Big-data applications in the government sector

2014 ◽  
Vol 57 (3) ◽  
pp. 78-85 ◽  
Author(s):  
Gang-Hoon Kim ◽  
Silvana Trimi ◽  
Ji-Hyong Chung
Keyword(s):  
Big Data ◽  
Government Sector ◽  
Big Data Applications ◽  
The Government

scholarly journals Cloud Computing in Singapore: Key Drivers and Recommendations for a Smart Nation

2018 ◽  
Vol 6 (4) ◽  
pp. 39-47 ◽  
Author(s):  
Reuben Ng
Keyword(s):  
Public Policy ◽  
Cloud Computing ◽  
Big Data ◽  
Business Models ◽  
Fog Computing ◽  
Novel Technologies ◽  
Cloud Computing Adoption ◽  
Big Data Applications ◽  
Key Drivers ◽  
The Government

Cloud computing adoption enables big data applications in governance and policy. Singapore’s adoption of cloud computing is propelled by five key drivers: (1) public demand for and satisfaction with e-government services; (2) focus on whole-of-government policies and practices; (3) restructuring of technology agencies to integrate strategy and implementation; (4) building the Smart Nation Platform; (5) purpose-driven cloud applications especially in healthcare. This commentary also provides recommendations to propel big data applications in public policy and management: (a) technologically, embrace cloud analytics, and explore “fog computing”—an emerging technology that enables on-site data sense-making before transmission to the cloud; (b) promote regulatory sandboxes to experiment with policies that proactively manage novel technologies and business models that may radically change society; (c) on the collaboration front, establish unconventional partnerships to co-innovate on challenges like the skills-gap—an example is the unprecedented partnership led by the Lee Kuan Yew School of Public Policy with the government, private sector and unions.

scholarly journals Use of Big Data to Improve Environmental Sustainability in Developing Countries

2017 ◽  
Vol 12 (11) ◽  
pp. 249 ◽  
Author(s):  
Maged Adel Abdo Mukred ◽  
Zheng Jianguo
Keyword(s):  
Big Data ◽  
Multinational Corporations ◽  
Environmental Sustainability ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Government Sector ◽  
Wide Range ◽  
Private And Public ◽  
The Government ◽  
Set Up

Big data inhibits the ability to significantly impact a wide range of fields in an economy, from the government sector to commercial sectors like retail and healthcare. Not only has it altered the way companies assess their product’s demand and supply patterns but has also phenomenally helped in making the environment healthier in recent years. It carries the ability to identify valuable data from a huge dataset with exceptional parallel processing. This study presents the general introduction of big data bringing forth its various features and advantages along with the challenges which organizations face while using with respect to environmental sustainability. Observations have also been made on the findings of various researches, and studies and surveys performed by some international organizations in the recent years on the urgent need of taking necessary measures and initiatives to prevent further depletion of natural resources thus making the environment sustainable. Making the issue the study aim, future studies must intend to explore how multinational corporations can enhance environmental sustainability through big data analytics. Lastly, recommendations have been made to organisations– private and public in hiring adequate expertise and set-up, thereby making big data analytics more efficient and reliable.

BIG DATA: POTENTIAL, CHALLENGES, AND IMPLICATIONS IN OFFICIAL STATISTICS

2018 ◽  
Vol 6 ◽  
pp. 95-99
Author(s):  
Ogerta Elezaj ◽  
Dhimitri Tole
Keyword(s):  
Big Data ◽  
Public Institutions ◽  
Official Statistics ◽  
Government Sector ◽  
Open Debate ◽  
Critical Issues ◽  
Data Source ◽  
Data Explosion ◽  
The Government

The data explosion called “data deluge”, is already starting to transform public institutions redefining their way of producing statistics in response to Big Data. The use of Big Data is considered as an innovation in the production of official statistics facing a range of opportunities, challenges and risks. This “data deluge” requires a number of challenges to be addressed in various domains: technological, legal, methodological, and statistical. Even though big data is changing the paradigm of producing statistics in many public organizations, an open debate still exists involving both IT specialists and statisticians of national statistical institutions.  In this paper we will provide an overview regarding the concepts of Big Data as a data source in production of official statistics by government institutions with the main focus on providing a synoptic overview of opportunities, challenges and risks. Following this, in the next section we will analyse a case study related to the potential use of mobile positing data, and how this data could be used to produce national statistical indicators in the country. This study serves as an example to identify some critical issues on challenges and risks, draw conclusions and give recommendations on the proper ways to shift to Big Data paradigm usage in the government sector in Albania.

scholarly journals BIG DATA AS PREVENTION AND ERADICATION OF CRIMINAL ACTS ON HUMAN TRAFFICKING BASED ON INTERNET OF THINGS (IOT) AT DIRECTORATE GENERAL OF IMMIGRATION

2019 ◽  
Vol 2 (2) ◽  
pp. 73-82
Author(s):  
Muhamad Iskandar Wijaya
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Human Trafficking ◽  
The Internet ◽  
Complex Data ◽  
Government Sector ◽  
Directorate General ◽  
Perpetrators And Victims ◽  
The Government ◽  
The Internet Of Things

Human trafficking Crimes is an action against the law of the perpetrators organized for the purpose of exploitation or result of exploited persons. The number of victims of the Criminal Trade Force case occurred, requiring the government to use modern ways and techniques to prevent, arrest and eradicate the perpetrators and victims of the Human Trafficking Criminal Act. The implementation of the Internet Of Things (IoT)-based Big Data in the government sector is an appropriate step by building a data center and integrated applications between the system cores with complex data exchanges to be utilized by the Ministry, The agency or stakeholders responsible for the prevention, arrest and Eradication of human Trafficking crimes. The mode of the perpetrators who have many variations so that the government needs a complex system implementation, with the application Of Big Data based on the Internet Of Things (IoT) is believed to be able to be a reliable system for prevention, arrest and eradication of human trafficking criminal cases . Each mode is recorded in the main database so that it can be used as an analytical material to conduct supervision, control and policy determinants to realize Clean and Good Government for government agencies, especially in Directorate General of Immigration 

Using big data and social network analysis for cultural tourism planning in Hakka villages

2020 ◽  
Vol 21 (1) ◽  
pp. 99-114
Author(s):  
In-Lin Hu ◽  
Chen-Chi Chang ◽  
Yu-Hsun Lin
Keyword(s):  
Big Data ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Current Trend ◽  
Cultural Tourism ◽  
Tourism Planning ◽  
Big Data Applications ◽  
The Government ◽  
Set Up

Traveling in a Hakka village, the tourist can feel the culture of the Hakka in Taiwan and see traditional drama, artwork, handicrafts, and foods. The current trend in tourism planning is to incorporate online word of mouth into route design. This paper aims to examine common characteristics of Hakka village tourism development, identifying the need for planning and offering a model of the directions planning might take. It begins with big data collection of the online service and combines that with social network analysis. The results indicated that tourism planning with user's online search strategy will provide a better and more precise tour service. It is suggested that the government should set up the tour service center at the location identified as being in the structural hole of the tourism network. As cultural tourism continues to expand, big data applications will offer new opportunities and challenges to tourism planning.

The Nodality Disconnect of Data-Driven Government

2021 ◽  
pp. 009539972199868
Author(s):  
Walter Castelnovo ◽  
Maddalena Sorrentino
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Data Analytics ◽  
Data Driven ◽  
Future Role ◽  
Data Intensive ◽  
Big Data Applications ◽  
The Government ◽  
Technical Features ◽  
Open Question

We must ask critical questions regarding what actors are gaining influence, and regarding why the centrality of government is to be preserved in a data-intensive society. The article recognizes that the transformative capacity of big data—and its artificial intelligence (AI)-based companion data analytics—does not deterministically result from the technologies concerned. Instead, the direction of change depends on both the technical features and the intertwining of big data applications and governmental machinery. In short, the reconfiguration of the government nodality remains an open question. Overall, government is urged to think strategically about its future role within digital ecosystems.

scholarly journals A News Big Data Analysis of Issues in Higher Education in Korea amid the COVID-19 Pandemic

2021 ◽  
Vol 13 (13) ◽  
pp. 7347
Author(s):  
Jangwan Ko ◽  
Seungsu Paek ◽  
Seoyoon Park ◽  
Jiwoo Park
Keyword(s):  
Higher Education ◽  
Big Data ◽  
Data Analysis ◽  
College Education ◽  
Big Data Analysis ◽  
Second Phase ◽  
Public Attention ◽  
Job Market ◽  
Media Reports ◽  
The Government

This paper examines the main issues regarding higher education in Korea—where college education experienced minimal interruptions—during the COVID-19 pandemic through a big data analysis of news articles. By analyzing policy responses from the government and colleges and examining prominent discourses on higher education, it provides a context for discussing the implications of COVID-19 on education policy and what the post-pandemic era would bring. To this end, we utilized BIgKinds, a big data research solution for news articles offered by the Korea Press Foundation, to select a total of 2636 media reports and conducted Topic Modelling based on LDA algorithms using NetMiner. The analyses are split into three distinct periods of COVID-19 spread in the country. Some notable topics from the first phase are remote class, tuition refund, returning Chinese international students, and normalization of college education. Preparations for the College Scholastic Ability Test (CSAT), contact and contactless classes, preparations for early admissions, and supporting job market candidates are extracted for the second phase. For the third phase, the extracted topics include CSAT and college-specific exams, quarantine on campus, social relations on campus, and support for job market candidates. The results confirmed widespread public attention to the relevant issues but also showed empirically that the measures taken by the government and college administrations to combat COVID-19 had limited visibility among media reports. It is important to note that timely and appropriate responses from the government and colleges have enabled continuation of higher education in some capacity during the pandemic. In addition to the media’s role in reporting issues of public interest, there is also a need for continued research and discussion on higher education amid COVID-19 to help effect actual results from various policy efforts.

scholarly journals DaLiF: a data lifecycle framework for data-driven governments

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Syed Iftikhar Hussain Shah ◽  
Vassilios Peristeras ◽  
Ioannis Magnisalis
Keyword(s):  
Big Data ◽  
Data Management ◽  
Good Governance ◽  
Business Community ◽  
Data Driven ◽  
Governmental Organizations ◽  
Data Lifecycle ◽  
The Government ◽  
Data Ecosystem ◽  
Governance Transparency

AbstractThe public sector, private firms, business community, and civil society are generating data that is high in volume, veracity, velocity and comes from a diversity of sources. This kind of data is known as big data. Public Administrations (PAs) pursue big data as “new oil” and implement data-centric policies to transform data into knowledge, to promote good governance, transparency, innovative digital services, and citizens’ engagement in public policy. From the above, the Government Big Data Ecosystem (GBDE) emerges. Managing big data throughout its lifecycle becomes a challenging task for governmental organizations. Despite the vast interest in this ecosystem, appropriate big data management is still a challenge. This study intends to fill the above-mentioned gap by proposing a data lifecycle framework for data-driven governments. Through a Systematic Literature Review, we identified and analysed 76 data lifecycles models to propose a data lifecycle framework for data-driven governments (DaliF). In this way, we contribute to the ongoing discussion around big data management, which attracts researchers’ and practitioners’ interest.

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