more efficiently. With the integration of ICT in cities, rapid response and predictive capabilities are expected to improve urban management. Currently, cities face a critical, unprepared challenge: immigration. If inadequately addressed, immigration can strain national cohesion, identity, and economic stability. This paper examines urban resilience within virtual communities, focusing on how networking platforms foster integration and social cohesion enhancing urban and economic resilience. The networking platform Meetup, being used in 230 cities aiming to enhance trust among members and a faster integration through online and face-to-face interaction. With a qualitative approach including surveys, it is possible to measure how these communities’ foster resilience and self-directed development.

Cultural Observatories as Digital Platforms of Public Value in Brazil

Silvia B. Ribeiro — 2025-05-19

For enhancing transparency and compliance with access to information laws, government portals provide information about investments, investing companies, and beneficiary sectors in creative economy. However, the dispersion and poor structuring of data on government investments in culture limit the understanding of the public value generated by these actions, both for public managers themselves and for society. Based on an empirical quantitative study with collected data frow digital portals of two Brazilian different subnational states, this article aims to discuss how government portals can structure their data on cultural investments in a way that translates its public value. As results, we propose directives for the structuring of culture data in government platforms that contemplates dimensions in a way that supports the perception of public value.

Cyberattacks in government organizations

Dimaz Cahya Ardhi — 2025-05-22

In the digital government era, the government must protect citizens’ data from cyberattacks to gain public trust. This study aims to identify the type of cyberattack incidents in government organizations and the implementation strategies to prevent cyberattacks. In this study, we conduct the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) approach to answer our research questions. It performs a detailed analysis based on 50 peer-reviewed articles published in the conference proceedings and journals from January 2020 to December 2024. Those articles are retrieved from five databases: ACM Digital Library, Engineering Village, IEEE Xplore, the University at Albany Library, and Web of Science. The results revealed six types of cyberattacks in government organizations: malware, denial-of-service attacks, phishing attacks, false data injection, supply chain attacks, and advanced persistent threats. Furthermore, our review showed that four strategies have been implemented to prevent cyberattacks: 1) developing national cybersecurity strategies and frameworks, 2) building cyber defense capacity, 3) enhancing infrastructure resilience, and 4) education, training, and awareness. This study contributes to the field by providing different types of cyberattacks associated with government organizations and presenting a centralized and comprehensive analysis of research work in security, which is an excellent resource for other researchers in a similar field. Finally, this study also offers practical implications for government organizations, providing strategies to help them prevent cyberattacks.

Landscaping digital transformation in academic education programmes within Europe

Grażyna Musiatowicz-Podbiał — 2025-06-30

This paper aims to recognize content and trends with topics related to Digital Transformation (DT) in educational offers in Higher Education Institutions (HEI), in four EU countries: Austria, Italy, the Netherlands, and Poland. Research is based on benchmarking, recognizing keywords in courses and programmes offered by European universities. The main findings indicate that DT is an essential element of EU education curricula.. The second observation shows DT education as frequently located at the intersection between technology and society. The third finding demonstrates the growing inclusion of DT topics in non-technical disciplines. This research also has practical implications, as its findings on educational portfolios can be applied globally.

Experiment Canvas

Welkey Costa do Carmo — 2025-07-25

This paper presents the Canvas of the Experiment, an innovative tool developed by the Innovation Laboratory of the Court of Justice of the State of Ceará (LabLuz) to structure, implement, and evaluate innovation within the Brazilian judiciary. By employing a data-driven approach, the Canvas aims to enhance efficiency, accessibility, and inclusion in judicial processes. The study descibes the methodology, structure, and impact of the Canvas through various case studies, demonstrating its effectiveness in generating measurable results and promoting evidence-based decision-making. The results reveal the potential of the Canvas to transform innovative ideas into practical solutions, offering a valuable model for other public institutions.

Measuring the Social Impact of Digital Services

Radomir Bolgov — 2025-05-19

The paper presents the results of using automated tools to study the dissemination of information in media, social networks and instant messengers, as well as the comments to mobile applications, allowing to search for information by keywords. The cases analysed are the Unified Ecosystem of Urban Services "Digital Petersburg" and its flagship application "I Live Here", as well as the mobile application "Unified Card of St. Petersburg Resident" as part of a study on the social impact of digital services. The data obtained indicate on low awareness of citizens about digital public services. At the same time, we can talk about the high demand among citizens for the "Unified Card of St. Petersburg Resident" service, where, unlike the first case, there is active feedback from the authorities and work to eliminate the shortcomings of the service.

Can We Trust Open Government Data in Public Procurement?

Robin Fritzsche — 2025-05-22

Evidence-based policy-making in public procurement depends on high-quality data. This case study evaluates 14 months (Nov 2023–Jan 2025) of procurement records from the EU’s Tenders Electronic Daily (TED) to assess the reliability of this key data source. Our analysis uncovers significant anomalies in data accuracy and governance, raising concerns about the integrity of procurement processes and the policies built on them. We highlight the urgent need for improved data governance to support transparency, accountability, and innovation-driven procurement.

Leveraging AI Models for Automated Pattern Detection in Citizen Participation Data

Amal Marzouki — 2025-07-10

Citizen Participation (CP) is essential for urban projects, traditionally done through face-to-face meetings. Information Technologies (IT) have introduced electronic participation (e- Participation), enhancing inclusivity and engagement. CPPs generate valuable data for decisionmaking, but processing large volumes of unstructured data is challenging. Traditional methods are inefficient. AI algorithms can improve data analysis, automate classification, detect patterns, and extract relevant information, reducing the workload for decision-makers. This research explores how AI can detect and classify patterns in CPP data, contributing to best practices in applying AI to government operations.

ARGOS

Eduardo Pacheco — 2025-05-19

We present the modeling of an AI system named ARGOS to classify free legal aid requests in the Court of Justice of Espírito Santo (TJES). The model replicates the decision-making pattern of a judge from the 6th Civil Court of Vila Velha, developed within Challenge 16 of PitchGovES by Atlas.IA, promoted by the State Management Laboratory of Espírito Santo (Lab.ges). The challenge proposed an automated solution to assess applicants' eligibility by cross-referencing multiple data sources to support judicial decisions. The approach consists of three key components: (i) a machine learning model for classifying requests, (ii) an information retrieval engine to support the model, and (iii) an explainability mechanism to justify decisions. A global model for TJES was initially considered but discarded due to legal and technical constraints. Instead, a judge-specific model was developed to align with the principle of Judicial Independence in Decision-Making. Model development began with analysing past judicial
decisions, classifying requests as granted or denied. A significant challenge was data imbalance, as requests were not evenly distributed across classes. To address this, balancing techniques and feature selection methods were applied. Various machine learning algorithms, including decision trees and deep learning models, were tested. The final model balanced accuracy and
interpretability, ensuring magistrates could understand the factors influencing decisions. The second component involved creating an information retrieval engine to supplement applicant data. Given that free legal aid assessment relies on financial capacity, the tool gathered external data. However, access to government databases was restricted, so alternative sources were used, including public income records, social assistance histories, and judicial metadata. The solution comprises four modules: applicant data capture, a dashboard, a decision interface with model training, and a recommendation system. The initial implementation achieved 81.3% balanced accuracy, surpassing the 70% target, demonstrating potential for broader judicial adoption.

The evolving AI regulation space

Nic DePaula — 2025-05-19

As artificial intelligence (AI) technologies proliferate, the US federal government has oscillated on related executive orders, and no federal laws have addressed AI comprehensively. However, many states have passed legislations related to AI in the previous 5 years, and these laws are evolving and becoming more targeted, creating challenges and opportunities for government agencies. For this study, we compiled all passed and enacted legislations across the 50 US states in 2024 and examined them in terms of: domains; regulation of AI use in the public sector and industry; and novel topics and issues being addressed. In this preliminary analysis, we find that recent AI legislations are multiplying across US states, but unevenly. AI regulation across states continue to address various domains, including healthcare, education, and now also generative AI and AI-generated content. Legislations are expanding the role of the public sector in AI governance and AI policies, but issues of AI ethics, such as bias, are unevenly addressed across states, and few states have comprehensive AI governance frameworks.

Converging Paths?

Yuliia Bartashevska — 2025-05-22

This study investigates how co-creation is being institutionalized in public service delivery in Poland and Ukraine, focusing on six domains of citizen involvement: legislative frameworks, digital platforms, public consultations, civic monitoring, local initiatives, and civic education. These neighboring countries, connected through shared regional initiatives but shaped by differing political, administrative, and civic trajectories, offer a compelling basis for comparative analysis. While both have made strides in adopting participatory practices, Poland tends to follow a more structured, policy-aligned approach, whereas Ukraine exhibits dynamic, bottom-up developments driven by ongoing decentralization reforms. Our findings indicate that co-creation is becoming more systematically integrated into governance structures, although institutionalization remains uneven across domains and administrative levels. Key challenges include institutional fragmentation, limited translation of public input into policy outcomes, and underdeveloped interdisciplinary competencies, particularly in light of digital transformation and the growing role of AI. The paper concludes with practical recommendations for strengthening co-creation ecosystems in both countries.

Beyond Technology

Luiza Schuch de Azambuja — 2025-05-19

Smart Sustainable Cities (SSCs) integrate technology, governance, and sustainability to address urban challenges and improve citizens' quality of life. However, the understanding of SSCs varies depending on local contexts and stakeholders’ perspectives and is often technocentric. This study presents preliminary findings on how local authorities in Porto Alegre (POA), Brazil, understand smart sustainable cities, analysing their perceptions and interpretations of this evolving urban model. This study addresses the following research question: What does "smart sustainable city" mean to local authorities in Porto Alegre? Using a qualitative approach, fifteen interviews with key officials from different city departments provide preliminary insights into how SSCs are framed beyond technological advancements illustrating examples of initiatives that contribute to Porto Alegre’s transition towards an SSC. While technology plays a role, local authorities emphasise inclusive governance, innovation, data-driven decision-making, education, collaboration, citizen-centricity, and integration as central to their vision of a smart sustainable city.

Enhancing user experience

Dwi Puspita Sari — 2025-05-22

Government organizations initiate digital transformation by using online platforms to facilitate the dissemination of open government data (OGD) to the public. Despite the government’s effort to increase citizens’ willingness to participate in the OGD initiative, there is a possibility that citizens may encounter challenges accessing the OGD through open government data portals (OGDP). This study aims to assess the effectiveness of user interface (UI) and user experience (UX) design in Satu Data Indonesia (SDI), the Indonesian national OGDP. The research question guiding this study is “How does user experience influence willingness to use OGDP?” We follow a quantitative approach to gain an understanding of the OGDP usability and users’ willingness to engage with the OGD. First, an experiment will examine participants’ access to SDI portal. Second, a survey will investigate whether the participants are willing to use OGD based on their experience engaging with OGDP. This study will enhance our understanding of OGDP usability within the context of developing countries and evaluate whether user experience influences future usage willingness. Ultimately, the findings will benefit governmental entities in improving their OGDPs’ usability and user experience.

BEPP-DS

José Antonio F. Macedo — 2025-05-26

The exponential growth of data and the advancement of computational tools have made Data Science (DS) an essential discipline for addressing complex societal challenges. In the public sector, Evidence-Based Public Policies (EBPP) leverage data-driven insights to enhance governance transparency, efficiency, and effectiveness. However, the integration of Data Science into policymaking presents challenges, including data quality, interdisciplinary collaboration, and institutional resistance. This paper introduces BEPP-DS, a structured methodology for developing EBPP using DS principles, emphasizing transparency, reproducibility, and scalability. The methodology is informed by real-world applications such as Big Data Social and Big Data Fortaleza, which illustrate how data-driven strategies improve policy design, implementation, and monitoring. BEPP-DS defines a structured framework, from problem identification to policy evaluation, ensuring data-driven decision-making in governance. The methodology provides a replicable model for governments seeking to harness Data Science in policy formulation. Future work includes expanding AI-driven analytics and strengthening citizen engagement in data governance.

Transformative Synergies

Neusa Andrade — 2025-05-15

This study presents the development and validation of a breast cancer patient journey as a real-world demonstration of how public-private collaboration can address digital government challenges while advancing Industry 4.0 and Government 4.0/5.0 paradigms. Using Curitiba, Brazil, as a pilot city, the initiative highlights how technologies, standards, and governance frameworks can foster social cohesion and reduce health inequalities by improving breast cancer care. By leveraging AI-driven tools, participatory governance, and data interoperability, the project aligns population health goals with economic efficiency, ensuring accessible and high-quality care. The results demonstrate the potential of collaborative digital health strategies to enhance public health equity and inform scalable governance models for broader applications across sectors. This research offers a replicable framework for advancing digital transformation in health systems, focusing on preventive and cost-effective interventions to promote resilient and inclusive health ecosystems.

Digital technologies and partnerships for Sustainable Development Goals

Beatriz Ventorini Lins de Albuquerque — 2025-05-21

Digital governance is a central concern in global efforts to achieve the Sustainable Development Goals (SDGs). The United Nations (UN) emphasizes the potential of digital technologies and technological partnerships to address global challenges, while governments struggle to develop technology governance policies at a pace that keeps up with technological advancements. Problem: despite growing recognition of digital technologies and technological partnerships as key enablers of sustainable development, there is limited understanding of how they could be more effectively leveraged by governmental and non-governmental organizations to advance the SDGs. Approach: This study examines how the UN envisions the role of digital
technologies and technological partnerships in advancing the SDGs and analyses these findings through the lens of Social Innovation Ecosystems (SIEs). Methods: A qualitative document analysis was conducted on six official UN documents (2022–2024) addressing digital technologies and technological partnerships in the SDGs context. Thematic and reflexive analysis was applied with iterative coding. Main results: Findings highlight priority issues such as AI regulation for child protection, ethical and inclusive AI governance, counterterrorism, and efforts to reduce digital inequality. Four thematic categories were generated, and analysis also reveals a dual focus: centralized governance and stringent regulation of emerging technologies — particularly AI — alongside a call for international cooperation, ecosystem-like partnerships, public digital goods, and open models. Conclusions: Some UN priorities present tensions, as strict governance structures may hinder the agility required for open collaboration, and vice versa. SIEs approach may offer a potential balance, enabling governments, corporations, academia, and civil society to co-create solutions, share resources, and scale social innovations while ensuring technological development and adoption aligns with human rights, digital equity, and the SDGs.

Drivers and Barriers in Libya’s E-Government Implementation

Amged B. Shwehdy — 2025-05-26

This study aims to identify and analyse the key drivers and barriers influencing the implementation of e-government initiatives in Libya's public sector, a developing country with a post-conflict context. Employing a combined theoretical framework based on TOE framework and UTAUT, this research adopts a mixed-methods approach. Semi-structured interviews with digital ecosystem multi-stakeholders, were conducted alongside closed-ended surveys. The findings reveal that e-government implementation in Libya is shaped by technological, organizational, and environmental factors, as well as user acceptance dimensions. The study
underscores the importance of addressing structural and institutional challenges through a centralized, strategic approach to enable successful digital transformation. Recommendations include enhancing digital infrastructure, fostering public-private partnerships, improving digital literacy, and reforming public sector policies. The insights gained are not only applicable to Libya but also offer valuable lessons for other nations facing similar challenges in digital transformation.

Automation of the Planning and Management Instruments of the Unified Health System (SUS)

Ilka Correa de Meo — 2025-05-26

This paper aimed to develop a solution using digital technological resources to overcome operational obstacles and improve efficiency in the process of developing and monitoring the Planning and Management Instruments of the Unified Health System (IGSUS). The IGSUS instruments include: the Municipal Health Plan (PMS), the Annual Health Programming (PAS), the Detailed Report of the Previous Quarter (RDQA), and the Annual Management Report (RAG). These instruments result from the collaboration of multiple stakeholders and are essential for organizing actions that address the health needs of the population. Reports from the team itself, corroborated by an initial mapping of the process, indicated that there was significant repetition of operational tasks and rework in the creation of data collection files, sending emails to technical areas, reviewing the information entered by respondents, consolidating spreadsheet files, and preparing the consolidated text file. The mapping and automation of the processes for developing and monitoring the IGSUS followed methodologies for project management, process management, and agile methods, focusing on a collaborative, governed approach inclined toward innovation and improvement in the delivery of public services. This work led to the establishment of standardized data collection forms, Python scripts that automated these tasks, and a platform for sharing spreadsheets, reducing the hours spent on these tasks and enabling better support for the planning process with the technical areas of the Municipal Health Department of São Paulo.

Adapting Your Startup’s Product for Public Sector Innovation Calls

Ramon Chaves — 2025-05-21

Recently, GovTech has gained prominence as a novel approach to fostering government-driven innovation by leveraging technology startups, academia, and innovators to develop digital public services. Although it promises more agile, user-centric, and cost-effective solutions, limited research explores how academic-based startups navigate public procurement models. This paper addresses that gap by presenting three cases of an academic-based Brazilian startup engaging in the public procurement process introduced by the Legal Framework for Startups (Marco Legal das Startups). The company proposed solutions adapted from its principal product for three public agencies: Tribunal de Contas da União (TCU), Correios, and Copasa, focusing on remote oversight of construction projects and building maintenance management. The lessons learned underscore the importance of predictable project scope and costs, emphasizing that unclear requirements can undermine competitiveness. Moreover, strong teams and reputable track records significantly enhance success prospects while balancing technological maturity with innovation, which remains critical for meeting specific public sector needs. Additionally, positioning a product at the technological frontier only proves beneficial when addressing actual government challenges. Effective communication, including well-crafted video pitches and presentations, further ensures evaluators grasp the solution’s value. These insights aim to guide both aspiring and established academic entrepreneurs in bridging their research-based innovations with GovTech opportunities, ultimately strengthening collaboration between the public sector and academia.

Reflections on Collaborative Design

Elaine Venson — 2025-05-26

Digital Transformation in public services requires a comprehensive understanding of the value creation to improve services and government operations. Designing digital public services is challenging, but Service Design methods can help achieve services that align with democratic values like accessibility, reliability, and a positive user experience. This article reports on the collaborative design of a mobile app for a regulatory agency in Brazil, using co-creation, co-design, and co-production methods through two workshop cycles. The first cycle, based on Lean Inception principles, defined the Minimum Viable Product (MVP), while the second cycle, utilizing Design Sprint techniques, refined and tested the MVP with citizens. Feedback from users and public servants is also shared, emphasizing the importance of involving citizens and government employees in developing public service solutions.

LiS

Adelnei de L. C. Felix — 2025-05-21

Digital transformation is a consolidated topic on government agendas and the use of AI-Artificial Intelligence in this context is increasingly expanding. However, efforts are needed to ensure that the digital transformation of public services no longer creates a channel for social exclusion. A key component in this sense is the use of clear language in products and information for access to digital public services. The main objective of this work is to describe the experience report of the construction of an Artificial Intelligence-AI, called LiS, with the purpose of improving the quality of the contents of service letters to users, from bodies of a subnational entity in Brazil. We will present the stages of developing the LiS, to review the contents of service letters to users, using plain language writing techniques. The combination of an automatic review, using LiS and a manual step, in the process of preparing and reviewing service letters for users, presented significant results in the services, which had their contents reviewed in this process. This gain was observed from the analysis of the results of evaluations of the content of services accessed by citizens. Another significant result presented was the reduction in review time for service letters. The use of the AI tool balanced with a human review stage, in the context of building and reviewing service letters for users, demonstrates efficiency in this process. Additionally, this combination reflects an approach to increase inclusion in citizen access to public services.

Developing the Strategic and Master Plan for Information and Communication Technology at the IT Agency of the State of Tocantins

Vanessa Tavares Nunes — 2025-06-30

The rapid evolution of digital governance necessitates strategic planning to ensure efficiency, transparency, and adaptability in public service delivery. This paper presents the development of the Strategic and Master Plan for Information and Communication Technology (PEDTIC) at the Tocantins State Information Technology Agency (ATI/TO), a pivotal initiative aimed at strengthening digital transformation efforts in Tocantins, Brazil. The PEDTIC was built upon three foundational diagnostic assessments: the Governance of ICT, the Strategic IT Plan (PDTI), and the ABEP-TIC Index evaluation. These diagnostics provided a comprehensive analysis of ATI/TO’s digital service capabilities, governance structures, and alignment with state objectives. The methodological approach combined situational assessments, regulatory reviews, management interviews, and benchmarking against national best practices. The findings highlighted gaps in IT governance, data integration, and digital service effectiveness. By aligning ATI/TO’s strategic vision with the broader objectives of the Tocantins government, the PEDTIC establishes a framework that prioritizes structured governance, risk management, and the enhancement of public digital services. This study discusses the lessons learned from the diagnostic phase, emphasizing the importance of clear communication, cross-department collaboration, and proactive risk management in digital transformation. The PEDTIC provides a structured action plan with clearly defined objectives, performance indicators, and accountability mechanisms to ensure continuous improvement and adaptation. The results of this initiative have already led to a significant improvement in ATI/TO’s ranking in the ABEP-TIC Index, demonstrating tangible progress in digital governance. Additionally, this paper explores the implications of ATI/TO’s transformation towards a more strategic operational model, shifting from purely technical functions to a leadership role in state digital governance. The conclusions drawn highlight the critical need for structured digital strategies, ongoing capacity-building initiatives, and stakeholder engagement to sustain long-term advancements in public digital services. The PEDTIC serves as a case study for other government institutions aiming to implement structured and scalable digital transformation initiatives.

Data, Algorithms, and Automation in Social Protection

Danyelle Carvalho — 2025-05-22

In recent years—particularly following the COVID-19 pandemic—governments have expanded the use of digital technologies and automated systems in social protection policies. One of the most prominent developments in this field is the spread of Single Registries: unified databases of individuals and families in vulnerable situations, often integrated with artificial intelligence (AI) and automated decision-making tools. In Brazil, the Unified Registry for Social Programs (“Cadastro Único”) has become the main infrastructure for identifying and selecting beneficiaries of a wide range of social programs, including Bolsa Família. As of late 2024, it holds data on over 95 million people. In July 2024, the Brazilian government launched its national Artificial Intelligence Plan, allocating R$ 1.76 billion to the use of AI in public services—part of which is earmarked for modernizing Cadastro Único. While automation can improve the management and coordination of social policies, it also introduces new risks. If not carefully
implemented, automated systems can produce errors, limit access to rights, and reinforce existing inequalities. In 2019, the UN Special Rapporteur on extreme poverty warned of the emergence of a “digital welfare dystopia” marked by opacity, exclusion, and lack of accountability. This workshop proposes a critical dialogue on the expansion of AI and automation in social protection, using the Brazilian experience as a starting point. We aim to discuss how data-driven tools are reshaping eligibility, targeting, and control in welfare systems, and to reflect on how a data justice approach can help ensure that digital governance in this field promotes — not undermines — equity and inclusion.

Indigenous worldviews and Digital Humanism

Bukelwa Ngoqo — 2025-06-30

As the world grapples with the challenge of integrating Artificial Intelligence (AI) into existing systems or processes, there is a resultant tension associated with the inherent nuances between determining where the role of the human-stops and that of the machine-begins. As new 4IR driven technologies are integrated into main-stream society, dialogue on the important topics
of inclusive e-Governance and Digital Humanism from a global south perspective must be encouraged. This paper acknowledges the limitations of technologies developed from a western viewpoint that prioritises individualism over community which is an inherent trait of the indigenous worldviews. In the universal viewpoint of Digital Humanism, indigenous perspectives must be included. Digital humanism transposes the social concept of humanism into the digital realm. Digital humanism seeks to ensure that human values such as dignity, freedom, ethics, democracy, social justice and self-determination are not overlooked as technological capabilities become more sophisticated. Historically, developing countries have been identified as late adopters of technological advancements. This paper seeks to unpack the concept of Digital Humanism, explore its relevance to e-Governance and investigate its alignment to existing (global south) e-inclusion discourse.

The Potential of Blockchain Technology for Collaboration among Countries

Jefferson Bicca Charczuk — 2025-05-22

In today’s interconnected world, cooperation between countries is crucial, whether to deal with challenges or opportunities in the economic, social, technological or environmental perspective. This document proposes a workshop regarding the potential use of blockchain technology to foster international cooperation among different countries, to address opportunities and challenges. Cross-border collaboration is often hindered by inefficiencies, lack of transparency, and trust issues between nations. Blockchain technology, characterized by its decentralized, transparent, and immutable nature, has the potential to change the way countries collaborate, offering new opportunities for more efficient, secure, and trusted cooperation.

Building Capacity for Smart Cities and Urban Resilience through Digital Transformation

Gabriela Viale Pereira — 2025-05-22

This workshop explores capacity-building needs for public sector digital transformation in the context of smart cities and systemic resilience. Framed within the Erasmus+ CAP4CITY_DM project, it brings together academics, practitioners, and students to identify emerging skills and competencies across governance levels and sectors. The program includes a brief introduction to the REALITIES Joint Master’s Curriculum, lightning talks from invited experts on digital governance, AI, smart communities, and innovation, followed by a collaborative session to map skill gaps in the field. Expected outcomes include shared insights on cross-sectoral capacity needs, contributions to curriculum development, and stronger connections between education, practice, and policy. The workshop supports a broader understanding of smart cities as part of interconnected systems to address complex societal challenges.

Workshop “Digital Government Measurement for Research and Public Policies”

Manuella Maia Ribeiro — 2025-05-22

Based on the Regional Center for Studies on the Development of the Information Society (Cetic.br) 20 years’ experience on measuring information and communication technologies (ICT) in Brazil and its participation in various international indicators standards working groups, the workshop aims to familiarize the participants with digital government indicators and strategies to use them in research and public policies. To achieve this purpose, participants will be informed about the availability of secondary data related to digital transformation and digital government from both demand- and supply-side, including international databases. The organizers also intend to present showcases using datasets of national surveys in Brazil relating to the adoption of technologies by governments and individuals.

Responsible application of artificial intelligence in the Brasilian public sector

André Luiz Sucupira Antonio — 2025-06-27

The proposed panel discusses the responsible application of artificial intelligence (AI) in the public sector, focusing on governance and the mitigation of inequalities inherent in risk, implementation, and structuring. AI presents unparalleled opportunities for enhancing efficiency and quality in public services. However, it is imperative to adopt a responsible approach to prevent exacerbating technical and social inequalities. This work examines best practices for governance in AI systems, transparency mechanisms, and inclusivity frameworks, ensuring that AI contributes to equitable and inclusive societal development.

Digital government and meaningful connectivity

Manuella Maia Ribiero — 2025-05-19

The panel aims to explore the role of meaningful connectivity in digital government theory and practice, identify existing gaps, and propose future research directions. The meaningful connectivity perspective, which transcends binary Internet access metrics, is generally defined by the presence of infrastructure, affordability, and digital skills—dimensions considered crucial for ensuring that low-income and vulnerable populations can effectively use digital public services. The panel discussion will also showcase practical case studies of meaningful connectivity measurement in Brazil, Chile, the Dominican Republic, and Uruguay using the methodology developed by the Regional Center for Studies on the Development of the Information Society (Cetic.br), a UNESCO Category II center located in Brazil. By engaging experts and researchers in digital government, the panel intends to provide valuable insights for academics, policymakers, and practitioners aiming to enhance the adoption of digital public services and bridge digital divides.

Beyond the Bureaucracy

Alois Paulin — 2025-06-27

Nonmediated Governance (nm-Gov) refers to a visionary state of a society in which members of the society steer their government through Liquid Democracy. This for now purely theoretical concept assumes that every citizen is represented in a digital form, that all assets of the society are represented digitally, as well as that rules that govern the community are digital. This paper summarizes nm-Gov and Liquid Democracy and describes a diagraming technique used to model use-cases to better understand how data in nm-Gov can be translated to concrete governance action. Deeper exploration of nm-Gov through modeling further use-cases with this diagraming technique is the theme of the Beyond Bureaucracy workshop at the dg.o 2025 in Porto Alegre, Brazil.

Advancing AI Adoption in the Public Sector

Helen K. Liu — 2025-05-19

Governments are increasingly adopting AI to improve public services as part of smart city development, and hybrid intelligence plays an essential role in this developmental process. This panel, emphasizing stakeholder perspectives, explores the opportunities and challenges of adopting hybrid intelligence for smart city development. We include three papers and six authors for the panel. The first paper investigates how smart city initiatives facilitated through citizen-government participation platforms differ in terms of stakeholder groups, types of participation, and technology employed. The second paper examines how the municipal city, Hsinchu City Government, utilizes intersection fisheye camera images to analyze traffic flow and their related
stakeholders' views on such adoption. The last study examines data-driven public services by combining the strengths of human experiences and artificial intelligence. This paper discusses studies utilizing open data, big data, or linked data to support informed decision-making through an inclusive process and inter-governmental collaboration and innovation transfer, as shown in the second paper. The panel will also reserve time for the audience to join the discussions and share their related research in applying hybrid intelligence for smart city development.