Big Data and cloud computing: innovation opportunities and challenges
By Chaowei Phil Yang, Qunying Huang, Zhenlong Li, Kai Liu, Fei Hu. International Journal of Digital Earth, 2017
727 citations recorded by the source corpus.
ABSTRACT Big Data has emerged in the past few years as a new paradigm providing abundant data and opportunities to improve and/or enable research and decision-support applications with unprecedented value for digital earth applications including business, sciences and engineering. At the same time, Big Data presents challenges for digital earth to store, transport, process, mine and serve the data. Cloud computing provides fundamental support to address the challenges with shared computing resources including computing, storage, networking and analytical software; the application of these resources has fostered impressive Big Data advancements. This paper surveys the two frontiers – Big Data and cloud computing – and reviews the advantages and consequences of utilizing cloud computing to tackling Big Data in the digital earth and relevant science domains. From the aspects of a general introduction, sources, challenges, technology status and research opportunities, the following observations are offered: (i) cloud computing and Big Data enable science discoveries and application developments; (ii) cloud computing provides major solutions for Big Data; (iii) Big Data, spatiotemporal thinking and various application domains drive the advancement of cloud computing and relevant technologies with new requirements; (iv) intrinsic spatiotemporal principles of Big Data and geospatial sciences provide the source for finding technical and theoretical solutions to optimize cloud computing and processing Big Data; (v) open availability of Big Data and processing capability pose social challenges of geospatial significance and (vi) a weave of innovations is transforming Big Data into geospatial research, engineering and business values. This review introduces future innovations and a research agenda for cloud computing supporting the transformation of the volume, velocity, variety and veracity into values of Big Data for local to global digital earth science and applications.
Subfields: Information Systems, Information Systems and Management
View Paper: https://www.semanticscholar.org/paper/116927fbe4c9732fd1e392035a100c33b14e9d59
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In Information Systems
- Dinh C. Nguyen
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- Edmundo Roberto Mauro Madeira
- Luiz Fernando Bittencourt
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- Omer Farooq Rana
In Information Systems and Management
Citations in the corpus
- Land cover 2.0 (2018, background): “Cloud-based computing systems increasingly enable users to process data and develop land cover products without signi fi cant investments in computing infrastructure (e.g., Gorelick et al. 2017; Yang et al. 2017a).”
- A Survey on Blockchain for Big Data: Approaches, Opportunities, and Future Directions (2020, background): “Blockchain provides decentralization facility for a transparent and secure distributed personal data [67].”
- The Internet of Things, Fog and Cloud Continuum: Integration and Challenges (2018, background): “Data locality is related to the capability of moving the computation close to where the actual data is being created or acquired, rather than transferring large amounts of data to a centralized computational resource [85] .”