Open Government Data Research Articles

Open Government Data and the Urban–Rural Income Divide in China: An Exploration of Data Inequalities and Their Consequences

Amidst excitement for the data revolution’s potential benefits, concerns mount over its negative impact as unequal data distribution, access, and use widen disparities between individuals and groups, highlighting the urgent need for advanced theoretical and empirical frameworks. This study investigated the impact of open government data (OGD) on the urban–rural income divide in China. Our theoretical analysis shows that the nonrival nature of data initially widens the urban–rural income divide before eventually mitigating it, resulting in an inverted U-shaped relationship. Using a multiperiod difference-in-differences specification, we found that OGD widened the urban–rural income divide between 2010 and 2019. Furthermore, cities with initially wider urban–rural income divides experienced a greater impact from OGD in expanding this divide. These findings provide valuable insights in the role of open data in addressing income inequality, and contribute to our understanding of data inequalities in the context of the data revolution.

Research and System Design of Open Government Data Value Measurement System Based on Integrated Machine Learning

Research and System Design of Open Government Data Value Measurement System Based on Integrated Machine Learning

Geospatial Hotspot Analysis and Endemicity Trends of Missing and Unrecovered Children in India.

Children constitute a nation's true asset. A country's future relies upon the proper development of its children, which necessitates a supportive environment and sufficient opportunities. Children, under the age of 18 yearsform a considerable percentage of India's population which imparts a huge responsibility for the nation. Everyday we come across news about a child going missing. The National Crime Record Bureau (NCRB) states that 73,138 children were reported missing overall in 2018. The prevalence increased by 8.9% in 2019, a worrisome situation. The cause behind children going missing is multi-dimensional like poverty, unemployment, loss of livelihood, natural calamities, social conflicts, and migration to urban areas. At present, missing children remain a neglected and non-urgent intervention area for everyone. Only the parents whose children are missing can feel the vacuum and sorrow of the situation. The sociologies of India's missing children merit dimensional and circumstantial examination. The sociological space into which a child goes missing is highly under-researched in India. This study helped in understanding the magnitude of missing cases across India based on existing literature and secondary sources. It also identified the potentially safe and worst areas with regard to missing children. The endemicity helped in identifying the changing trends in each of these areas of interest, which could serve as baseline data for policymakers and law enforcement alike. This is a cross-sectional analytical type of study. The data of missingand unrecovered children for the past five years (2021-2017) were obtained from open government data portal (https://data.gov.in) and geospatial hotspot analysis was done using the Getis-Order-G statisticson the same usingGeoPandas and PySAL libraries of python. The endemicity of missing cases was studied using hierarchical cluster analysis and self-organizing maps using Python. For boys,Uttar Pradesh, Rajasthan, and Madhya Pradesh remained consistent hotspots (high risk of missing cases) across all five years of study whereas Karnataka became a hotspot for 2020 and 2021.Among the cold spots (low risk of missing cases), Andaman and Nicobar Islands remained consistent cold spot across all five years of study and has emerged as a safe haven for boys.The missing girls' data reveals that Uttar Pradesh has consistently been the worst state for girls (along with their neighbors) as it possess the risk of girls going missing all through the study period with Chhattisgarh being included from 2019 onwards.Jharkhand, Gujarat, Sikkim, and Andaman and Nicobar Islands have consistently been cold spots across the board and have emerged as areas with low risk for missing girls. This study helps us in understanding the magnitude of missing cases across India and it also identifies which are potentially safe areas as well as worst areas with regard to missing children. The endemicity also helps us in identifying the changing trends in each of these areas of interest. This will serve as a great resource for policy makers and law enforcement alike.

Data Preparation: A Technological Perspective and Review

Data analysis often uses data sets that were collected for different purposes. Indeed, new insights are often obtained by combining data sets that were produced independently of each other, for example by combining data from outside an organization with internal data resources. As a result, there is a need to discover, clean, integrate and restructure data into a form that is suitable for an intended analysis. Data preparation, also known as data wrangling, is the process by which data are transformed from its existing representation into a form that is suitable for analysis. In this paper, we review the state-of-the-art in data preparation, by: (i) describing functionalities that are central to data preparation pipelines, specifically profiling, matching, mapping, format transformation and data repair; and (ii) presenting how these capabilities surface in different approaches to data preparation, that involve programming, writing workflows, interacting with individual data sets as tables, and automating aspects of the process. These functionalities and approaches are illustrated with reference to a running example that combines open government data with web extracted real estate data.

The role of open government data and co-creation in crisis management: Initial conceptual propositions from the COVID-19 pandemic

During the COVID-19 pandemic, open government data (OGD) was often used as a valuable crisis management resource. Unfortunately, there is limited research that explores how OGD can be used during times of crisis as a crisis management tool. To ensure that OGD can be used effectively in future crises, there is a need to understand how it may be used and what benefits its usage may bring. This paper brings new insight into this topic by conducting a comparative exploratory case study of three Central and Eastern European (CEE) countries – Czech Republic, Estonia and Latvia, where OGD was used at different levels to help manage different aspects of the COVID-19 pandemic. As a result of this research, three contributions are made: (1) it integrates OGD into previous crisis management literature, offering new and initial conceptual propositions; (2) it demonstrates how OGD enables the co-creation of new services that create public value during times of crisis; and (3) it provides empirical examples of OGD-driven co-created services.

Seeing data like a state: A case of Open Government Data in India’s livelihoods program

Open Government Data (OGD) initiatives promise to make governments transparent, enabling citizens to participate actively in governance. Yet, empirical evidence suggests that OGD doesn’t have the democratic impact that its advocates expect. Based on a 14-month ethnography of India’s livelihood program, we argue that the assumptions underlying the design of OGD initiatives vary with citizens’ social context. We show how OGD initiatives are state-centric in their design to make the functioning of the everyday state legible towards controlling corruption. However, citizens and social activists do not always share such an “anti-corruption” view in their engagement with the everyday state. Instead, they prioritise “getting things done”, i.e. accessing the state’s services. The state-centric OGD is of limited value to them due to its techno-official language and its emphasis on aggregate datasets. We suggest complementing state-centric OGD with citizen-centric OGD to enable the citizens to “see the state”.

Rethinking Open Government Data for Citizen Participation. An Introduction to a Special Issue

Citizen participation has always been considered one of the key pillars of open government: providing citizens with government information should enable them to participate effectively in decision-making or other government procedures. Despite this obvious connection between open government data (OGD) and citizen participation in theory, their relationship turns out to be much more complicated in practice, as OGD is hardly used in practice to hold the government accountable or change government policy. This introduction argues for a reconceptualization of the idea of citizen participation in relation to OGD, moving away from the ‘more is better’ approach towards a more refined understanding of different levels of citizen participation.

Campania Crea—A Collaborative Platform to Co-Create Open Data and Scaffold Information Visualization within the Campania Region

Open government data, as open data, are published to let interested stakeholders exploit data and create value out of them, but limited technical skills are a crucial barrier. Moreover, data silos within any public agency behave as a further obstacle in enabling collaboration between different working groups. This paper investigates the acceptance level of a collaborative platform to co-create, analyze, and visualize open government data within an Italian Regional Public Administration—the Campania region. This investigation first requires retracing and documenting the organizational changes applied to the Campania Region in moving from a siloed structure to a more horizontal and collaborative one. Second, it introduces the technical and technological contribution provided by the proposal of a Social Platform on Open Data (SPOD) as a regional public administration back-office, i.e., an internal platform, co-designed with public agency delegates and referred to as Campania Crea. Finally, it reports on the training session moderated by the University of Salerno to evaluate the acceptance rate of the proposed platform in real settings by involving 54 public agency members in actively using Campania Crea to co-create, analyze, and visualize open government data. The After Scenario Questionnaire was used to assess the acceptance level and attitude in using Campania Crea to report task-based results and the Technology Acceptance Model as an overall assessment of the platform acceptance level. As a result, Campania Crea supports regional public administration members in accomplishing their daily tasks concerning co-creation, analysis, and visualization of open data who positively accepted Campania Crea as a back-office tool. However, further effort should be invested in raising awareness and developing skills concerning open government data management.

LEGO: Linked electronic government ontology

E-government services are subject to a growing level of complexity, which requires a disruptive approach that better support the citizen needs concerning the government administration. Nowadays, available information technologies facilitate the description and online execution of administrative tasks, saving time and reducing possible errors. These technologies reduce administrative costs but require a complex electronic government system. We propose using semantic technologies to describe the e-government organisational units and services in the Open Government Data and Services context. The use of semantics improves government management, service delivery and decision-making processes. This article presents an extension of related work, introducing the evolution of the Ontology for Electronic Government (EGO): integrating other existing ontologies, supporting new features to describe e-government services and widening the usage scenarios. This extension enables the use in a real scenario with four use cases: the electronic government in the Province of Misiones (Argentina). However, the use in the domain of electronic government in a provincial context is also a proof of concept that this approach is general enough to expand into superior domains of countries that adopt the republican system of government with the division of government into the executive, legislative and judicial branches.

Increasing Continuous Engagement With Open Government Data

A number of countries are today implementing open government data (OGD) initiatives. Yet many of these initiatives are failing to attract the levels of continuous use they need to deliver an acceptable return on investment. This raises the obvious question of why this should be the case. To answer this question, it is important to understand the factors that most strongly influence user behaviour in OGD adoption. Qualitative data were used to identify the factors that play a key role in influencing the intention to engage with ODG. A quantitative approach was then used to evaluate the extent to which these factors drive/limit behaviour. The study's findings showed that there are four factors that play a significant role in intention to use OGD. It is also believed that the findings will be useful in helping policymakers in all jurisdictions formulate and implement strategies that successfully drive up continuous OGD engagement.

Usability and Accessibility of Open Government Data Portals of Countries Worldwide

The open government data (OGD) portal is an initiative by governments worldwide to promote transparency and accountability and enhance citizen participation and public value creation. The ability of these portals to deliver the expected benefits depends on their usability and accessibility, besides their content. This study conducts an integrated assessment and comparison of the OGD portals of 75 countries based on their usability and accessibility. The usability of the portals is measured through several technical indicators, classified into performance metrics, browser timings, and optimisation using automated diagnostic tools. Accessibility is evaluated through portals' conformance to web content accessibility guidelines (WCAG). The ‘technique for order of preference by similarity to ideal solution' (TOPSIS) and entropy weight method are used to rank the portals. The findings of this study could be helpful for policymakers and internal stakeholders of OGD initiatives to identify the focus area and make decisions on resource allocation.

Towards a taxonomy of research areas in open government data

PurposeThis study aimed to develop a taxonomy of research areas in open government data (OGD) through a bibliometric mapping tool and a qualitative analysis software.Design/methodology/approachIn this study, the authors extracted metadata of 442 documents from a bibliographic database. The authors used a bibliometric mapping tool for familiarization with the literature. After that, the authors used qualitative analysis software to develop taxonomy.FindingsThis paper developed taxonomy of OGD with three research areas: implementation and management, architecture, users and utilization. These research areas are further analyzed into seven topics and twenty-eight subtopics. The present study extends Charalabidis et al. (2016) taxonomy by adding two research topics, namely the adoption factors and barriers of OGD implementations and OGD ecosystems. Also, the authors include artificial intelligence in the taxonomy as an emerging research interest in the literature. The authors suggest four directions for future research: indigenous knowledge in open data, open data at local governments, development of OGD-specific theories and user studies in certain research themes.Practical implicationsEarly career researchers and doctoral students can use the taxonomy to familiarize themselves with the literature. Also, established researchers can use the proposed taxonomy to inform future research. Taxonomy-building procedures in this study are applicable to other fields.Originality/valueThis study developed a novel taxonomy of research areas in OGD. Taxonomy building is significant because there is insufficient taxonomy of research areas in this discipline. Also, conceptual knowledge through taxonomy creation is a basis for theorizing and theory-building for future studies.

Empirical analysis of open government data usage in Tanzania

PurposeDespite the potential benefits of open government data (OGD) and its recent adoption by many governments, little is known about monitoring its use by the public. This paper aims to address the knowledge gap by empirically examining OGD usage in Tanzania.Design/methodology/approachA field survey design was used to gather quantitative data from 288 people in seven regions of Tanzania to facilitate an analysis of the determinants of users’ behavioural intention and use behaviour of OGD. Guided by the Unified Theory of Acceptance and Use of Technology model, the study analysed the tendencies of these determinants on the use of the OGD portal.FindingsThe results show that performance expectancy, effort expectancy, social influence and facilitating conditions affect users’ acceptance and use of the OGD portal. The results suggest that OGD initiatives should focus more on their potential applications than publication. It is important to monitor and evaluate OGD use and the conditions that allow it to continue. By linking OGD with other government initiatives, governments can build strategies, capacity and social awareness. During the development of OGD platforms for extensive reuse, new data technologies like the semantic web should be considered.Originality/valueHitherto, research has underlined the significance of OGD initiatives at large and that studies in developing countries are scarce, especially that probe the uptake of the current efforts. The present study seeks to plug this research gap by examining the use of OGD in Tanzania’s context.

Constructing a knowledge graph for open government data: the case of Nova Scotia disease datasets

The majority of available datasets in open government data are statistical. They are widely published by various governments to be used by the public and data consumers. However, most open government data portals do not provide the five-star Linked Data standard datasets. The published datasets are isolated from one another while conceptually connected. This paper constructs a knowledge graph for the disease-related datasets of a Canadian government data portal, Nova Scotia Open Data. We leveraged the Semantic Web technologies to transform the disease-related datasets into Resource Description Framework (RDF) and enriched them with semantic rules. An RDF data model using the RDF Cube vocabulary was designed in this work to develop a graph that adheres to best practices and standards, allowing for expansion, modification and flexible re-use. The study also discusses the lessons learned during the cross-dimensional knowledge graph construction and integration of open statistical datasets from multiple sources.

Open Government Index in Local Government During the Period of the COVID-19 Pandemic

Identification that has been carried out in studies of open data government and e-government has been widely described from various perspectives. This study aims to examine how the government applies open government data. This study analyzed the existing open government of local government in Indonesia during the COVID-19 period, providing information to test the transparency of existing local governments. This study adopts the Benchmark Model Evaluating Data Openness theory and E-Gov assessment using a quantitative approach by dividing several categories and assessment variables. The open government analysis assessment uses a score of 1-5, and a web assessment with a score of 100. From this calculation, it is found that the five provinces with increased cases have high OGD scores. The results are plotted based on the spread of COVID-19 throughout Indonesia, as determined by reviewing and surveying the provincial government's COVID-19 website. West Java (89.87), East Java (89.87), Jakarta (88.75), Central Java (88.37), and Yogyakarta (88.37) all had high and nearly balanced total scores (84.87). The increased assessment results are supported by infrastructure and good management, and the five areas are "metropolitan" areas with good quality technology and information

Citizens’ utilization of open government data portals in China: a comparative case study of supply vs demand

PurposeThe rising volume of open government data (OGD) contrasts with the limited acceptance and utilization of OGD among citizens. This study investigates the reasons for citizens’ not using available OGD by comparing citizens’ attitudes towards OGD with the development of OGD portals. The comparison includes four OGD utilization processes derived from the literature, namely OGD awareness, needs, access and consumption.Design/methodology/approachA case study in China has been carried out. A sociological questionnaire was designed to collect data from Chinese citizens (demand), and personal visits were carried out to collect data from OGD portals (supply).FindingsResults show that Chinese citizens have low awareness of OGD and OGD portals. Significant differences were recognized between citizens’ expectations and OGD portals development in OGD categories and features, data access services and support functions. Correlations were found between citizens’ OGD awareness, needs, access and consumption.Originality/valueBy linking the supply of OGD from the governments with each process of citizens’ OGD utilization, this paper proposes a framework for citizens’ OGD utilization lifecycle and provides a new tool to investigate reasons for citizens’ not making use of OGD.

Graph Neural Networks and Open-Government Data to Forecast Traffic Flow

Traffic forecasting has been an important area of research for several decades, with significant implications for urban traffic planning, management, and control. In recent years, deep-learning models, such as graph neural networks (GNN), have shown great promise in traffic forecasting due to their ability to capture complex spatio–temporal dependencies within traffic networks. Additionally, public authorities around the world have started providing real-time traffic data as open-government data (OGD). This large volume of dynamic and high-value data can open new avenues for creating innovative algorithms, services, and applications. In this paper, we investigate the use of traffic OGD with advanced deep-learning algorithms. Specifically, we deploy two GNN models—the Temporal Graph Convolutional Network and Diffusion Convolutional Recurrent Neural Network—to predict traffic flow based on real-time traffic OGD. Our evaluation of the forecasting models shows that both GNN models outperform the two baseline models—Historical Average and Autoregressive Integrated Moving Average—in terms of prediction performance. We anticipate that the exploitation of OGD in deep-learning scenarios will contribute to the development of more robust and reliable traffic-forecasting algorithms, as well as provide innovative and efficient public services for citizens and businesses.

Effects of Visual Communication Design Accessibility (VCDA) Guidelines for Low Vision on Public and Open Government Health Data.

Since 2019, the Korean government's investments in making data more accessible to the public have grown by 337%. However, open government data, which should be accessible to everyone, are not entirely accessible to people with low vision, who represent an information-vulnerable class. Emergencies, such as the COVID-19 pandemic, decrease face-to-face encounters and inevitably increase untact encounters. Thus, the information gap experienced by low-vision people, who are underprivileged in terms of information, will be further widened, and they may consequently face various disadvantages. This study proposed visual communication design accessibility (VCDA) guidelines for people with low vision. Introduced screens enhanced by accessibility guidelines were presented to 16 people with low vision and 16 people with normal vision and the speed of visual information recognition was analyzed. No statistically significant difference (p > 0.05) was found due to the small sample size; however, this study's results approached significance with improved visual recognition speed for people with low vision after adopting VCDA. As a result of the intervention, the visual information recognition speed of both normal and low-vision people improved. Thus, our results can help improve information recognition speed among people with normal and low vision.

Methodologies for publishing linked open government data on the Web: A systematic mapping and a unified process model

Since the beginning of the release of open data by many countries, different methodologies for publishing linked data have been proposed. However, they seem not to be adopted by early studies exploring linked data for different reasons. In this work, we conducted a systematic mapping in the literature to synthesize the different approaches around the following topics: common steps, associated tools and practices, quality assessment validations, and evaluation of the methodology. The findings show a core set of activities, based on the linked data principles, but with additional critical steps for practical use in scale. Furthermore, although a fair amount of quality issues are reported in the literature, very few of these methodologies embed validation steps in their process. We describe an integrated overview of the different activities and how they can be executed with appropriate tools. We also present research challenges that need to be addressed in future works in this area.

Freedom of information laws and open government data as anti-corruption measures

The phenomenon of corruption can be cited as a problem of social development – economic, political and social, in most of the counties in the world.
 The corruption is concerned with the lack of democracy and can lead to unequal distribution of power and resources, lack of accountability, weak institutions and mismanagement. The purpose of the article is to analyze the importance of access to information laws and open data in the field of fighting corruption. The author argues his point of view, thе access to public information is a basic value in a democratic society and a prerequisite for the right of citizens to reasonably express an opinion and disseminate it. The general scientific research methods applied in the article are: analysis and synthesis methods, methods of systematic research, inductive and deductive methods, comparative analysis, comparative-legal method and systematic interpretation. The study showed that in order to defend our guaranteed human and civil rights, we must, strive not to turn a blind eye to corruption, but to look for possible ways of counteraction and prevention. By joining forces in this direction, members of society can support democracy, protect their human rights and, just as importantly, protect the moral foundations of society.