Open Government Data Research Articles

Integration of quantum physics theories to understand open government data (OGD) adoption by the government

PurposeThis paper aims to further the understanding of Open Government Data (OGD) adoption by the government by invoking two quantum physics theories – percolation theory and expander graph theory.Design/methodology/approachExtant research on the barriers to adoption and rollout of OGD is reviewed to drive home the research question for the present study. Both the theories are summarized, and lessons are derived therefrom for answering the research question.FindingsThe percolation theory solves the riddle of why the OGD initiatives find it difficult to seep across the hierarchical and geographical levels of any administrative division. The expander graph theory builds the understanding of the need for having networking among and within the key government personnel for bolstering the motivation and capacity building of the operational personnel linked with the OGD initiative. The theoretical understanding also aids in the implementation and institutionalization of OGD in general.Originality/valueIntersectionality of domains for conducting research on any theme is always a need. Given the fact that there are innumerable challenges regarding the adoption of OGD by the governments across the world, the application of the two theories of quantum physics might solve the quandary in a befitting way.

Medical Support Vehicle Location and Deployment at Mass Casualty Incidents

Anticipating and planning for the urgent response to large-scale disasters is critical to increase the probability of survival at these events. These incidents present various challenges that complicate the response, such as unfavorable weather conditions, difficulties in accessing affected areas, and the geographical spread of the victims. Furthermore, local socioeconomic factors, such as inadequate prevention education, limited disaster resources, and insufficient coordination between public and private emergency services, can complicate these situations. In large-scale emergencies, multiple demand points (DPs) are generally observed, which requires efforts to coordinate the strategic allocation of human and material resources in different geographical areas. Therefore, the precise management of these resources based on the specific needs of each area becomes fundamental. To address these complexities, this paper proposes a methodology that models these scenarios as a multi-objective optimization problem, focusing on the location-allocation problem of resources in Mass Casualty Incidents (MCIs). The proposed case study is Mexico City in a earthquake post-disaster scenario, using voluntary geographic information, open government data, and historical data from the 19 September 2017 earthquake. It is assumed that the resources that require optimal location and allocation are ambulances, which focus on medical issues that affect the survival of victims. The designed solution involves the use of a metaheuristic optimization technique, along with a parameter tuning technique, to find configurations that perform at different instances of the problem, i.e., different hypothetical scenarios that can be used as a reference for future possible situations. Finally, the objective is to present the different solutions graphically, accompanied by relevant information to facilitate the decision-making process of the authorities responsible for the practical implementation of these solutions.

Open Government Data for Urban Management in Indonesia’s Smart Cities

Rapid implementation of Open Government Data (OGD) across the world comes as the result of the advancement of Information, and Communication Technology in the government sectors to support decision making process including for urban planning. In one side, countries such as European countries, UK, and US has been implementing OGD while developing the framework and the maturity standard to ensure its quality. In the other side, Indonesia had just begun to develop several OGD portals which some of the practices could be found in its smart city namely Jakarta, Bandung, and Surabaya. The established OGD portals goals are to achieve transparency, government accountability, support innovation and development. This data-rich portals have potential roles for creating data-driven urban management. However, very least research observed implication of OGD practices in Indonesia for urban management. Therefore, this study aims to answer the question on how OGD portal could support urban management in Indonesia smart cities. The study identifies the implication of three open government data portals operated by smart cities in Indonesia by extracting and analysing the available data for urban management. The identification will be conducted with descriptive qualitative method based on open data principles and data-driven urban management dimensions. The study finding will explore the OGD practice level for urban management in Indonesia and recommend the improvement if needed.

Exploring open government data ecosystems across data, information, and business

Although the Open Government Data (OGD) movement is flourishing globally, the large-scale utilization and value creation of OGD has not really opened yet, which is far from the goal and expectation of data openness. Guiding the practice of OGD with the concept of “ecosystem” can help promote the efficient utilization and value realization of data. From the perspective of the whole process of OGD utilization, ecosystems have various types of ecological characteristics such as data flow, information expression and value realization. To this end, this paper proposes a new perspective of viewing OGD ecosystems across data, information and business based on the theories of supernetworks, data value chains, information ecosystems and business ecosystems, and further explores the ecosystems through a case study in Guizhou, China. We conclude that the hierarchical division of OGD ecosystems as a whole is clearer, and the focus of each layer is more focused; the cross-level dynamics mechanism of the ecosystem, and the information transmission mechanism assumed by the information ecosystem make the three layers interact with each other; and the different actors play different roles in the three layers and occupy different ecological position. This study provides useful reference for OGD practice and also expands new ideas and space for theoretical research and application practice of the ecosystem approach.

Challenges and Opportunities in Implementing Open Government Data Initiatives in East Africa

Open Government Data (OGD) initiatives in East Africa represent a transformative approach to governance, aiming to promote transparency, accountability, citizen engagement, innovation, and economic development.These initiatives seek to make government data openly accessible to the public, empowering citizens to scrutinize government actions, monitor public spending, and participate in decision-making processes. However, the implementation of OGD initiatives faces several challenges, including infrastructure limitations, data quality and availability issues, data privacy and security concerns, and the lack of clear legal and policy frameworks. Addressing these challenges requires significant investments in technological infrastructure, data management practices, capacity building, and policy reform. Despite the challenges, OGD initiatives present numerous opportunities for driving positive change and fostering socio-economic development in East Africa. By promoting transparency, accountability, and citizen participation, OGD initiatives lay the foundation for a more inclusive, responsive, and prosperous society. Keywords: Open Government Data (OGD), East Africa, Challenges, Opportunities, Governance

Artificial Intelligence and International Trade Laws: In Light of Trade Policy and Data Sharing

Due to rapid increased in the interest in how Artificial Intelligence (AI) will affect recently, there has been significant emphasis directed into the impact of this emerging technology on international trade rules, particularly in relation to the economy and trade. We examine the world’s most powerful countries, how they revaluating the trade by using AI and introducing new laws relate to AI. We explore the possibility that AI approaches might provide predictions and connections that are more accurate than those produced by traditional economic models, for accurate predictors. Additionally, we discuss that AI may be used to examine trade patterns and events like trade wars, countries give high importance on comprehending and predicting future trade trends by using AI. Having access to the data is crucial because only open-government data can be used as the fuel for AI that can anticipate and suggest policies. In order to fully use the promise of AI technologies, policymakers should take into account the connections between trade and AI technologies that are explored in this article. The major focus of this investigation is on China’s endeavours to develop and expand its AI industry, as well as the actions that the country has made to establish itself as a dominant player in the global trade market. We also examine to get advantages of globalization international trade policies continue to be in the spotlight. We also highlight that the use AI approaches to understand how trade patterns are impacted by extreme events like pandemics and trade wars.

IJCM_273A: Severe adverse events following Covid 19 vaccination immunisation in India: Retrospective Study.

Background: Coronavirus disease 2019 is a newly emerged viral infection reported in India on 30th Jan 2020. Because of high transmissibility rate it spread rapidly and become a pandemic in the year 2020. Though it was a new disease, there were no specific treatment measures for the same. COVISHIELD is the vaccine manufactured from serum institute of India and give approval for emergency use from 30th Dec 2020 without conducting phase trials, Because of numerous infective cases, complications and deaths. There is no separate AEFI surveillance system for COVID 19 vaccines. All the AEFIs were reported via immunization division of Ministry of Health and Family welfare. Objective: 1. To identify the type of AEFI following COVID 19 vaccination. 2. To detail the outcome of AEFI following COVID 19 vaccination Methodology: An observational study on AEFI following COVID 19 vaccination in India, the secondary data during 2020 to 2022 was collected from the open access government data http://surl.li/npkmb from 1st to 20th Oct 2023. The causality assessment results, 254 reported serious AEFI cases were approved by National AEFI Committee on 3rd May 2022.2 The data analysed by using SPSS Statistics. Results: A total of 125 million COVID 19 vaccine doses were administered all over India till 2nd Feb 2022. Out of which 254 reported serious AEFI. Among this 20.1% were =60 years of age. Serious AEFI with hospitalization was 57.9% and death was 42.1%. Around 30.7% cases were found to have a consistent causal association to vaccination. Among this 60.26 %were anxiety related and 39.74 % were vaccine product related. 8 deaths per 1 lakh COVID 19 vaccinations. Only 24.4% of the people with severe AEFI have comorbidities. Conclusion: Benefits of COVID 19 vaccination are enormous. However, as a measure of utmost precaution, all emerging AEFI are being constantly tracked and reviewed periodically.

The Moderating Effect of Gender and Academic Background in Open Government Data (OGD) User Adoption and Usage

ABSTRACT The present research seeks to rest its edifice on the proposition that the role of gender and academic background of a user in terms of the technical/liberal/hospitality and care domain impinges upon the Open Government Data (OGD) adoption and usage. Specifically, the adapted Unified Theory of Acceptance and Use of Technology (UTAUT) model is being deployed to empirically validate how the OGD usage and adoption vary among the 313 respondents in a leading private university in India in line with their academic background and gender. Findings from the study via Partial Least Squares-Structural Equation Modelling (PLS-SEM) show that academic background and gender are moderating Behavioural Intention to use and adopt OGD through Performance Expectancy, Facilitating Conditions, Data Quality, System Quality, Information Quality and Trust, whilst the Multi-Group Analysis (MGA) shows that there are differences between the technical and liberal/hospitality and care cohorts in terms of their gender vis-a-vis Voluntariness of Use and System Quality vis-a-via the Behavioural Intention to adopt and use OGD.

Exploring dimensions of metadata quality assessment: A scoping review

Assessing metadata is of paramount importance for several critical reasons. Metadata plays a pivotal role in various aspects, including data retrieval and search, data organization, interoperability, data preservation, and the overall user experience. The purpose of this scoping review is to identify the most commonly measured dimensions of metadata quality in existing studies on metadata quality assessment. The study also investigates the types of data sources and countries contributing most to the literature on metadata quality assessment and the types of documents used to communicate their findings. The methodology involves the application of PRISMA model for qualitatively evaluating 55 studies on metadata quality assessment. The co-occurrence analysis is made on the title and abstract of selected articles using VOSviewer 1.6.18 version, visualization software. The review found that completeness, accuracy, consistency, accessibility, conformance, provenance, and timeliness are commonly used dimensions in metadata quality assessment. However, there is no consensus on their exact definition and measurement, indicating a need for further investigation into less commonly assessed quality dimensions. Digital repositories and open government data are the most commonly studied data sources, with the United States being the leading contributor and journal articles being the most commonly used document type. The cluster analysis based on co-occurrence of terms in title and abstract found three research areas, “Metadata Quality Assessment,” “Metadata Quality Dimensions,” and “Metadata Quality Applications, Frameworks, and Approaches” as prominent areas of research. The originality of the study lies in its methodology that involves rigorous screening of articles on metadata quality. It is a first attempt to qualitatively synthesize literature on metadata quality. The article emphasizes the importance of metadata quality research and the need to improve the flexibility of metadata quality assessment tools to facilitate better metadata quality assurance measures.

Open government data and resource allocation efficiency: evidence from China

ABSTRACT Data are among the most valuable resources. This paper, utilizing the China Tax Survey Database from 2009 to 2016, investigates the impact of Open Government Data (hereafter, OGD) on the efficiency of resource allocation among firms within the Chinese context. The findings indicate that OGD significantly reduces the deviation in firms’ factor inputs, thereby enhancing the efficiency of resource allocation. This is primarily achieved through the optimization of government-business relationships, the reduction of rent-seeking costs, and the decrease in information asymmetry. Given the inclusive nature of OGD, it has a more pronounced positive impact on disadvantaged firms and cities. Furthermore, while OGD directly improves representative firm’s TFP, its greater economic impact lies in elevating aggregate TFP by enhancing resource allocation efficiency. In the current global economy, highly dependent on data-driven processes, the conclusions of this paper provide a novel perspective on the role of OGD in enhancing productivity. This has significant implications for accelerating the implementation of open data policies and enhancing economic efficiency.

Research of open government data in China: A systematic literature study in public administration (2013–2023)

By building structures on open government data and illuminating the area of China with a systematic assessment of 220 papers published in major journals of public administration from 2013 to 2023, this article aims to bridge the research gap of open government data. It presents an overview of the landscape of Chinese OGD research and exposes the current gaps with the paths of unresolved research in the future by thoroughly examining the overall progress, theoretical topics, theoretical underpinnings, and methodologies of these studies. Combining the findings of this analysis with the overall trends in Chinese OGD development and the current international research frontiers on OGD, the article suggests that Chinese scholars should critically examine international theories and construct a development framework tailored to the specific needs of Chinese OGD. It also proposes the coordinate mechanism and the synergistic effect at the micro-level need to be further explored and use more advanced quantitative research methodologies to confirm theoretical and qualitative empirical findings.

Anti-corruption Policy Analysis: Indonesian Open Government Study

The central role of the Indonesian government in campaigning for open government is not in line with the findings of corruption cases in Indonesia. This research aims to analyze anti-corruption open government bibliometrics and the content of Indonesia’s open government anti-corruption policies. This research uses a qualitative approach with bibliometric analysis and content analysis methods. This study analyzes 200 papers on the Google Scholar database published in the 2018–2022 period and analyzes Indonesia’s open government anti-corruption policies. This research found 4587 citations, h-index 37, g-index 57, 172 keywords, 22 clusters, 2531 total link strengths, and 784 occurrences in open government anti-corruption papers. Anticorruption, data disclosure, open data, open government, e-government, information disclosure, transparency, open government data, public procurement, and beneficial ownership are the most popular open government anti-corruption trends. In the same time period, the Indonesian government established 10 anti-corruption policies covering public procurement, beneficial ownership, and elections. This research concludes that although the Indonesian government’s corruption index is unsatisfactory, anticorruption policies in Indonesia are in line with global anti-corruption trends, especially in several popular policies such as open data, transparency, information disclosure, public procurement, and beneficial ownership.
 Keywords: anti-corruption, open government Indonesia, bibliometric analysis, content analysis

Linked Open Government Data: Still a Viable Option for Sharing and Integrating Public Data?

Linked Data (LD) principles, when applied to Open Government Data (OGD), aim to make government data accessible and interconnected, unlocking its full potential and facilitating widespread reuse. As a modular and scalable solution to fragmented government data, Linked Open Government Data (LOGD) improve citizens’ understanding of government functions while promoting greater data interoperability, ultimately leading to more efficient government processes. However, despite promising developments in the early 2010s, including the release of LOGD datasets by some government agencies, and studies and methodological proposals by numerous scholars, a cursory examination of government websites and portals suggests that interest in this technology has gradually waned. Given the initial expectations surrounding LOGD, this paper goes beyond a superficial analysis and provides a deeper insight into the evolution of interest in LOGD by raising questions about the extent to which the dream of LD has influenced the reality of OGD and whether it remains sustainable.

How top leaders’ support affects open government data (OGD)-driven innovation capacity of firms: Based on the TOE framework perspective

Abstract The innovation value of open government data (OGD) drives firms to the participation in OGD-driven innovation. However, to fully excavate the innovation value of OGD for firms, it is essential to explore the factors and mechanisms that affect OGD-driven innovation capacity. On the basis of the technology–organization–environment (TOE) framework, a theoretical model affecting OGD-driven innovation capacity is proposed for analysis by partial least squares structural equation modeling with 236 sample data from China. The results indicate that top leaders’ support positively impacts on OGD-driven innovation capacity in firms. And we also prove that technical competence, organizational arrangement, and innovation support partially mediate the relationship between top leaders’ support and OGD-driven innovation capacity on the basis of the TOE framework. Consequently, the findings provide new research perspectives and practical guidance for promoting OGD-driven innovation capacity in firms.

Exploring government open data: understanding contributions of better walkability to real estate pricing

Exploring government open data: understanding contributions of better walkability to real estate pricing

Open government data use: The Brazilian states and federal district cases.

This paper presents the results of an online survey and subsequent interviews investigating whether, how, and why public administrations of Brazilian states and the federal district (Federation Units) use open government data. According to the literature reviewed, the questions were categorized into four big groups: benefits, barriers, enablers, and drivers. The Survey method, based on a questionnaire followed by interviews, was used to collect and analyze data from the open data officers of 26 Brazilian Federation Units. The use of open government data is controversial as responses from the questionnaires and interviews do not match and raise questions about how well-represented each Federation Unit was. Evidence of open government data use was found. Among others, findings showed that political leadership committed to using open data facilitates and motivates public agents to use these data. Additionally, interviews indicated that the lack of human resources with the knowledge, skills, and capabilities to use open data is a relevant barrier to data use. Findings also revealed that open government data mainly support policy and decision-making processes. This research contributed to the open data and public administration fields. It portrays diverse realities of open government data use and institutionalization in Brazilian state and district public administrations. In addition, it provides lists of open government data use benefits, barriers, drivers, and enablers from the perspective of these administrations so that they can benchmark against each other and improve their OGD use. For academia, this research provides empirical evidence of the factors influencing public administrations' use of open government data at the subnational level in Brazil. Even though Brazil ranks high on OGD global assessments, few studies on its use and reuse in the public sector were identified. This is one of the first academic studies focusing on open government data use in the country. It also contributes by offering to the academic community two instruments, a questionnaire and an interview protocol, which can be applied to other public settings to expand this study's results or open new research paths by applying them to other contexts.

Using Multilayer Perceptron Neural Network to Assess the Critical Factors of Traffic Accidents

This study is based on the traffic accident data of Taoyuan City from the government's open data. The study compiled the data set of traffic accidents in Taiwan from 2012 to 2017, and six classifiers were applied to evaluate the effectiveness of traffic accident prediction with the number of injuries as the prediction target. In order to verify the classifier's stability, cross-validation was used to evaluate the model during the training process, and the multilayer perceptron neural network (MLPNN) classifier performed best in testing the dataset's accuracy and evaluating the model's best performance. Then, a boosting ensemble learning approach and a combination of traffic accident factors improve the experiment's performance. According to this experiment, the results show that this study uses the Pearson Chi-square feature selection method to select important traffic factor combinations, and the boosting method indeed helps improve the effectiveness of the construction of the traffic accident model. Finally, the experimental results of the NN-MLP model have a correct rate of 77% and AUC is 78.7%. In constructing the model, it was found that the degree of injury, the part of the vehicle hit, the type of accident, the leading cause, the type of vehicle, and the period of the accident were the main factors causing dangerous traffic accidents. Doi: 10.28991/HIJ-2024-05-01-012 Full Text: PDF

Value co‐creation (VCC) and value co‐destruction (VCD) via open government data (OGD): Empirical case of Tanzania

AbstractHaving emphasized upon the potential benefits of Open Government Data (OGD) initiatives via value derivation and innovation pursuits of the stakeholders, it falls in place to complement this line of OGD research in the specific case of Tanzania, a developing country, to support the inferences. Specifically, it is important to understand the manner in which OGD VCC‐one of the hinges of OGD initiatives‐ and OGD VCD‐a possible fall out of OGD initiatives‐happens to pass. Thus, a content analysis of the interviews of 15 public officials and managers associated directly with the management and operationationalization of OGD initiatives is being done to arrive at the conclusions. Thus, the interviewees aver that OGD Value Co‐creation (VCC) may be facilitated on top‐priority bases by consistent marketing efforts by the government as also the partnerships with the key stakeholders of the OGD ecosystem, and, among the prominent Value Co‐Destruction (VCD) factors may be counted the issues linked with data privacy and resource restriction. Literature on OGD VCC is at a nascent stage and the one on OGD VCD is evolving. As an atypical empirical validation case vis‐a‐vis the emerging OGD VCC‐VCD research, the study is an additional contribution to the extant literature with specific reference to the developing country's experiences.

Are creative users more apt in reusing and adopting Open Government Data (OGD)? Gender differences

Open Government Data (OGD) has been considered as a potent instrument for value creation and innovation by a range of stakeholders. Given that individual ingenuity is a function of individual and environmental factors, it is important to understand how the OGD adoption and usage is a factor of creative performance behaviors (CPB), viz., Problem Identification (PI), Information Search (IS), Idea Generation (IG) and Idea Promotion (IP) as well as creative self-efficacy (CSE). Invoking the adapted Unified Theory of Acceptance and Use of Technology (UTAUT) constructs alongside the moderating effects of CPB and CSE constructs and also gender, the present study seeks to underline the behavioural intention towards OGD adoption and usage among 362 undergraduate and postgraduate university students in India. The guiding research question is: “Is there any difference among the males and females in terms of their OGD adoption and usage as far as their creative propensities are concerned?” Findings from the PLS-SEM (Partial Least Squares-Structural Equation Modeling) procedures show that there are gender differences across the CPB and CSE constructs. The study's contribution lies in furthering our understanding of OGD adoption and use with the additional determinants of creativity literature.

Role of perceived technological innovativeness (PTI) across genders vis-à-vis open government data (OGD) adoption and usage

PurposeThe purpose of the study is to understand the moderating impact of perceived technological innovativeness (PTI) in terms of gender differences as far as adoption and usage of Open Government Data (OGD) is concerned.Design/methodology/approachPartial least squares-structural equation modelling (PLS-SEM) methodological approach is used wherein the adapted unified theory of acceptance and use of technology (UTAUT) model is being used for estimating the research model.FindingsPTI has been attested to have moderating impact on the UTAUT-BI relationships in select cases (SI, SQ, IQ, TR-BI). Furthermore, gender differences were observed as far as far as the PTI's moderating role on UTAUT-BI relationships were concerned.Originality/valueWhile there has been ample impetus upon the OGD adoption and usage propensities underscoring the role of different variables, the present study's contribution lies in terms of understanding the moderating role of PTI as far as individual-centric analysis is concerned.