Characteristics of Open Government Data (OGD) Around the World: A Country-based Comparative Meta-Analysis

Tang, Rong; Jiang, Jie

doi:10.2478/dim-2020-0026

Cited by 10 publications

(7 citation statements)

References 48 publications

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“…The creation of OGD portals or sites is used to implement an OGD. Tang & Jiang (2021) define OGDs in their research as sites or portals that allow the public to access government information or public data. Little attention has been given to the usage of OGD platforms and there is limited understanding of how these platforms for open data service innovation are controlled, where the nurturing of an installed base of diversified service innovators can lead to higher OGD usage (Bonina & Eaton, 2020).…”

Section: Website As Ogd's Initiativementioning

confidence: 99%

Developing a Framework of Citizen’s Engagement in Open Government Data’s Website

Ashahril,

Mat Isa,

Anwar

2023

E-BPJ

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Website is one of the OGD initiatives that provide input and spread information to the public. This research’s objective is to develop a framework for citizen engagement in using OGD’s website, i.e. Ministry’s websites. This research proposes a few combinations of determinants from the Theory of Human Behavior, Technology Acceptance Model (TAM), Theory of Planned Behaviour (TPB), Theory of Reasoned Action (TRA), and Information System Success Model (ISSM). This research will provide input and information on how the implementation of OGD in Malaysia can become a sustainable innovation in developing a user-friendly website to attract engagement from the public.

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Section: Website As Ogd's Initiativementioning

confidence: 99%

Developing a Framework of Citizen’s Engagement in Open Government Data’s Website

Ashahril,

Mat Isa,

Anwar

2023

E-BPJ

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“…Table 1 provides the definitions and examples of these file types. However, there are clear variations among world regions in terms of the number of data formats, datasets, and data categories [7,23].…”

Section: Open Government Data Practicementioning

confidence: 99%

“…The current concept of open data and particularly open government data (OGD) started to become visible and popular in 2009 with a number of governments in the developed world who announced new initiatives to open up their public information records such as the USA, UK, and New Zealand. These initiatives were triggered by the mandate for transparency and open government from the then American President Barack Obama administration, thus kick starting the Open Government Data Movement [6,7].…”

Section: Introductionmentioning

confidence: 99%

Open Government Data: Development, Practice, and Challenges

Abdelrahman¹

2022

Open Data

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This chapter explores the concept of open data with a focus on Open Government Data (OGD). The chapter presents an overview of the development and practice of Open Government Data at the international level. It also discusses the advantages and benefits of Open Government Data. The scope and characteristics of OGD, in addition to the perceived risks, obstacles and challenges are also presented. The chapter closes with a look at the future of open data and open government data in particular. The author adopted literature review as a method and a tool of data collection for the purpose of writing this chapter.

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“…Machine learning, a subset of artificial intelligence, has emerged as a potent tool in the fight against COVID-19. Its ability to process vast datasets [4], identify patterns [5], and make predictions has been harnessed for surveillance [6], forecasting [7], and patient management [8]. Integrating machine learning into healthcare systems has enabled real-time monitoring of the pandemic's progression and the identification of potential hotspots [9].…”

Section: Introductionmentioning

confidence: 99%

Comparative analysis of the machine learning models determining COVID-19 patient risk levels

Bazilevych,

Kyrylenko,

Parfenyuk

et al. 2023

reks

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The COVID-19 pandemic has posed unprecedented challenges to global healthcare systems, emphasizing the need for predictive tools for resource allocation and patient care. This study delves into the potential of machine learning models to predict the risk levels of COVID-19 patients using a comprehensive dataset. This study aimed to evaluate and compare the efficacy of three distinct machine learning methodologies – Bayesian Criterion, Logistic Regression, and Gradient Boosting – in predicting the risk associated with COVID-19 patients based on their symptoms, status, and medical history. This research is targeted at the process of patient state determination. The research subjects are machine learning methods for patient state determination. To achieve the aim of the research, the following tasks have been formulated: methods and models of the COVID-19 patients state determination should be analyzed; classification model of the patient state determination based on Bayes criterion should be developed; classification model of the patient state determination based on logistic regression should be developed; classification model of the patient state determination based on gradient boosting should be developed; the information system should be developed; the experimental study based on machine learning methods should be provided; and the results of the experimental study should be analyzed. Methods: using a dataset provided by the Mexican government, which encompasses over a million unique patients with 21 distinct features, we developed an information system in C# programming language. This system allows users to select their preferred method for risk calculation, offering a real-time decision-making tool for healthcare professionals. Results: All models demonstrated commendable accuracy levels. However, subtle differences in their performance metrics, such as sensitivity, precision, and the F1-score, were observed. The Gradient Boosting method slightly outperformed the other models in terms of overall accuracy. Conclusions: While each model showcased its merits, the choice of method should be based on the specific needs and constraints of the healthcare system. The Gradient Boosting method emerged as marginally superior in this study. This research underscores the potential of machine learning in enhancing pandemic response strategies, offering both scientific insights and practical tools for healthcare professionals.

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Characteristics of Open Government Data (OGD) Around the World: A Country-based Comparative Meta-Analysis

Cited by 10 publications

References 48 publications

Developing a Framework of Citizen’s Engagement in Open Government Data’s Website

Developing a Framework of Citizen’s Engagement in Open Government Data’s Website

Open Government Data: Development, Practice, and Challenges

Comparative analysis of the machine learning models determining COVID-19 patient risk levels

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