scholarly journals Industrial Value Chain Model and Big Data Application for developing green agriculture in China

2021 ◽  
Vol 1883 (1) ◽  
pp. 012117
Author(s):  
Die Hu ◽  
Yuxue Chen ◽  
Menghan Hu
Keyword(s):  
Big Data ◽  
Value Chain ◽  
Chain Model ◽  
Data Application ◽  
Big Data Application ◽  
Industrial Value Chain

scholarly journals Big Data Analytic Framework for Organizational Leverage

2021 ◽  
Vol 11 (5) ◽  
pp. 2340
Author(s):  
Sanjay Mathrani ◽  
Xusheng Lai
Keyword(s):  
Big Data ◽  
Web Sites ◽  
Big Data Analytics ◽  
Building Blocks ◽  
Application Service ◽  
Data Application ◽  
Other Information ◽  
Big Data Application ◽  
Diverse Data ◽  
Framework System

Web data have grown exponentially to reach zettabyte scales. Mountains of data come from several online applications, such as e-commerce, social media, web and sensor-based devices, business web sites, and other information types posted by users. Big data analytics (BDA) can help to derive new insights from this huge and fast-growing data source. The core advantage of BDA technology is in its ability to mine these data and provide information on underlying trends. BDA, however, faces innate difficulty in optimizing the process and capabilities that require merging of diverse data assets to generate viable information. This paper explores the BDA process and capabilities in leveraging data via three case studies who are prime users of BDA tools. Findings emphasize four key components of the BDA process framework: system coordination, data sourcing, big data application service, and end users. Further building blocks are data security, privacy, and management that represent services for providing functionality to the four components of the BDA process across information and technology value chains.

Preliminary Benefits of Big Data in the Construction Industry: A Case Study

2022 ◽  
pp. 1-11
Author(s):  
Bernard Tuffour Atuahene ◽  
Sittimont Kanjanabootra ◽  
Thayaparan Gajendran
Keyword(s):  
Big Data ◽  
Construction Industry ◽  
Construction Projects ◽  
Big Data Applications ◽  
Data Application ◽  
Construction Firm ◽  
Big Data Application ◽  
Tangible Benefit ◽  
Design Construction

Big data applications consist of i) data collection using big data sources, ii) storing and processing the data, and iii) analysing data to gain insights for creating organisational benefit. The influx of digital technologies and digitization in the construction process includes big data as one newly emerging digital technology adopted in the construction industry. Big data application is in a nascent stage in construction, and there is a need to understand the tangible benefit(s) that big data can offer the construction industry. This study explores the benefits of big data in the construction industry. Using a qualitative case study design, construction professionals in an Australian Construction firm were interviewed. The research highlights that the benefits of big data include reduction of litigation amongst projects stakeholders, enablement of near to real-time communication, and facilitation of effective subcontractor selection. By implication, on a broader scale, these benefits can improve contract management, procurement, and management of construction projects. This study contributes to an ongoing discourse on big data application, and more generally, digitization in the construction industry.

scholarly journals Federated Learning in Big Data Application and Sharing

2020 ◽  
Author(s):  
Jing Yang ◽  
Quan Zhang ◽  
Kunpeng Liu ◽  
Peng Jin ◽  
Guoyi Zhao
Keyword(s):  
Big Data ◽  
Data Privacy ◽  
The State ◽  
Ideal Model ◽  
Local Data ◽  
Data Safety ◽  
Big Data Applications ◽  
Data Application ◽  
Big Data Application ◽  
Uniform Model

In recent years, electricity big data has extensive applications in the grid companies across the provinces. However, certain problems are encountered including, the inability to generate an ideal model using the isolated data possessed by each company, and the priority concerns for data privacy and safety during big data application and sharing. In this pursuit, the present research envisaged the application of federated learning to protect the local data, and to build a uniform model for different companies affiliated to the State Grid. Federated learning can serve as an essential means for realizing the grid-wide promotion of the achievements of big data applications, while ensuring the data safety.

scholarly journals Research Progress and Advantage Analysis of Big Data Application in Chinese Academic Journals

2020 ◽  
Author(s):  
Qin Wu ◽  
Hui Wu
Keyword(s):  
Big Data ◽  
Scientific Data ◽  
Research Progress ◽  
Academic Journals ◽  
Bibliometric Method ◽  
Data Application ◽  
Quantitative Visualization ◽  
Big Data Application ◽  
Social Units ◽  
Relationship Of

The mining and application of big data in academic journals can accelerate the construction of data journals, enhance journal’s influence, and promote the sharing and dissemination of scientific data in academic journals worldwide. This paper uses bibliometric method to retrieve published articles with the theme of big data and journal in CNKI database, analyzes the academic achievements of the development of academic journals with the application of big data in the recent five years using quantitative visualization analysis, expounds the research progress of academic journals in big data field, and discusses the advantages of big data application in periodical industry. The results show that: study on the application of big data in academic journals are gradually deepening and scientific, and the relevant research still needs more financial fund from the state and social units, big data has prominent advantages such as accuracy, scientificity and value maximization in the workflows of academic journals. The mining and application of massive data is very important for promoting the development of high-quality academic journals and optimizing the supply-demand relationship of knowledge services of academic journals.

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