Development Of Big Data Research Articles

Enhancing environmental management through big data: spatial analysis of urban ecological governance and big data development

Introduction: This research focuses on exploring the impact of Big Data Development (BDD) on Urban Ecological Governance Performance (EGP), with a particular emphasis on environmental dimensions within and among various regions. It aims to understand the complex interplay between technological advancements, urbanization, and environmental management in the context of urban ecological governance.Methods: Employing the Spatial Durbin Model (SDM), the study rigorously investigates the effects of BDD on EGP. It also examines the mediating role of Industrial Structure Level (ISL) and the moderating effects of both Level of Technological Investment (LTI) and Urbanization Level (URB), to provide a comprehensive analysis of the factors influencing urban ecological governance.Results: The findings reveal that big data significantly strengthens urban ecological governance, characterized by pronounced spatial spillover effects, indicating interregional interdependence in environmental management. Urbanization level notably amplifies the influence of BDD on EGP, whereas the magnitude of technological investments does not show a similar effect. Moreover, the industrial structure acts as a partial mediator in the relationship between BDD and EGP, with this mediating role demonstrating variability across different regions.Discussion: The research highlights the critical role of big data in enhancing urban ecological governance, particularly in terms of environmental aspects. It underscores the importance of technological advancements and urbanization in augmenting the effectiveness of ecological governance. The variability of the mediating role of industrial structure across regions suggests the need for tailored strategies in implementing big data initiatives for environmental management.

Big Data for Public Domain: A bibliometric and visualized study of the scientific discourse during 2000–2020

This article aims to investigate the trend of scientific publications under ‘big data and policy’ research during the last two decades, including the dynamics of the network structure of researchers and the institutions. Bibliometrics is utilized as a tool to reveal the dynamics of scientific discussions that occur through articles, published in international journals indexed/contained in the Scopus database; meanwhile, the analysis visualization is performed by using VOSviewer 1.6.16. The search results indicate that the United States serves as the country of origin for most productive author affiliations in publishing articles, the University of Oxford (United Kingdom) serves as the home institution for most productive author affiliations, and Williamson, B., from the University of Edinburgh (United Kingdom), is considered as the most prolific writer. In addition, the Swiss Sustainability Journal from MDPI is cited as the source for the most widely discussed publication topic in its journals. Further, ‘Big Data for Development: A Review of Promises and Challenges’ is regarded as the article with the most references. Additionally, the most discussed topics on ‘big data and policy’ include smart cities, open data, privacy, artificial intelligence, machine learning, and data science.

Datafication, value and power in developing countries: Big data in two Indian public service organizations

AbstractMotivationDatafication—the growing presence, use and impact of data in social processes—is spreading to all sectors in developing countries. But, to date, there are few analyses of real‐world experiences of datafication in developing country organizations.PurposeWe address this knowledge gap by analysing evidence of big data in practice in relation to three key issues: implementation, value and power.Approach and methodsUsing interview, observation and documentary sources, we analyse the implementation and impact of big data systems in Indian electricity and transport public sector organizations.FindingsBig data systems have been much slower to implement than anticipated, and the article exposes the nature and scale of the implementation challenge facing such systems. These are already delivering value for some managers within public service organizations but are, as yet, more operational than strategic and incremental not transformative. Big data systems are facilitating a shift in power from the public sector to the private sector, and from labour and middle management to panopticon‐type control by central managers. Big data intersects with politics especially around the imaginaries of wider stakeholders, changing their view of the financial and political issues that technology can address.Policy implicationsPolicy‐makers and practitioners can better understand and plan for big data in development using three frameworks presented in the article: information value chain, decision pyramid, and big data–power model. These expose key issues of implementation, organizational value and power that must be incorporated into big data policy and projects. Benefits of datafication have been largely restricted to senior managers, private contractors and some politicians. To spread these to other stakeholders, including workers and citizens, action must be taken to address both practical and political issues arising in the datafication of development.

Application of Big data for Development of Korean Christian research

Application of Big data for Development of Korean Christian research

Big data for development: applications and techniques

With the explosion of social media sites and proliferation of digital computing devices and Internet access, massive amounts of public data is being generated on a daily basis. Efficient techniques/algorithms to analyze this massive amount of data can provide near real-time information about emerging trends and provide early warning in case of an imminent emergency (such as the outbreak of a viral disease). In addition, careful mining of these data can reveal many useful indicators of socioeconomic and political events, which can help in establishing effective public policies. The focus of this study is to review the application of big data analytics for the purpose of human development. The emerging ability to use big data techniques for development (BD4D) promises to revolutionalize healthcare, education, and agriculture; facilitate the alleviation of poverty; and help to deal with humanitarian crises and violent conflicts. Besides all the benefits, the large-scale deployment of BD4D is beset with several challenges due to the massive size, fast-changing and diverse nature of big data. The most pressing concerns relate to efficient data acquisition and sharing, establishing of context (e.g., geolocation and time) and veracity of a dataset, and ensuring appropriate privacy. In this study, we provide a review of existing BD4D work to study the impact of big data on the development of society. In addition to reviewing the important works, we also highlight important challenges and open issues.

Big Data for Development: A Review of Promises and Challenges

The article uses a conceptual framework to review empirical evidence and some 180 articles related to the opportunities and threats of Big Data Analytics for international development. The advent of Big Data delivers a cost‐effective prospect for improved decision‐making in critical development areas such as healthcare, economic productivity and security. At the same time, the well‐known caveats of the Big Data debate, such as privacy concerns and human resource scarcity, are aggravated in developing countries by long‐standing structural shortages in the areas of infrastructure, economic resources and institutions. The result is a new kind of digital divide: a divide in the use of data‐based knowledge to inform intelligent decision‐making. The article systematically reviews several available policy options in terms of fostering opportunities and minimising risks.

Is bigger better? The emergence of big data as a tool for international development policy

The use of digital communication technologies, and of mobile phones in particular, has seen an exponential rise in low- and middle-income countries over the last decade. These data, emitted as a byproduct of technologies such as mobile phone location information and calling metadata, have the potential to fill some of the problematic gaps in data resources available to country policymakers and international development organisations. Using three examples of current big data initiatives in the international development field, we examine the implications of these new types of data for development policy and planning: their advantages and drawbacks, emerging practices relating to their use, and how they potentially influence ideas and policies of development. We also assess the politics of these new types of digital data, which are often collected and processed by corporations or by researchers in industrialised countries. Our analysis indicates that these new data sources already represent an important complement to country-level statistics, but that there are currently important challenges which will need to addressed if the promises of big data in development are to be fulfilled.

Big Data for Development in China

Big Data for Development in China

Big Data for Development: From Information - to Knowledge Societies

The article uses an established three-dimensional conceptual framework to systematically review literature and empirical evidence related to the prerequisites, opportunities, and threats of Big Data Analysis for international development. On the one hand, the advent of Big Data delivers the cost-effective prospect to improve decision-making in critical development areas such as health care, employment, economic productivity, crime and security, and natural disaster and resource management. This provides a wealth of opportunities for developing countries. On the other hand, all the well-known caveats of the Big Data debate, such as privacy concerns, interoperability challenges, and the almighty power of imperfect algorithms, are aggravated in developing countries by long-standing development challenges like lacking technological infrastructure and economic and human resource scarcity. This has the potential to result in a new kind of digital divide: a divide in data-based knowledge to inform intelligent decision-making. This shows that the exploration of data-based knowledge to improve development is not automatic and requires tailor-made policy choices that help to foster this emerging paradigm.

Big Data for Development

Big DataVol. 1, No. 1 PerspectiveBig Data for DevelopmentRobert KirkpatrickRobert KirkpatrickSearch for more papers by this authorPublished Online:13 Feb 2013https://doi.org/10.1089/big.2012.1502AboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View article"Big Data for Development." , 1(1), pp. 3–4FiguresReferencesRelatedDetailsCited byAdoption of big data analytics in marketing: an analysis in Bangladesh28 November 2022 | Journal of Data, Information and Management, Vol. 4, No. 3-4Detailed Investigation of Influence of Machine learning (ML) and Big Data on Digital Transformation in MarketingInclusive Smart Cities: Beyond Voluntary Corporate Data Sharing21 July 2021 | Sustainability, Vol. 13, No. 15Semi-automatic Scholar Encyclopedia Generating System Based on Scholar Social NetworkThe Social Dilemma of Big Data: Donating Personal Data to Promote Social WelfareSSRN Electronic Journal, Vol. 15Data driven social partnerships: Exploring an emergent trend in search of research challenges and questionsGovernment Information Quarterly, Vol. 36, No. 1Data & Policy : A new venue to study and explore policy–data interaction10 June 2019 | Data & Policy, Vol. 1A Research Roadmap to Advance Data Collaboratives Practice as a Novel Research DirectionInternational Journal of Electronic Government Research, Vol. 14, No. 3Citizen science provides a reliable and scalable tool to track disease-carrying mosquitoes24 October 2017 | Nature Communications, Vol. 8, No. 1Unified Retrieval Model of Big Data8 October 2016Crisis analytics: big data-driven crisis response17 August 2016 | Journal of International Humanitarian Action, Vol. 1, No. 1Big data for development: applications and techniques1 July 2016 | Big Data Analytics, Vol. 1, No. 1Advanced SolutionsThe FutureThe Governance of Big Data: Perspectives and IssuesSSRN Electronic Journal Volume 1Issue 1Mar 2013 InformationCopyright 2013, Mary Ann Liebert, Inc.To cite this article:Robert Kirkpatrick.Big Data for Development.Big Data.Mar 2013.3-4.http://doi.org/10.1089/big.2012.1502Published in Volume: 1 Issue 1: February 13, 2013Online Ahead of Print:November 7, 2012PDF download