On the use of big data frameworks for big service composition

2020 ◽  
Vol 166 ◽  
pp. 102732 ◽  
Author(s):  
Mokhtar Sellami ◽  
Haithem Mezni ◽  
Mohand Said Hacid
Keyword(s):  
Big Data ◽  
Service Composition ◽  
Big Service

Fast approaches for semantic service composition in big data environment

2019 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Jun Huang ◽  
Yide Zhou ◽  
Qiang Duan ◽  
Cong Cong Xing
Keyword(s):  
Big Data ◽  
Service Composition ◽  
Data Environment ◽  
Semantic Service

A Service-Oriented Foundation for Big Data

2020 ◽  
Vol 10 (1) ◽  
pp. 1-17
Author(s):  
Zhaohao Sun
Keyword(s):  
Big Data ◽  
Business Intelligence ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Business Analytics ◽  
Technological Characteristics ◽  
Service Oriented ◽  
Technological Level ◽  
Multi Level ◽  
Big Service

This paper provides a service-oriented foundation for big data. The foundation has two parts. Part 1 reveals 10 big characteristics of big data. Part 2 presents a service-oriented framework for big data. The framework has fundamental, technological, and socio-economic levels. The fundamental level has four big fundamental characteristics of big data: big volume, big velocity, big variety, and big veracity. The technological level consists of three big technological characteristics of big data: Big intelligence, big analytics, big infrastructure. The socioeconomic level has three big socioeconomic characteristics of big data: big service, big value, and big market. The article looks at each level of the proposed framework from a service-oriented perspective. The multi-level framework will help organizations and researchers understand how the 10 big characteristics relate to big opportunities, big challenges, and big impacts arising from big data. The proposed approach in this paper might facilitate the research and development of big data, big data analytics, business intelligence, and business analytics.

Fast approaches for semantic service composition in big data environment

2019 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Qiang Duan ◽  
Cong Cong Xing ◽  
Yide Zhou ◽  
Jun Huang
Keyword(s):  
Big Data ◽  
Service Composition ◽  
Data Environment ◽  
Semantic Service

Big Data for Digital Government

2014 ◽  
Vol 1 (1) ◽  
pp. 1-14 ◽  
Author(s):  
Yu-Che Chen ◽  
Tsui-Chuan Hsieh
Keyword(s):  
Big Data ◽  
Data Management ◽  
Governance Structure ◽  
Future Research ◽  
Business Analytics ◽  
Digital Government ◽  
Privacy And Security ◽  
Critical Issues ◽  
And Performance ◽  
Big Service

“Big data” is one of the emerging and critical issues facing government in the digital age. This study first delineates the defining features of big data (volume, velocity, and variety) and proposes a big data typology that is suitable for the public sector. This study then examines the opportunities of big data in generating business analytics to promote better utilization of information and communication technology (ICT) resources and improved personalization of e-government services. Moreover, it discusses the big data management challenges in building appropriate governance structure, integrating diverse data sources, managing digital privacy and security risks, and acquiring big data talent and tools. An effective big data management strategy to address these challenges should develop a stakeholder-focused and performance-oriented governance structure and build capacity for data management and business analytics as well as leverage and prioritize big data assets for performance. In addition, this study illustrates the opportunities, challenges, and strategy for big service data in government with the E-housekeeper program in Taiwan. This brief case study offers insight into the implementation of big data for improving government information and services. This article concludes with the main findings and topics of future research in big data for public administration.

A Service-Oriented Foundation for Big Data

2022 ◽  
pp. 869-887
Author(s):  
Zhaohao Sun
Keyword(s):  
Big Data ◽  
Big Data Analytics ◽  
Socioeconomic Level ◽  
Business Analytics ◽  
Socioeconomic Characteristics ◽  
Fundamental Level ◽  
Service Oriented ◽  
Technological Level ◽  
Multi Level ◽  
Big Service

This paper provides a service-oriented foundation for big data. The foundation has two parts. Part 1 reveals 10 big characteristics of big data. Part 2 presents a service-oriented framework for big data. The framework has fundamental, technological, and socio-economic levels. The fundamental level has four big fundamental characteristics of big data: big volume, big velocity, big variety, and big veracity. The technological level consists of three big technological characteristics of big data: Big intelligence, big analytics, big infrastructure. The socioeconomic level has three big socioeconomic characteristics of big data: big service, big value, and big market. The article looks at each level of the proposed framework from a service-oriented perspective. The multi-level framework will help organizations and researchers understand how the 10 big characteristics relate to big opportunities, big challenges, and big impacts arising from big data. The proposed approach in this paper might facilitate the research and development of big data, big data analytics, business intelligence, and business analytics.

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